Changes in elbow flexion EMG morphology during adjustment of deep brain stimulator in advanced Parkinson's disease.

OBJECTIVE: Deep brain stimulation (DBS) is an effective treatment for motor symptoms of advanced Parkinson's disease (PD). Currently, DBS programming outcome is based on a clinical assessment. In an optimal situation, an objectively measurable feature would assist the operator to select the appropriate settings for DBS. Surface electromyographic (EMG) measurements have been used to characterise the motor symptoms of PD with good results; with proper methodology, these measurements could be used as an aid to program DBS.
METHODS: Muscle activation measurements were performed for 13 patients who had advanced PD and were treated with DBS. The DBS pulse voltage, frequency, and width were changed during the measurements. The measured EMG signals were analysed with parameters that characterise the EMG signal morphology, and the results were compared to the clinical outcome of the adjustment.
RESULTS: The EMG signal correlation dimension, recurrence rate, and kurtosis changed significantly when the DBS settings were changed. DBS adjustment affected the signal recurrence rate the most. Relative to the optimal settings, increased recurrence rates (median ± IQR) 1.1 ± 0.5 (-0.3 V), 1.3 ± 1.1 (+0.3 V), 1.7 ± 0.4 (-30 Hz), 1.7 ± 0.8 (+30 Hz), 2.0 ± 1.7 (+30 μs), and 1.5 ± 1.1 (DBS off) were observed. With optimal stimulation settings, the patients' Unified Parkinson's Disease Rating Scale motor part (UPDRS-III) score decreased by 35% on average compared to turning the device off. However, the changes in UPRDS-III arm tremor and rigidity scores did not differ significantly in any settings compared to the optimal stimulation settings.
CONCLUSION: Adjustment of DBS treatment alters the muscle activation patterns in PD patients. The changes in the muscle activation patterns can be observed with EMG, and the parameters calculated from the signals differ between optimal and non-optimal settings of DBS. This provides a possibility for using the EMG-based measurement to aid the clinicians to adjust the DBS.

Introduction

Parkinson’s disease (PD) is a progressive neurodegenerative disease that has an increased prevalence with age. The main motor symptoms are resting tremor, bradykinesia, and rigidity, but they may be preceded by non-motor symptoms for over a decade [1]. The motor symptoms are usually unilateral at onset. There are no curative or disease-halting treatments to PD, but the quality of life of patients can be improved by relieving the symptoms with appropriate medication. Levodopa is the most efficient medication treatment for PD and it is normally used along with a combination of dopamine agonists and MAO-B inhibitors. Levodopa dosage must be increased as the disease progresses to maintain therapeutic response. Almost half of the patients develop motor fluctuations, dyskinesias, or both within five years after the initiation of levodopa treatment [2].

Deep brain stimulation (DBS) is currently the most efficient treatment for motor symptoms of advanced PD [3-5]. DBS treatment must be individually programmed for the best outcome. Programming of the DBS is an optimisation task that aims to minimise patients’ symptoms while avoiding side effects that the stimulation may cause. The programming operator is usually a trained clinician. Even though there are strategies to ascertain the best DBS settings, the programming may be time consuming due to a multitude of parameters that require to be adjusted [5, 6]. Clinical evaluation during programming is based on the operator’s observation and UPDRS-III score. While this is currently the best means to assess patients, subtask scores used to assess limb tremor and rigidity are coarse and there is variation in assessment among clinicians [7]. The symptoms vary on a daily basis and challenge the clinical assessment, which is typically performed within a short time frame. Thus, the operator has to rely partially on patients’ own subjective assessment of the symptoms. The programming of DBS is becoming increasingly complicated due to the newest type of stimulators with customisable pulse types [8] and directional electrodes [9]. Objective measurement-based assessment of symptoms would be beneficial for optimising among different settings. Further, methods with the ability for long-term monitoring of the symptoms could be helpful aids in clinical decision-making.

Surface electromyographic (EMG) signals of PD patients have been found to have lower complexity and contain more rhythmic bursts and tonic background activity compared to signals of healthy controls [10-12]. Moreover, the muscle activation patterns of patients with PD also differ from those of patients with other motor diseases with similar symptoms [13-15]. Studies on elbow flexion-extension have reveal that EMG signals in PD contain more recurring patterns due to motor unit synchronization [10] and that DBS decreases these patterns and increases the sample entropy of EMG signals [16]. Although the effect of DBS on muscle activity has been studied in a few EMG-based studies [16, 17], the studies do not include DBS programming. Rissanen et al. report a difference in isometric EMG signals between lower and upper limbs during the programming of DBS [18]. EMG-based measurements accompanied with amplitude, frequency, and non-linear analysis have been used in the quantification of symptoms of PD [16, 19, 20].

EMG measurements are useful for evaluating muscle activity in patients with PD since they are non-invasive, easy to produce, and cost-effective. Thus, EMG measurement during dynamic arm movement could be a feasible method for assessing changes in muscle activity while programming DBS. In this study, the muscle activity of 13 patients with advanced PD were measured during the DBS programming session. The measurements were performed with seven different DBS settings that change the pulse voltage, frequency, and width within a clinical range. The aim of this work was to determine whether EMG measurement can quantify the difference among the DBS settings.

Materials and methods

The study was approved by the Research Ethics Committee of the Northern Savo Hospital District. All patients provided written informed consent before the measurement. An EMG measurement was performed for 13 patients with advanced PD to observe the muscle activation patterns while adjusting the DBS. The demographics of the patients are presented in Table 1. The patients had implanted STN-DBS (Kinetra or Activa PC Neurostimulator, Medtronic Inc, Minneapolis, USA) because of severe motor fluctuations, wearing off phases, dyskinesias, tremor, or rigidity. At the time of measurement, the age of the patients was (58 ± 11) (mean ± SD) and the duration from diagnosis (11 ± 5) years. The severity of the motor symptoms was assessed with UDPRS-III motor in the range of 0 − 108. Patients’ UPDRS-III motor score with DBS off was (36 ± 12) and motor score with DBS on was (23 ± 8). The patients continued to have their current antiparkinsonian medication throughout the measurement. The measurements were performed at the BioMag laboratory, Helsinki, by an experienced neurologist (adjustment of DBS, assessment of UPDRS-III), and a physicist (EMG recordings).

Table 1

Patients, UPDRS-III score, and DBS details.

DBS months refer to number of months after DBS implantation. UPDRS-III assessment could not be completed on patients 2 and 13 due to side effects and notion ≥ is used.

Patient	Age	Sex	UPDRS III on(off)	DBS months		Optimal settings of DBS: voltage, frequency, pulse width
1	46	M	21(36)	5	Right:	3.5 V, 130 Hz, 60 μs
					Left:	3.7 V, 130 Hz, 60 μs
2	59	F	26(≥ 37)	34	Right:	3.4 V, 130 Hz, 60 μs
					Left:	3.2 V, 130 Hz, 60 μs
3	64	M	22(29)	23	Right:	3.1 V, 130 Hz, 60 μs
					Left:	3.3 V, 130 Hz, 60 μs
4	58	F	10(18)	5	Right:	2.6 V, 130 Hz, 60 μs
					Left:	2.5 V, 130 Hz, 60 μs
5	64	M	16(36)	2	Right:	2.8 V, 130 Hz, 60 μs
					Left:	3.4 V, 130 Hz, 90 μs
6	66	M	21(28)	8	Right:	2.5 V, 130 Hz, 60 μs
					Left:	2.5 V, 130 Hz, 60 μs
7	66	M	34(45)	21	Right:	2.3 V, 130 Hz, 60 μs
					Left:	3.3 V, 130 Hz, 60 μs
8	38	M	27(50)	22	Right:	3.4 V, 130 Hz, 60 μs
					Left:	3.4 V, 130 Hz, 60 μs
9	71	M	22(36)	4	Right:	3.1 V, 130 Hz, 60 μs
					Left:	3.4 V, 130 Hz, 60 μs
10	47	M	31(38)	4	Right:	2.3 V, 180 Hz, 60 μs
					Left:	2.5 V, 180 Hz, 60 μs
11	58	F	12(23)	6	Right:	2.4 V, 130 Hz, 60 μs
					Left:	2.4 V, 130 Hz, 60 μs
12	70	M	31(62)	30	Right:	2.7 V, 130 Hz, 60 μs
					Left:	3.3 V, 130 Hz, 60 μs
13	45	M	31(≥ 36)	29	Right:	3.1 V, 120 Hz, 60 μs
					Left:	3.1 V, 120 Hz, 60 μs

Measurement protocol

The surface of the biceps brachii muscle beneath the measurement electrodes was properly cleaned with wet ethanol cotton pads. Large disposable Ag/AgCl surface electrodes (Medicotest M-00-S) with an interelectrode distance of 3 cm were used to improve the signal quality and increase the number of recorded motor units. The electrodes were placed on top of left and right biceps brachii muscle, below the belly of the muscle. Bipolar configuration was used and the reference electrode was placed on an inactive point on the lateral side of the brachium, 6–7 cm (depending on the patient’s arm size) from the recording electrodes. The signals were recorded with ME6000 biosignal monitor (Bittium Corporation, Oulu, Finland) with a sampling rate of 1000 Hz and resolution 1 μV.

The patients were made to sit on an ordinary wooden chair without armrests during the measurement. The task consisted of 7–8 repetitions of elbow flexion and extension, with elbow staying in place next to the torso. The movement began with the forearm parallel to the ground and had an angular range of approximately 80 degrees, depending on the patients mobility. The patient was guided in terms of the speed of the arm movement by showing them an example. A similar task has been used earlier to study EMG in PD [10, 21–23]. The movements of the left and right arms were measured separately. The patients were instructed on the course of the measurement beforehand. They were encouraged to get used to the measurement setup and practice the tasks before the measurement. If the patient felt unsure about the procedure, guidance was given during the measurement.

Before the study began, the patients’ stimulators were programmed to optimal stimulation settings. The patients’ original settings are presented in Table 1 and are subsequently referred to as the base setup. The patient measurement was always initiated with DBS at the base setup and ended with DBS off. After the first setup, the stimulation settings were changed one at a time and the measurement was repeated. After each adjustment of DBS, the patient’s state was stabilised for a minimum of five minutes before beginning the measurement. The order of settings between the first and the last setting was randomised for each patient. The settings were changed relative to the patients’ base setup, and the steps were similar to those used in an ordinary DBS programming session:

base setup (A0)

decrease pulse voltage by 0.3 V (-A)

increase pulse voltage by 0.3 V (+A)

decrease frequency by 30 Hz (-F)

increase frequency by 30 Hz (+F)

increase pulse width by 30 μs (+W)

DBS off

The possible side effects were carefully observed and the patients were advised to immediately report subjective changes. If the patient experienced evident side effects or felt uncomfortable, the base settings were immediately restored. The patients were given the choice to abort the measurement, but all patients were willing to pursue the measurements with other adjustments after the patients’ clinical state was stabilised. The UPDRS-III motor score was determined in the beginning of the measurement with the base setup and with DBS off at the end. In other settings, only arm tremor and rigidity were assessed.

Analysis

All the signal processing was performed in MATLAB 2019b (MathWorks Inc). Preprocessing of the EMG signal consisted of three stages of filtering. First, the smoothness priors detrending method [24] was used to remove low frequency variation from the signals. The method resembles a high-pass filter and the cut-off frequency of the filter is set by tuning a smoothing parameter—α. Low frequency variation was eliminated by setting α = 300, corresponding to a cut-off of approximately 10 Hz. Second, DBS-induced noise was eliminated with spectrum linear interpolation [25] of ± 2 Hz around the individual DBS stimulation frequency. Third, the harmonics of DBS stimulation frequency and possible other high frequency noise were eliminated with ninth-order Butterworth low-pass filter with a cut-off frequency of 150 Hz.

Each measurement consisted of seven to eight flexion extension repetitions, of which flexions were analysed in this study. The flexion phases of each repetition were manually selected from the signals. The parameters were calculated for each flexion patient-wise and then averaged.

The signal distribution and parameters based on fine structure were used to characterise the changes in EMG signals. The EMG signal of a healthy subject is a stochastic process in which single muscle activations are summed up to generate the desired type of muscle contraction. The motor symptoms of PD interfere with the EMG signal and introduce synchronisation of muscle activation, which is seen as tonic background and bursts in the signal [26]. The parameter KURT may be used to describe the the tonic background and the bursts of the signal, and can be defined for the EMG signal x(t) as where μ is the mean and σ the standard deviation of x(t). EMG signal kurtosis is typically higher in patients with PD compared to healthy subjects due to the higher number of signal peaks.

The fine structure of the signal can be analysed with recurrence rate (%REC) and correlation dimension (CD). These parameters originate from recurrence quantification analysis. %REC describes the rate of recurrent structures in the signal and can be described in the following manner: where N is the length of the signal, Θ the Heaviside step function, ϵ the calculation threshold 0.2, d the Euclidean distance between two signal elements and Θ(ϵ − d) describes the recurrent element. Webber et al. described %REC for the assessment of dynamic systems in 1994 [27]. Recurring patterns in EMG signals arise due to increased synchronisation of muscle activation potentials. A larger number of recurrent EMG patterns have been observed during isometric muscle contraction in patients with PD compared to healthy subjects [26]. Moreover, the %REC has also been used to analyse dynamic muscle contractions in PD [10].

The correlation dimension (CD) can be defined as boundary value from similar equation when autocorrelation i = j is ignored and ϵ and signal length N approach infinity:

The CD cannot be determined without infinite signal, but it can be estimated by determining the slope of the logarithmic regression line. The EMG correlation dimension has been previously linked to muscle fatigue [28]. The correlation dimension measures the complexity of the signal and has been observed to be lower in the isometric EMG of patients with PD compared to healthy controls [26]. A decrease in correlation dimension indicates that the complexity of the signal decreases. In PD, this is typically caused by periodicity due to synchronisation.

The differences in EMG parameters between the different DBS settings were individually compared against the base setup. The patients’ more symptomatic arm was determined based on the anamnesis and the UPDRS-III score. Lilliefors test for data normality was performed for the parameters. The parameters were not normally distributed and Wilcoxon signed rank test was performed to determine if the differences between setups compared to the base setup were significant.

Results

The UPDRS-III score decreased from 15% to 45% (mean 35%) when comparing DBS off and the base setup (Table 1). Measured arm tremor and rigidity scores are presented in Table 2. Arm tremor or rigidity did not change significantly between the settings. In three patients, no changes in arm tremor or rigidity occurred during the entire measurement.

Table 2

Arm tremor and rigidity during settings (mean ± sd).

The changes in arm tremor and rigidity were non-significant throughout the measurement. The arm tremor and rigidity increased due to a decrease in stimulation values (-A, -F, off) and decreased due to an increase in stimulation values (+A, +F) in certain patients. The changes were generally small compared to the deviation.

Setting	Tremor (0–8)	Rigidity (0–8)
A0	0.4 ± 0.8	1.2 ± 1.5
-A	1.0 ± 1.5	1.4 ± 1.9
+A	0.1 ± 0.3	0.4 ± 0.9
-F	1.1 ± 1.4	1.1 ± 1.4
+F	0.2 ± 0.4	0.8 ± 1.4
+W	0.4 ± 1.0	0.3 ± 0.7
DBS off	1.6 ± 2.0	2.2 ± 2.0

Fig 1 presents the EMG signal response of a patient during the adjustment of DBS. The response to DBS stimulation varied with each individual. On this patient the activation patterns during the contraction of biceps muscle are regular when DBS is set to the base setup (A0). The change of stimulation voltage caused burst patterns (+A) and a large spike (-A) probably caused by a dystonic movement at the end of the extension of the elbow. Changing the pulse frequency prolonged the flexion part of the signal. When the stimulator was turned off, the EMG activity increased notably and did not cease between the contractions. Instead, a tonic background muscle contraction remained throughout the task with more synchronised bursts in the signal.

Fig 1

The EMG signals of one patient during the elbow flexion-extension task during the adjustment of DBS.

The morphology of the EMG signal differs among the different adjustments of DBS. Turning the stimulator off caused the strongest effect and introduces significant tonic background to the EMG signal. Scaling is identical in all settings.

Significant changes were observed during the adjustment of DBS in the parameters calculated from the patients’ more symptomatic arm (Table 3). %REC increased significantly in all settings compared to the base setup. Similar changes were observed for KURT and CD, but the changes were significant in only part of the setups. KURT increased significantly in +A, -F, and DBS OFF, while CD decreased significantly in +A, -F, +F, and +W. The changes in the parameters calculated from the patients’ less symptomatic arm were non-significant during the adjustment of DBS. %REC and CD differed the most when the pulse width was adjusted (+W), despite the fact that a major proportion of the patients could not be measured due to strong effects of DBS. There was also a considerable amount of variation between the patients in the parameters in +W as well as in certain parameters in -A, -F, and +F (Fig 2). An increase or decrease in pulse frequency affected EMG parameters slightly more than an increase or decrease in pulse voltage.

Table 3

Relative EMG signal parameters recurrence rate (%REC), kurtosis (KURT), and correlation dimension (CD) (median ± IQR).

%REC changed significantly after each adjustment. Increasing voltage or decreasing frequency of the stimulation changed each parameter significantly. Significance levels *p < 0.05, † p < 0.01.

Setting	%REC	KURT	CD
More affected hand
-A (-0.3 V)	1.10 ± 0.50*	1.02 ± 0.16	0.96 ± 0.11
+A (+0.3 V)	1.34 ± 1.14*	1.06 ± 0.19*	0.91 ± 0.22*
-F (-30 Hz)	1.65 ± 0.43†	1.13 ± 0.23*	0.88 ± 0.11†
+F(+30 Hz)	1.66 ± 0.79*	1.13 ± 0.25	0.92 ± 0.09*
+W (+30 μs)	1.98 ± 1.69*	1.13 ± 0.23	0.82 ± 0.22*
DBS off	1.47 ± 1.10*	1.10 ± 0.08†	0.94 ± 0.15
Less affected hand
-A (-0,3 V)	0.90 ± 0.49	0.99 ± 0.10	1.02 ± 0.11
+A (+0,3 V)	1.02 ± 0.73	1.01 ± 0.14	0.95 ± 0.15
-F(-30 Hz)	1.06 ± 0.45	0.97 ± 0.22	0.96 ± 0.14
+F(+30 Hz)	0.92 ± 0.70	0.96 ± 0.22	1.01 ± 0.17
+W (+30 μs)	0.95 ± 0.68	1.01 ± 0.27	0.96 ± 0.14
DBS off	1.32 ± 0.66	1.01 ± 0.25	0.95 ± 0.14

Fig 2

The EMG parameters of patients during elbow flexion-extension task during different adjustments of DBS.

There are significant changes in each parameter compared to the base setup. Recurrence rate changes significantly in each adjustment. Changes are stronger on more symptomatic side compared to less symptomatic side. Fig 2 shows parameter vaules separately for more (black) and less (gray) symptomatic arm. The small gray dots next to boxplot indicate the individual patient values. The vertical axis value 1 is the setting A0 value. The deviation is considerable in all settings. Significance levels *p < 0.05, † p < 0.01.

Side effects were observed 17 times, of which 11 caused the abortion of the measurement as it caused the patient discomfort. Most of the side effects were caused by increasing the pulse width. Six patients developed dysarthria probably by unwanted stimulation of corticobulbar fibers. Three patients had muscle contraction probably due to stimulation of corticospinal fibers. One patient developed diplopia due to stimulation of oculomotor nerve. Seven patients developed dyskinesia due to non-optimal stimulation. All side effects vanished when original DBS settings were restored.

Discussion

Muscle activation patterns of 13 patients with advanced PD were measured during adjustment of DBS. The DBS was adjusted in small steps of 0.3V, 30Hz, and 30μs, similar to a clinical DBS programming session. The main finding was that adjustment of the DBS causes changes to the EMG signal morphology via changed muscle activation patterns. The respective clinical markers for rigidity or tremor did not change significantly. The secondary finding was that changes in signal morphology were more pronounced on the patients’ more symptomatic arm, whereas there were no significant changes in signal morphology on the patients’ less symptomatic arm.

The EMG parameters (%REC, KURT, CD) differed significantly between the optimal and other adjustments of DBS and indicated that with optimal settings, the signal contained less parkinsonian signal features on average compared to any other measured setup. Adjusting DBS voltage, frequency, or pulse width into other than the optimal values, the EMG activity changed and contained more synchronised bursts on average, which are known to be related to the symptoms of PD. In this study, %REC was the most sensitive parameter for detecting differences between the base setup and the other DBS adjustments. %REC measures the density of repeating patterns in EMG signal and is typically higher in patients with PD compared to healthy subjects [26]. KURT and CD differed between the adjustments, but the difference was not significant in each setup. These parameters describe the signal in a different manner compared to %REC and it appears that recurrent patterns are more sensitive indicators for DBS adjustments compared to signal complexity and peakedness.

Montgomery proposes that response to DBS stimulation follows a U-shaped curve: increase in stimulation voltage improves motor performance only until a certain point is reached. After this point, according to Montgomery, patient’s motor performance becomes worse if the voltage is further increased [29]. The results of the study are in agreement with Montgomery’s theory: the EMG parameters had their extremum value at the base setup (low peak for %REC and KURT, high peak for CD).

Although the parameters changed significantly at the group level, there was considerable variation. This was taken into account by normalising the parameters with the patients base setup, thereby allowing for a comparison of the changes among the patients. At the individual level, the parameters differed between the optimal and non-optimal stimulation in most patients. In certain patients, the parameters did not reach the peak value at base setup and, thus, the parameters did not indicate the optimal stimulation setting. This was observed slightly more when stimulation amplitude was altered compared to frequency or pulse width adjustment. It must be noted that altering the stimulation settings may improve some PD symptoms like rigidity, but simultaneously induce unwanted motor or non-motor side effects.

Rigidity and tremor are suggested for assessing DBS symptomatic relief during programming as they react quickly to changes in adjustment [6]. Rigidity is more reliable symptom for adjustment compared to tremor since tremor often fluctuates unlike rigidity. While the UPDRS-III full motor assessment differed significantly between the base setup and DBS off, there was no significant difference in arm tremor and rigidity tasks between the DBS settings. This may be due to the following factors: 1) DBS may affect symptoms other than arm tremor and rigidity, 2) the scoring for arm tremor and rigidity may be too coarse to detect minor changes due to adjustment of DBS in small steps. Similar results have been reported by Heida et al. [30]. The UPDRS evaluation has been devised for comprehensive assessment of motor and non-motor symptoms of the PD, while single tasks score were used to assess patients in this study. Even though there was no difference in rigidity and tremor score between the adjustments, the patients still preferred the base settings over other adjustments. The optimal settings for DBS depend on multiple factors, including the possible side effects that DBS may cause. Full UPDRS-III evaluation was not performed with each DBS setting, as it would have been too time-consuming and too strenuous for patients.

The finding that EMG parameters change significantly during adjustment of DBS while arm rigidity and tremor do not is significant. The result is in concordance with Heldman et al. [7], who suggest that kinematic measurement can be more sensitive for characterising finger tapping in PD compared to assessment by a clinician. The changes in the EMG parameters reflect the small steps in which stimulator was adjusted. If larger adjustment steps were used, the differences would possibly have been more pronounced. Despite adjusting the stimulator in small steps, motor and non-motor side effects were observed. Dyskinesia, dysarthria, or impairment of vision are typically caused by unwanted stimulation of nearby tissue. Rapid movements of limbs require strong muscle activation and cause significant amplitude spikes to the EMG signal. Moreover, tonic muscle contractions may be seen as background activity in EMG even at rest. Motor side effects were rarely recorded during the study since the measurement was aborted after their emergence. The adjustment of the pulse width caused the greatest number of side effects and thus, the patient in Fig 1 is not an exemplary case, since EMG morphology changed only slightly after pulse width adjustment. Other generalisations regarding what side effects were caused by different stimulation settings cannot be made based on our results.

The therapeutic effect of DBS has different delay for relieving different symptoms. Rigidity and tremor are relieved in seconds to minutes [6, 17, 31], while it may take from minutes to days to relieve bradykinesia and axial symptoms [6]. This is an inherent challenge in DBS programming and it is possible that symptoms with longer stabilisation time cannot be observed during the programming session to the full extent. These symptoms must be observed in multiple sessions or with long period measurements. A stabilisation time of minimum 5 minutes was selected to maintain the measurement session short—a total of 2,5 hours. While it is possible that the patients’ response to the DBS was still stabilising, most of the effects were likely present during the measurement.

The patients had advanced PD with motor symptoms that could not be adequately controlled by optimal medical treatment. Antiparkinsonian medication is typically used along with DBS therapy to achieve optimal control of symptoms. While the first adjustments of the stimulator after installation are done without medication, the fine-tuning may be done with medication. The patients were studied with their current normal medication. While this might weaken the results, a study suggests that medication cannot fully alleviate patterns typical to PD from EMG signals [21]. The effect of medication was taken into account in the planning by keeping the total duration of the measurements as low as possible, while maintaining a sufficiently long time for DBS stabilisation. This helped in two ways: the measurements were not burdensome to the patients, but also the medication response was relatively stable during the measurement. Further, the different DBS settings were measured in randomised order to decrease systematic errors caused by a change in the medication response.

Conclusion

Clinical observation is currently the golden standard for PD diagnosis and is predominantly used for programming the DBS. This study is one of the first studies to evaluate EMG signal parameters during the adjustment of DBS. The results suggest that while UPDRS-III tremor and rigidity tasks are used a part of the evaluation of programming the DBS, these scores may not be sufficiently specific to detect the small differences in the patients motor state and thus the operators, despite being trained professionals, may have to rely on their craftmanship for the evaluation of tremor and rigidity, since the UPDRS motor scoring may lack precision.

This emphasises the need for specific objective methods to assess the symptoms of PD during DBS programming. While this study shows promising results for using EMG to quantify changes during the adjustment of DBS, the role of the study was a proof of concept and shall be validated with a larger number of patients. A larger number of patients would enable, for example, dividing the patients into groups based on their main symptom (tremor, rigidity, motor fluctuations), examining only the patients with a change in the clinical tremor or rigidity, and performing receiver operator characteristic analysis or other sophisticated statistical predictions.

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23 Jun 2021

PONE-D-21-16366

Elbow flexion EMG morphology changes during adjustment of deep brain stimulator in advanced Parkinson's disease

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Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: I Don't Know

**********

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Reviewer #1: No

Reviewer #2: No

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Reviewer #1: No

Reviewer #2: No

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5. Review Comments to the Author

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Reviewer #1: General comments

This manuscript investigates the effect of modifying DBS settings on EMG of the biceps brachii muscle bilaterally and the UPDRS III clinical sub-scores for tremor and rigidity. Results indicate that whilst clinical sub-scores did not change between settings, there were significant differences in EMG metrics. This is an interesting and relevant study to better understand if and how motor changes relate to modifying DBS frequency, width, and amplitude settings. There are however several general areas that need to be addressed:

• There are numerous grammatical errors throughout the manuscript usually with a word missing, incorrectly used word and several typos. Please proofread the manuscript and correct.

• No discussion of how altered ‘EMG signal morphology’ relates to clinical changes has been made. Is there any evidence that for example increased recurrence rate (greater repetition) relates to improved clinical function?

• Complexity has a definite mathematical definition and indicates greater interactions (Didier Delignieres & Vivien Marmelat, Fractal Fluctuations and Complexity: Current Debates and Future Challenges, December 2012, Critical Reviews in Biomedical Engineering 40(6):485-500). Decreased regularity does not mean increased complexity. Please check throughout the manuscript that the use of the word ‘complexity’ is appropriate.

• Tremor and rigidity were assessed with sub-scores of UPDRS III which is a very blunt tool. Tremor can be measured quantitatively with an accelerometer and an indication of rigidity by measuring co-activation of agonist and antagonist. Why were quantitative measures of recording tremor and rigidity not undertaken?

• Statistics is only very briefly mentioned. Only a Wilcoxon signed rank test was performed. Were the data nonparametric? Could Friedman/ Kruskal Wallis be used? Please expand more on the statistics.

Methods

• In Methods, how was the location of placement of the electrodes determined? Were SENIAM guidelines followed?

• At what angle was the elbow joint at the beginning of the recording session and what was the angular range of movement and velocity? Length of fascicle, angular velocity and eccentric/ concentric contractions will all modify EMG signals.

• Please include the safety levels for the DBS parameters.

• Please provide a reference on pg4, line 124 for why 5 minutes was selected between setings.

Analysis

• How were the flexion phases of the EMG signals selected?

• Please explain why kurtosis, recurrence rate and correlation dimension were analysed and not other metrics. What algorithms were used and what software?

• Results

• A demographics’ table with individual’s demographics and clinical details should be included

Discussion

• Line 217 – Is it possible for anything to change ‘instantly’? Please revise.

• ‘Miniscule’ is a vague term and preferable to be replaced with ‘nonsignificant changes’.

• Lines 238-240. EMG records muscle activity therefore by definition it will have greater sensitivity to muscle activity changes as this is what it is measuring! Please revise. EMG is quantitative and UPDRS III is a subjective qualitative clinical measure.

• Line 240 – How is ‘optimally tuned’ DBS defined?

Conclusion

• The conclusion is weak as there is no strong message other than changes occur. It is recommended to introduce some clinical relevance.

Figures

Figure 1- Please either define the acronyms of the 7 settings in the figure legend or ideally, add as subheadings.

Figure 2 – See above.

Reviewer #2: The authors address one of the main challenges in deep brain stimulation (DBS) therapy: To determine DBS parameters leading to best clinical efficacy of DBS in the individual patient by using an objective feedback measure. Such an approach may not only spare time needed during “conventional” DBS programming sessions but may also reduce the number of recurrent clinical visits normally needed to evaluate often delayed DBS effects. Moreover, individual DBS clinical efficacy may be enhanced and DBS side effects reduced.

The authors present an explorative study which evaluates measures of EMG recordings during a patient driven phasic motor task of an elbow flexion correlated to clinical effects of subthalamic nucleus DBS in Parkinson´s disease (PD) patients.

Some additional aspects may strengthen the findings and could help to improve the manuscript:

Introduction

- The introduction should be shortened and should have stronger focus on the need to improve the quality of programming algorithms for DBS therapy.

- Description of general medical treatment strategies in PD may be left out as well as hypotheses on the mechanisms of action of DBS.

- Instead, a statement that DBS is an appropriate therapeutic option in late stage PD may be enough and may be followed by discussing the problems clinicians and patients are confronted with during conventional DBS programming sessions (try and error, delayed DBS effects and side effects).

- The last paragraph in the introduction may then illustrate why the authors have chosen EMG recordings to objectify clinical DBS effects.

Methods

- Authors should explain why they have chosen the mentioned motor task. To me, this task is far from being “objective” as the performance of such a task is patient driven in acceleration and speed of the movements and in its muscle strength which directly affects EMG activity.

- The authors should explain why they have chosen to evaluate such minimal changes of amplitude and frequency compared to the clinically chosen DBS settings, which the authors call “base setup”. I do agree that sometimes subtle changes of DBS parameters may influence motor symptoms of PD but I cannot see any rationale for +-0.3V, +-30Hz, +-30µs.

- I would strongly recommend to additionally study patients in medication / dopamine depleted state as PD motor symptoms may similarly become reduced with medication or DBS. Otherwise, their relative influence on symptom relief cannot be described and therefore effects on EMG recording cannot clearly be assigned to one or the other therapy: What parameters of EMG recordings are influenced by medication? What parameters of EMG recordings are influenced by DBS?

- Characteristics of EMG recordings due to side effects (affecting pyramidal tract) should be defined to distinguish “optimal” from “above threshold” stimulation. Especially because the authors describe “side effects” (without further specification of their clinical appearance) due to greater pulse widths.

Analysis

- The reader may profit from a more detailed clinical / practical view on and explanation of the parameters chosen to be evaluated from EMG recordings: kurtosis, recurrence rate, correlation dimension.

- What are the clinical significances of differences in kurtosis, recurrence rate and correlative distribution between PD and healthy controls? What is the physiological meaning of the mentioned parameters?

Results

- Table 1 shows that “base setup” may not be “best setup” as the increase of the parameters amplitude, frequency or pulse width, even in such narrow margins (see above), may further improve DBS clinical efficacy. Authors should discuss and may further analyse differences in EMG recordings which may distinguish patients with suboptimal stimulation from optimal stimulation (e.g. complete clinical rigidity control as clinical feeback).

- Figure 2 shows results of EMG-parameters in relation to “base setup” (A0). Although clinically more effective to weaken tremor and rigidity (see table 1), A+ is still greater 1, suggesting A+ to be “worse” than A0. The authors may explain 1) why they have chosen to analyse EMG parameters relative to A0 and 2) why A+ performs less effective than A0 in the EMG parameters although clinically better in the reduction of PD motor symptoms (same for F+ which performs worse than DBS OFF in the EMG parameters, although of better clinical efficacy than A0).

- The authors should explain and name the mentioned “side effects” of DBS due to changed parameters (e.g. pulse width). DBS may have affected the fibres of the pyramidal tract? What are the effects of these “side effects” on EMG recordings? Again, authors may analyse / discuss how to distinguish suboptimal, optimal and above threshold stimulation (side effects) by means of EMG recordings.

- Statistical results are not rigorously stated (performed tests and resulting values are missing).

Discussion

- The “U-shaped theory” of optimal stimulation parameters needs to be better explained. “EMG parameters had their extremum at the base setup” is not shown in the results section (only relative values in fig2).

The whole manuscript needs major editing concerning language and spelling.

**********

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Reviewer #1: Yes: Annette Pantall

Reviewer #2: No

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Submitted filename: Elbow flexion_180621.docx

Click here for additional data file.

3 Oct 2021

Dear Editor, reviewers #1 and #2,

Thank you for your excellent corrections and comments. We have revised the manuscript thoroughly.

Dear Editor,

>>>Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

...PLOSone_formatting_sample_main_body.pdf and

...PLOSone_sample_title_authors_affiliations.pdf

Manuscript has been checked against to these templates and required changes have been made. However, requirement "Tables must be cell-based in Microsoft Word or embedded with Microsoft Excel" could not be fullfilled as the manuscript is prepared on PLOS ONE LaTeX template.

>>> We note that the grant information you provided in the 'Funding information' and 'Financial Disclosure' sections do not match.

Funding information updated:

The work was supported by Academy of Finland under project (252748). VR has received research grant from Finnish Parkinson foundation. EP has received Finnish Govermental research funding (TYH-fund). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

#>>> We note that you have a patent relating to material pertinent to this article. Please provide an amended statement of Competing Interests to declare this patent (with details including name and number), along with any other relevant declarations relating to employment, consultancy, patents, products in development or modified products etc.

V.R. is an inventor in patent application PCT/FI2019/050163 "Measurement unit and monitoring system for monitoring indicator of Parkinson's disease in person".

S.M.R. and P.A.K. are inventors in patent applications EP18159445.8 "Electrode patch, system, and method for detecting indicator of Parkinson's disease in person", PCT/EP2019/055002 "Electrode patch, system, and method for detecting indicator of Parkinson's disease in person", and PCT/FI2019/050163 "Measurement unit and monitoring system for monitoring indicator of Parkinson's disease in person".

S.M.R and P.A.K are co-founders of Adamant Health Ltd.

E.P. is a Standing Member of the MDS Non-Motor Parkinson's Disease Study Group.

>>> Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, as detailed online in our guide for authors by including the following statement... .

These patents, patent applications nor other interests do not alter our adherence to PLOS ONE policies on sharing data and materials.

If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

This study is part of larger research project that has been approved 2004 and updated 2011 by research ethics committee of the Northern Savo Hospital District (155/2004). The approval of the study requires that all the raw patient data related to the research project has to be destroyed after the end of the project. The ethics statement related to this project allows us to publish processed data, but the data has to be anonymised so that it cannot be linked to the patients participating the study. The data regulations in Finland are strict and all health related data of patients is considered confidential by definition. Please note that Finland is not that big a country, and there are not so many patients with Parkinson's disease, we have to be especially considerate on this matter.

We are unfortunately unable to share raw data from the measurements. However, we do want to cooperate to solve this issue within the limits set by the ethics statement, national law and the EU directive on data protection (GDPR). We have included a datasheet with intermediate data to verify the results and conclusions stated in the manuscript. We do hope that this helps the decision.

Dear reviewer #1,

>>> There are numerous grammatical errors throughout the manuscript usually with a word missing, incorrectly used word and several typos. Please proofread manuscript and correct.

Manuscript updated:

>>> No discussion of how altered ‘EMG signal morphology’ relates to clinical changes has been made. Is there any evidence that for example increased recurrence rate (greater repetition) relates to improved clinical function?

We like to think it other way around - improved clinical function is reflected to muscle activation as change in parameters e.g. recurrence. The parameters in this study have been shown to differ between patients with PD and healthy subjects (Meigal et al. 2009, Rissanen et al. 2008).

As you have pointed out later in a comment, UPDRS subtask scores are a blunt tool for assessing delicate changes. As the results of the study show, this clinical marker is unable to differentiate between the settings even though the patients are suffering from advanced PD. Thus, the adjustment has to be based on other factors as well. During the course of these measurements, different stimulation settings were tested, but as a whole, patients had least symptoms and side effects with the optimal setup: after all the patients chose to continue with the same optimal settings after the adjustment.

Manuscript updated.

>>> Complexity has a definite mathematical definition and indicates greater interactions (Didier Delignieres & Vivien Marmelat, Fractal Fluctuations and Complexity: Current Debates and Future Challenges, December 2012, Critical Reviews in Biomedical Engineering 40(6):485-500). Decreased regularity does not mean increased complexity. Please check throughout the manuscript that the use of the word ‘complexity’ is appropriate.

Manuscript updated. Decreased complexity now refers only to decrease in correlation dimension, which is a measure of complexity.

>>> Tremor and rigidity were assessed with sub-scores of UPDRS III which is a very blunt tool. Tremor can be measured quantitatively with an accelerometer and an indication of rigidity by measuring co-activation of agonist and antagonist. Why were quantitative measures of recording tremor and rigidity not undertaken?

Excellent point, this is one of the key messages of this study. UPDRS-III subtasks, despite being blunt, are still the golden standard when assessing PD symptoms during adjustment of DBS. The scope of this study was to prove that the changes that DBS causes to muscle activation can be detected objectively with simple EMG measurement setup. We are aware, that tremor can be measured with accelerometer and it has been proven in many peer reviewed publications. The measurement of rigidity, however, we believe is not that straightforward and depends on many factors that may include agonist-antagonist activation. Biceps EMG has been used to recognize rigidity in earlier study with similar task (Rissanen et al. 2009).

Manuscript updated.

>>> Statistics is only very briefly mentioned. Only a Wilcoxon signed rank test was performed. Were the data nonparametric? Could Friedman/ Kruskal Wallis be used? Please expand more on the statistics.

Lilliefors test for data normality was performed for the parameters. Wilcoxon test was used because it is paired and determines directly the significance between the measurement phases. Kruskal-Wallis is used for non-paired data and while it may be used, part of the information is lost in the process.

Manuscript updated.

Methods

>>> In Methods, how was the location of placement of the electrodes determined? Were SENIAM guidelines followed?

SENIAM guidelines were followed in positioning recording electrodes. SENIAM guideline on reference electrode positioning was not followed. The analysis methods that are used in this study require high quality EMG measurements. To improve signal quality and reduce noise, we chose to use a EMG preamplifier with approx 15 cm electrode leads. With this setup, lateral side of brachium was an optimal place to position the reference electrode. SENIAM guideline on electrode separation was not followed. There are theoretical and practical reasons to this. Electrode size and the distance between them affect to the number of motor units they record. Since this study is about EMG morphology and motor unit synchronisation patterns, it was necessary to measure multiple motor units simultaneously. Due to this big (diameter 3 cm) electrodes with 3 cm separation were used. The electrodes could have been cut to decrease the distance, but that would have risked to shortcut the electrode gels and also would have decreased the number of motor units they measure. The measurement setup has been used in numerous studies (Rissanen et al. 2007, 2009 and 2011, Meigal et al. 2009 and 2012, Ruonala et al. 2014 and 2018).

Manuscript updated.

>>> At what angle was the elbow joint at the beginning of the recording session and what was the angular range of movement and velocity? Length of fascicle, angular velocity and eccentric/ concentric contractions will all modify EMG signals.

The elbow angle was not measured during the measurements. The measurement began with forearm parallel to ground. Angular range of the movement was approx 80 degrees and the repetition frequency 45-55 bpm.

Manuscript updated.

>>> Please include the safety levels for the DBS parameters.

Usually DBS voltage range up to max 5 volts is recommended. The stimulation pulse width and stimulation frequency depend on type of stimulator and the stimulation target. For STN-DBS 30-210 µs have been studied. Stimulation frequency over 185 Hz does not improve symptoms significantly. (Koeglsperger et al 2019)

During DBS programming in clinic, we at first keep pulse width and frequency constant at 60 µs and 130 Hz, respectively. First monopolar survey will be accomplished by gradually increasing voltage by 0.5 V steps up to 5 V, continuously observing clinical response (rigidity being most reliable followed by bradykinesia and tremor) unless clear side-effects will appear, like dysarthria, diplopia, paresthesia. When necessary, specifically in tremor dominant PD patients’ response to frequency will be tested between 60-200 Hz. Usually 60, 130, 160 and 200 Hz. Finally response to pulse width will be tested by gradually increasing pulse width up to 90 µs (STN). Activa/Kinetra system do not allow to reduce pulse width below 60 µs.

During this study, one patient was tested for 210 Hz stimulation frequency, one patient was tested for 120 us pulse width. Neither of these settings did not produce better results compared to optimal settings.

Manuscript updated.

>>> Please provide a reference on pg4, line 124 for why 5 minutes was selected between setings.

Manuscript updated: Discussion on stabilisation time has been transferred to 'Discussion' section. Detailed explanation with references is included.

Analysis

>>> How were the flexion phases of the EMG signals selected?

Flexion phases of the movement were selected by hand from the signals by the author.

>>> Please explain why kurtosis, recurrence rate and correlation dimension were analysed and not other metrics. What algorithms were used and what software?

Kurtosis, recurrence rate and correlation dimension showed strongest potential in detecting DBS induced changes. The parameters were caluculated by algorithms that were tailored for this study and are based on the equations in 'Analysis' section. The computations were made with MATLAB 2019b (Mathworks).

Manuscript updated: Computation software added.

Results

>>> A demographics’ table with individual’s demographics and clinical details should be included

Manuscript updated.

Discussion

>>> Line 217 – Is it possible for anything to change ‘instantly’? Please revise.

Manuscript updated.

>>> ‘Miniscule’ is a vague term and preferable to be replaced with ‘nonsignificant changes’.

Manuscript updated.

>>> Lines 238-240. EMG records muscle activity therefore by definition it will have greater sensitivity to muscle activity changes as this is what it is measuring! Please revise. EMG is quantitative and UPDRS III is a subjective qualitative clinical measure.

Manuscript updated.

>>> Line 240 – How is ‘optimally tuned’ DBS defined?

Optimally tuned refers to base setup defined in 'Methods' section.

Manuscript updated.

Conclusion

>>> The conclusion is weak as there is no strong message other than changes occur. It is recommended to introduce some clinical relevance.

The nature of this study is a proof of concept: we aim to prove that EMG is sensitive enough to detect differences between different DBS adjustments. The results support this hypothesis even though the number of patients in this study does not allow for wider conclusions. We believe that it is essential to have objective means to assess the symptoms of PD and not only for adjustment of DBS. The study shows that the clinical state of the patient may change while the current clinical markers stay unchanged, and it indicates that the clinical assessment is too coarse. The study provides means to assess the changes based on muscle activation patterns.

Manuscript updated.

Figures

>>> Figure 1- Please either define the acronyms of the 7 settings in the figure legend or ideally, add as subheadings.

>>> Figure 2 – See above.

Manuscript updated.

Dear reviewer #2,

Introduction

>>> The introduction should be shortened and should have stronger focus on the need to improve the quality of programming algorithms for DBS therapy.

>>> Description of general medical treatment strategies in PD may be left out as well as hypotheses on the mechanisms of action of DBS.

>>> Instead, a statement that DBS is an appropriate therapeutic option in late stage PD may be enough and may be followed by discussing the problems clinicians and patients are confronted with during conventional DBS programming sessions (try and error, delayed DBS effects and side effects).

#>>> The last paragraph in the introduction may then illustrate why the authors have chosen EMG recordings to objectify clinical DBS effects.

Manuscript updated. We like to include short description of the general picture of the disease and available treatments before going into details of the study. However, parts related to elementary physiology of PD and mechanisms of DBS have been focused.

Methods

>>> Authors should explain why they have chosen the mentioned motor task. To me, this task is far from being “objective” as the performance of such a task is patient driven in acceleration and speed of the movements and in its muscle strength which directly affects EMG activity.

The dynamic elbow flexion task or slight variations have been used in multiple PD studies (Rissanen et al 2009, Flament et al 2003, Robichaud et al 2002, Pfann et al 2001). It is true that the task is patient driven in speed of movements. The dynamic movement does not alleviate the symptoms, quite the opposite, it may even provoke the symptoms. As the movement speed in this particular task cannot be controlled precisely without a manipulator, traditional EMG analysis for e.g. amplitude is not helpful. However, we argue that slight variations in movement speed do not signifcantly affect the muscle synchronisation in PD. It has been reported that kurtosis is affected at high speed movement (120 bpm and above), but not lower such as in this study (Ahmad et al. 2009).

Manuscript updated.

>>> The authors should explain why they have chosen to evaluate such minimal changes of amplitude and frequency compared to the clinically chosen DBS settings, which the authors call “base setup”. I do agree that sometimes subtle changes of DBS parameters may influence motor symptoms of PD but I cannot see any rationale for +-0.3V, +-30Hz, +-30µs.

In DBS treatment, the effect of the treatment strongly depends on the stimulation settings, voltage, frequency, pulse width. The stimulator has to be tuned individually to determine the optimal stimulation settings for the best treatment effect. These optimal stimulation settings are defined as the base setup in the manuscript. Subtle changes around these optimal values were selected since the purpose of the study was to determine if clinically relevant small steps in tuning DBS can be detected with EMG measurement. The exact steps were selected to reflect typical DBS adjustment session, in which the purpose is to fine tune the DBS.

Manuscript updated.

>>> I would strongly recommend to additionally study patients in medication / dopamine depleted state as PD motor symptoms may similarly become reduced with medication or DBS. Otherwise, their relative influence on symptom relief cannot be described and therefore effects on EMG recording cannot clearly be assigned to one or the other therapy: What parameters of EMG recordings are influenced by medication? What parameters of EMG recordings are influenced by DBS?

This is an important point. The medication is typically used along with DBS therapy to achieve optimal symptom control. The patients were studied with their current normal medication as that is the situation when the patients have their stimulator fine tuned. (The first adjustments are done without medication). This was taken into account when planning the study. The measurement duration was kept as low as possible while maintaining enough time for the DBS to stabilise. By doing this had two advantages: the measurement was not burdensome to the patient, but also the medication response was somewhat constant. Further, the different DBS settings (excluding optimal and off) were measured in randomized order to decrease systematic errors such as this.

Manuscript updated.

>>> Characteristics of EMG recordings due to side effects (affecting pyramidal tract) should be defined to distinguish “optimal” from “above threshold” stimulation. Especially because the authors describe “side effects” (without further specification of their clinical appearance) due to greater pulse widths.

Please see explanation below.

Manuscript updated.

Analysis

>>> The reader may profit from a more detailed clinical / practical view on and explanation of the parameters chosen to be evaluated from EMG recordings: kurtosis, recurrence rate, correlation dimension.

>>> What are the clinical significances of differences in kurtosis, recurrence rate and correlative distribution between PD and healthy controls? What is the physiological meaning of the mentioned parameters? (onko tätä kysymystä siirretty?)

Manuscript updated.

Results

>>> Table 1 shows that “base setup” may not be “best setup” as the increase of the parameters amplitude, frequency or pulse width, even in such narrow margins (see above), may further improve DBS clinical efficacy. Authors should discuss and may further analyse differences in EMG recordings which may distinguish patients with suboptimal stimulation from optimal stimulation (e.g. complete clinical rigidity control as clinical feeback).

This is a good point. We should emphasize that even though some changes were seen, the statistical tests (Wilcoxon) show non significant change in tremor and rigidity scores of the patients during the measurements. In other words, changes in UPDRS-III rigidity and tremor subscore did not show difference between the setups. Full UPDRS-III motor assessment was done with A0 and with DBS off if possible. Full UPDRS-III changed significantly between these two phases.

Manuscript updated.

>>> Figure 2 shows results of EMG-parameters in relation to “base setup” (A0). Although clinically more effective to weaken tremor and rigidity (see table 1), A+ is still greater 1, suggesting A+ to be “worse” than A0. The authors may explain 1) why they have chosen to analyse EMG parameters relative to A0 and 2) why A+ performs less effective than A0 in the EMG parameters although clinically better in the reduction of PD motor symptoms (same for F+ which performs worse than DBS OFF in the EMG parameters, although of better clinical efficacy than A0).

1) In the relative analysis, each patient is compared to their own optimal settings (arms separately). The EMG parameters were analysed in relation to A0 to be able to compare the change between the parameters, not absolute values. The comparison could be relative to any other parameter, possibly to DBS off. We do believe that it is most useful to compare the parameter values to A0 since it was the starting point and also the optimal setting for the patients.

2) There was no significant differences in clinical rigidity and tremor subscores. However, this is a very complicated question. The ultimate goal of adjustment of DBS is to improve patient's motor function and eventually the life quality. There are multiple factors that affect the goodness of DBS adjustment of which arm rigidity and tremor are only a part of. It is possible that patients clinical state seems to be improved based on motor assessment, but the patient has adverse effects or just "bad sensation". Ultimately it is the patient together with neurologist who judge between the adjustments and the motor evaluation is just a tool to aid the decision. This study focuses on changes in EMG morphology and thus motor performance of the patient. The methods presented in this study do not allow for "comprehensive assessment of DBS adjumstent" since there are other motor (posture, gait) and non-motor (side effects: dysartria, diplopia, possibly even gambling?) factors that affect the optimal adjustment.

The patients may have multiple optimal settings for different type daily activities and sometimes the goal of adjustment is to increase the therapeutic range of the stimulator. In this case the goal is to adjust the stimulator in a way that the clinical parameters do not change.

Manuscript updated.

>>> The authors should explain and name the mentioned “side effects” of DBS due to changed parameters (e.g. pulse width). DBS may have affected the fibres of the pyramidal tract? What are the effects of these “side effects” on EMG recordings? Again, authors may analyse / discuss how to distinguish suboptimal, optimal and above threshold stimulation (side effects) by means of EMG recordings.

Manuscript updated.

There was substantial overlap between previous comments regarding side effects, suboptimal stimulation and we have refactored them to three new comments:

>>> The authors should explain and name the mentioned “side effects” of DBS due to changed parameters (e.g. pulse width). Especially because the authors describe “side effects” (without further specification of their clinical appearance) due to greater pulse widths. What are the effects of these “side effects” on EMG recordings? DBS may have affected the fibres of the pyramidal tract?

Patients were carefully observed for side effects, and they were also advised to immediately report subjective changes. According to our research protocol, original DBS settings (base setup) were immediately restored when clear side effects appeared. Hence, we were not able to record reliable EMG signal during side effects.

Side effects were observed in total of 17 measurement phases. Most side effects were caused by increasing pulse width. Six patients developed dysarthria probably by unwanted stimulation of corticobulbar fibers. Three patients had muscle contraction probably due to stimulation of corticospinal fibers. One patient developed diplopia due to stimulation of oculomotor nerve. Seven patients developed dyskinesia due to stimulation. All side effects vanished when original DBS settings were restored.

Generally rapid limb movements or muscle contraction may be detected from EMG as signal amplitude changes. Mild twitching and tingling may not be visible, but can be observed as change of signal morphology. Non-motor symptoms e.g. dysartria, diplopia cannot be directly measured with EMG.

Manuscript updated.

>>> Authors should discuss and may further analyse differences in EMG recordings which may distinguish patients with suboptimal stimulation from optimal stimulation (e.g. complete clinical rigidity control as clinical feeback). Again, authors may analyse / discuss how to distinguish suboptimal, optimal and above threshold stimulation (side effects) by means of EMG recordings. Characteristics of EMG recordings due to side effects (affecting pyramidal tract) should be defined to distinguish “optimal” from “above threshold” stimulation.

This is an interesting question. In this study, the patients reacted individually to non-optimal settings. Some patients experienced dystonic movements while others had dysarthria. No generalisations about how or which side effects different stimulation settings cause can be made based on the results.

Non-optimal stimulation settings cause changes to EMG signal morphology. With optimal settings DBS regulates the motor control system in a way that pathological synchronisation decreases. Thus, sub-threshold and above threshold stimulation may have similar effects to EMG signal.

Manuscript updated.

>>> Statistical results are not rigorously stated (performed tests and resulting values are missing).

Manuscript updated.

Discussion

>>> The “U-shaped theory” of optimal stimulation parameters needs to be better explained. “EMG parameters had their extremum at the base setup” is not shown in the results section (only relative values in fig2).

Unfortunately we do not understand the comment. Montgomery et al. have suggested suggested that increase in stimulation voltage improves the symptoms only until a certain point is reached. After this point the symptoms get worse if voltage is further increased. This theory has been used as an analogy for interpreting the results of this study.

Manuscript updated.

>>> The whole manuscript needs major editing concerning language and spelling.

Manuscript updated.

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23 Dec 2021

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Reviewers' comments:

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Reviewer #2: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Partly

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Reviewer #2: Yes

Reviewer #3: No

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: No

Reviewer #3: No

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: The authors present a re-structured and re-written manuscript of their work aiming to correlate DBS-effects with EMG-recordings. To me, the manuscript has much improved and almost all of my concerns were satisfactorily answered.

Nevertheless, there are still few concerns:

- The Abstract ends with the sentence “The parameters had their extremum at optimal clinical settings” which is (without having studied the whole manuscript) contextually not understandable and thus needs to be further explained.

- Introduction ll15-17: The authors may leave out these useless phrases concerning DBS mechanisms of action (as their work does not deal with this topic at all) or have to explain the current opinions of DBS mechanisms of action further in detail.

- Discussion ll 226-232: I would interpret this U-shape theory that symptoms may get worse when voltage is further increased by side effects due to current spread to neighbouring structures rather than due to worsening of PD symptoms per se. The latter may become worse when voltage is decreased. Accordingly, authors should also revise (or further explain) the phrase “Adjusting the DBS further, increasing or decreasing voltage of frequency or increasing pulse width, caused the parameters to get worse as more parkinsonian features get to the signal”.

- Reference 33 is obviously not correct.

- The whole manuscript may still profit from a strict proof reading according to spelling and language, the latter preferably by an english native speaker.

Reviewer #3: In their paper Ruona explored the effect of changes in DBS setting on EMG signals . The rationale of the study is well received since optimising DBS parameters is still an empirical, time consuming and rather subjective process. The work build on earlier findings in which the group now aimed to see whether optimal settings could be differentiated from sub-optimal settings. Their key findings were that there were significant differences between the EMG characteristics but not between clinical scores measured with UPDRS scores.

Although the findings are interesting, many answers are still missing. For example in how much % of the cases a combination of the EMG characteristics can predict the optimal settings. This would be more informative. Furthermore, it is very well possible that small changes in DBS settings don’t elicit lead to EMG changes. For this reason, the authors could make use of only those settings that resulted in a different clinical score and perform ROC analyses.

Were wash-out of DBS times taken into account?

Was the inter-rater agreement of the UPDRS scores known?

minor

> abstract > I’m missing numbers in the abstract, significant should be mentioned

> quantify between settings? > this is prob rather difficult, isn’t it easier to differentiate between effective and non-effective parameters?

> intro > more than a decade

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Reviewer #2: No

Reviewer #3: No

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24 Jan 2022

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Partly

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: No

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: No

Reviewer #3: No

We would like to emphasise that we have already provided data underlying the findings described in the manuscript (supplementary_information.xlsx). Unfortunately we are unable to share the raw patient data related to the manuscript due to local regulations and the ethics statement related to the project.

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: No

Reviewer #3: No

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2:

The authors present a re-structured and re-written manuscript of their work aiming to correlate DBS-effects with EMG-recordings. To me, the manuscript has much improved and almost all of my concerns were satisfactorily answered.

Nevertheless, there are still few concerns:

- The Abstract ends with the sentence “The parameters had their extremum at optimal clinical settings” which is (without having studied the whole manuscript) contextually not understandable and thus needs to be further explained.

> Manuscipt updated to clarify this.

- Introduction ll15-17: The authors may leave out these useless phrases concerning DBS mechanisms of action (as their work does not deal with this topic at all) or have to explain the current opinions of DBS mechanisms of action further in detail.

> Manuscript updated.

- Discussion ll 226-232: I would interpret this U-shape theory that symptoms may get worse when voltage is further increased by side effects due to current spread to neighbouring structures rather than due to worsening of PD symptoms per se. The latter may become worse when voltage is decreased. Accordingly, authors should also revise (or further explain) the phrase “Adjusting the DBS further, increasing or decreasing voltage of frequency or increasing pulse width, caused the parameters to get worse as more parkinsonian features get to the signal”.

> Yes, you're right. U-shaped theory concerns "motor performance" and may be interpreted as combination of symptoms and side effects.

>Manuscript updated.

- Reference 33 is obviously not correct.

> Manuscript updated, reference omitted - recurrence quantification analysis is a well established methodology. Detailed references are provided later on the manuscript.

- The whole manuscript may still profit from a strict proof reading according to spelling and language, the latter preferably by an english native speaker.

> Manuscript has been proofread by an english native speaker. The corrections of spelling and language are not indicated in the revised manuscript.

Reviewer #3:

In their paper Ruona explored the effect of changes in DBS setting on EMG signals. The rationale of the study is well received since optimising DBS parameters is still an empirical, time consuming and rather subjective process. The work build on earlier findings in which the group now aimed to see whether optimal settings could be differentiated from sub-optimal settings. Their key findings were that there were significant differences between the EMG characteristics but not between clinical scores measured with UPDRS scores.

- Although the findings are interesting, many answers are still missing. For example in how much % of the cases a combination of the EMG characteristics can predict the optimal settings. This would be more informative.

> This is an interesting suggestion. We want to emphasise, that the nature of the study is more like proof of concept. While the results show that in most of the cases the parameters indicate the optimal amplitude, frequency or pulse width, the number of patients is still low for statistics. Figure 2 has been updated to clarify the differences between the patients. Manuscript has been updated.

- Furthermore, it is very well possible that small changes in DBS settings don’t elicit lead to EMG changes. For this reason, the authors could make use of only those settings that resulted in a different clinical score and perform ROC analyses.

>Contrary to our expectations, there was only small change in clinical parameters (arm tremor and rigidity) during the adjustment, not even turning the stimulator off caused significant increase in these variables. (There was a significant increase in full UPDRS-III assessment though.) Unfortunately the data (N=13) does not allow for further splitting. However we believe that ROC analysis would be an interesting to test in further studies with larger data set.

>Manuscript has been updated to address this.

- Were wash-out of DBS times taken into account?

> The patient's state was let to stabilise minimum of five minutes after the adjustment of DBS before beginning the measurement. We believe that it is enough for rapidly relieving symptoms (rigidity, tremor). Other symptoms may take longer time to stabilise and that is an inherent challenge - the observation time should be much longer. We tried to balance between long enough time for adequate stabilisation while at the same time keeping the total duration of measurements sufficiently short, 2,5 hours.

- Was the inter-rater agreement of the UPDRS scores known?

> Inter-rater agreement was not evaluated in this study. All UPDRS evaluations were made by same experienced neurologist specialised to Parkinson's disease.

minor

- abstract > I’m missing numbers in the abstract, significant should be mentioned

> Manuscript updated: Significant results related to UPDRS and significant changes in recurrence rate (table 2) were included in the abstract.

- quantify between settings? > this is prob rather difficult, isn’t it easier to differentiate between effective and non-effective parameters?

> This is an excellent comment. Manuscript has been updated to emphasise that comparisons were only made between the optimal setup and other setups.

- intro > more than a decade

> Manuscript updated.

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Reviewer #2: No

Reviewer #3: No

Submitted filename: response_to_reviewers.txt

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31 Mar 2022

Changes in elbow flexion EMG morphology during adjustment of deep brain stimulator in advanced Parkinson's disease

PONE-D-21-16366R2

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7 Apr 2022

PONE-D-21-16366R2

Changes in elbow flexion EMG morphology during adjustment of deep brain stimulator in advanced Parkinson's disease

Dear Dr. Ruonala:

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