Literature DB >> 30047893

Comparing Surface and Intramuscular Electromyography for Simultaneous and Proportional Control Based on a Musculoskeletal Model: A Pilot Study.

Dustin L Crouch, Lizhi Pan, William Filer, Jonathan W Stallings, He Huang.   

Abstract

Simultaneous and proportional control (SPC) of neural-machine interfaces uses magnitudes of smoothed electromyograms (EMG) as control inputs. Though surface EMG (sEMG) electrodes are common for clinical neural-machine interfaces, intramuscular EMG (iEMG) electrodes may be indicated in some circumstances (e.g., for controlling many degrees of freedom). However, differences in signal characteristics between sEMG and iEMG may influence SPC performance. We conducted a pilot study to determine the effect of electrode type (sEMG and iEMG) on real-time task performance with SPC based on a novel 2-degree-of-freedom EMG-driven musculoskeletal model of the wrist and hand. Four able-bodied subjects and one transradial amputee performed a virtual posture matching task with either sEMG or iEMG. There was a trend of better task performance with sEMG than iEMG for both able-bodied and amputee subjects, though the difference was not statistically significant. Thus, while iEMG may permit targeted recording of EMG, its signal characteristics may not be as ideal for SPC as those of sEMG. The tradeoff between recording specificity and signal characteristics is an important consideration for development and clinical implementation of SPC for neural-machine interfaces.

Mesh:

Year:  2018        PMID: 30047893     DOI: 10.1109/TNSRE.2018.2859833

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  4 in total

1.  Ultrasound Echogenicity as an Indicator of Muscle Fatigue during Functional Electrical Stimulation.

Authors:  Qiang Zhang; Ashwin Iyer; Krysten Lambeth; Kang Kim; Nitin Sharma
Journal:  Sensors (Basel)       Date:  2022-01-03       Impact factor: 3.576

2.  Fused ultrasound and electromyography-driven neuromuscular model to improve plantarflexion moment prediction across walking speeds.

Authors:  Qiang Zhang; Natalie Fragnito; Jason R Franz; Nitin Sharma
Journal:  J Neuroeng Rehabil       Date:  2022-08-09       Impact factor: 5.208

3.  Electroencephalogram and surface electromyogram fusion-based precise detection of lower limb voluntary movement using convolution neural network-long short-term memory model.

Authors:  Xiaodong Zhang; Hanzhe Li; Runlin Dong; Zhufeng Lu; Cunxin Li
Journal:  Front Neurosci       Date:  2022-09-23       Impact factor: 5.152

Review 4.  Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges.

Authors:  Kostas Nizamis; Alkinoos Athanasiou; Sofia Almpani; Christos Dimitrousis; Alexander Astaras
Journal:  Sensors (Basel)       Date:  2021-03-16       Impact factor: 3.576

  4 in total

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