BACKGROUND AND PURPOSE: Motor symptoms of Parkinson's disease (PD) are typically assessed using clinical scales such as the Unified Parkinson's Disease Rating Scale, but clinical scales are insensitive to subtle changes early in the disease process. The goal of this project was to use current sensing technology to develop a quantitative assessment tool to document fine motor deficits in PD based on the ability to control grip force output. The assessment was designed to challenge deficits commonly encountered as a result of PD, including dual-task performance of a motor task and a cognitive task simultaneously. METHODS: Two force sensors were used to measure the isometric pinch grip force between the thumb and index finger in 30 individuals with PD and 30 control participants of similar age without disability. Participants performed a target force tracking task with each of two different target waveforms (sinusoidal or pseudorandom) under each of three different cognitive load conditions (none, subtract 1, and subtract 3). Dependent variables calculated from the force sensor data included root mean square error, tremor integral, and lag. RESULTS: In general, individuals with PD showed significantly less accuracy in generating the target forces as shown by larger root mean square error compared with controls (P < 0.001). They also showed greater amounts of tremor and lag compared with controls (P = 0.001 and <0.001, respectively). Deficits were more pronounced during the cognitive multitasking component of the test. DISCUSSION AND CONCLUSIONS: These results will serve as a preliminary work for the development of a clinical biomarker for PD that may help to identify subtle deficits in fine motor control early in the disease process and facilitate tracking of disease progression with time.
BACKGROUND AND PURPOSE: Motor symptoms of Parkinson's disease (PD) are typically assessed using clinical scales such as the Unified Parkinson's Disease Rating Scale, but clinical scales are insensitive to subtle changes early in the disease process. The goal of this project was to use current sensing technology to develop a quantitative assessment tool to document fine motor deficits in PD based on the ability to control grip force output. The assessment was designed to challenge deficits commonly encountered as a result of PD, including dual-task performance of a motor task and a cognitive task simultaneously. METHODS: Two force sensors were used to measure the isometric pinch grip force between the thumb and index finger in 30 individuals with PD and 30 control participants of similar age without disability. Participants performed a target force tracking task with each of two different target waveforms (sinusoidal or pseudorandom) under each of three different cognitive load conditions (none, subtract 1, and subtract 3). Dependent variables calculated from the force sensor data included root mean square error, tremor integral, and lag. RESULTS: In general, individuals with PD showed significantly less accuracy in generating the target forces as shown by larger root mean square error compared with controls (P < 0.001). They also showed greater amounts of tremor and lag compared with controls (P = 0.001 and <0.001, respectively). Deficits were more pronounced during the cognitive multitasking component of the test. DISCUSSION AND CONCLUSIONS: These results will serve as a preliminary work for the development of a clinical biomarker for PD that may help to identify subtle deficits in fine motor control early in the disease process and facilitate tracking of disease progression with time.
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