Abstract
Characterizing ALS disease progression using surface electromyography: a feasibility study
Muscle & nerve, v 66(S2), pp S12-S12
01 Nov 2022
Abstract
Background: Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by the loss of motor neurons with resultant progressive weakness. Motor neuron loss is typically assessed indirectly using methods such as grip strength, signs of chronic partial denervation in electromyography (EMG), functional inventories, and compound muscle action potential., etc. However, measures like the ALS Functional Rating Scale-Revised (ALSFRS-R) are subjective and can only extract a snapshot of the dynamic progression of disease over time. Surface EMG (sEMG) is a technique in which electrodes are placed on the skin surface to detect the electrical activity of the underlying muscle. sEMG sensors are accessible and noninvasive, making frequent remote collection possible in monitoring ALS progression.
Objective: The purpose of this research is to determine the feasibility of wearable sEMG in longitudinal data collection of ALS progression, evaluate the relationship between sEMG, the ALSFRS-R, and grip strength, and determine if sEMG methods can differentiate between pALS and healthy volunteers (HV).
Methods: ALS subjects (PALS) and healthy volunteers (HV) were recruited from the ALS/MDA Center for Hope and families. Trained staff collected sEMG, ALSFRS-R, and grip strength data every 3-weeks over a 7-month period for pALS and at a single time point for HV. To determine the relationship between sEMG and ALSFRS-R score, time-frequency domain features were used to regress ALSFRS-R onto sEMG and grip strength data. To assess whether sEMG could distinguish between pALS and HV, receiver operating characteristic curve analysis was performed.
Results: Six pALS and six age- and sex-matched HV participated in the study. Data collection for this study is ongoing and the results of this longitudinal study will be presented.
Conclusions: Results from this investigation will offer insights into the predictive potential of sEMG which can lead to better stratification of disease progression that can impact clinical decision-making, assessment, and intervention.
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Details
- Title
- Characterizing ALS disease progression using surface electromyography: a feasibility study
- Creators
- Baothy Huynh - PISON Technology (United States, Boston)Mike Kowalczyk - PISON Technology (United States, Boston)Sam Karnes - PISON Technology (United States, Boston)Henry Valk - PISON Technology (United States, Boston)Aiden Mastronardo - Drexel UniversityYashodha Ravichandran - Drexel University, School of Biomedical Engineering, Science, and Health SystemsGrace Feldman - Drexel University, School of Biomedical Engineering, Science, and Health SystemsBadrudin Sheikh - Drexel University, School of Biomedical Engineering, Science, and Health SystemsRamya Ashish - Drexel University, School of Biomedical Engineering, Science, and Health SystemsEmma Dryden - Drexel UniversitySara Feldman - Temple UniversityTerry Heiman-Patterson - Temple University
- Publication Details
- Muscle & nerve, v 66(S2), pp S12-S12
- Conference
- 21st Annual Meeting of the Northeast ALS Consortium, 21st (Clearwater Beach, Florida, United States, 01 Nov 2022–03 Nov 2022)
- Publisher
- Wiley Subscription Services, Inc
- Number of pages
- 1
- Resource Type
- Abstract
- Language
- English
- Academic Unit
- Drexel Solutions Institute; College of Arts and Sciences; School of Biomedical Engineering, Science, and Health Systems
- Other Identifier
- 991019276214404721