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Hand impairment is prevalent in individuals after stroke. Regaining independent finger control is especially challenging. An objective and continuous assessment of finger impairment could inform clinicians and allow them to prescribe targeted therapies. The objective of this preliminary work was to quantify the neuromuscular factors that contribute to impairment in independent finger control in chronic stroke survivors. We obtained high-density electromyographic (HD-EMG) signals of extrinsic finger muscles and fingertip forces, while stroke or control participants were instructed to produce independent finger forces. We observed an impaired ability to isolate individual muscle compartment activation (i.e., co-activation of muscle compartment). This muscle co-activation pattern correlated with finger independence as well as clinical assessment scales on hand impairment. Our preliminary work showed that HD-EMG recordings can be used to continuously monitor activation abnormalities of small finger muscles in contribution to impaired finger independence. With further development, the outcomes can provide a basis for clinical decision making to reduce hand impairments of stroke survivors.
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Distribution of M-Wave and H-Reflex in Hand Muscles Evoked via Transcutaneous Nerve Stimulation: A Preliminary Report
Neuromuscular electrical stimulation (NMES) targeting the muscle belly is commonly used to restore muscle strength in individuals with neurological disorders. However, early onset of muscle fatigue is a major limiting factor. Transcutaneous nerve stimulation (TNS) can delay muscle fatigue compared with traditional NMES techniques. However, the recruitment of Ia afferent fibers has not be specifically targeted to maximize muscle activation through the reflex pathway, which can lead to more orderly recruitment of motor units, further delaying fatigue. This preliminary study assessed the distribution of M-wave and H-reflex of intrinsic and extrinsic finger muscles. TNS was delivered using an electrode array placed along the medial side of the upper arm. Selective electrode pairs targeted the median and ulnar nerves innervating the finger flexors. High-density electromyography (HD EMG) was utilized to quantify the spatial distribution of the elicited activation of finger intrinsic and extrinsic muscles along the hand and forearm. The spatial patterns were characterized through isolation of the M-wave and H-reflex across various stimulation levels and EMG channels. Our preliminary results showed that, by altering the stimulation amplitude, distinct M-wave and H-reflex responses were evoked across EMG channels. In addition, distinct stimulation locations appeared to result in varied levels of reflex recruitment. Our findings indicate that it is possible to adjust stimulation parameters to maximize reflex activation, which can potentially facilitate physiological recruitment order of motoneurons.
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- PAR ID:
- 10319955
- Date Published:
- Journal Name:
- 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Converging evidence in human and animal models suggests that exogenous stimulation of the motor cortex (M1) elicits responses in the hand with similar modular structure to that found during voluntary grasping movements. The aim of this study was to establish the extent to which modularity in muscle responses to transcranial magnetic stimulation (TMS) to M1 resembles modularity in muscle activation during voluntary hand movements involving finger fractionation. EMG was recorded from eight hand-forearm muscles in nine healthy individuals. Modularity was defined using non-negative matrix factorization to identify low rank approximations (spatial muscle synergies) of the complex activation patterns of EMG data recorded during high density TMS mapping of M1 and voluntary formation of gestures in the American Sign Language alphabet. Analysis of synergies as a set, and individually, revealed greater than chance similarity between those derived from TMS and those derived from voluntary movement. Both datasets included synergies dominated by single intrinsic hand muscles presumably to meet the demand for highly fractionated finger movement. These results suggest a cortical role in combining corticospinal connectivity to individual intrinsic hand muscles with modular mulit-muscle activation via synergies.more » « less
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Abstract Accurate anatomical matching for patient-specific electromyographic (EMG) mapping is crucial yet technically challenging in various medical disciplines. The fixed electrode construction of multielectrode arrays (MEAs) makes it nearly impossible to match an individual's unique muscle anatomy. This mismatch between the MEAs and target muscles leads to missing relevant muscle activity, highly redundant data, complicated electrode placement optimization, and inaccuracies in classification algorithms. Here, we present customizable and reconfigurable drawn-on-skin (DoS) MEAs as the first demonstration of high-density EMG mapping from in situ-fabricated electrodes with tunable configurations adapted to subject-specific muscle anatomy. The DoS MEAs show uniform electrical properties and can map EMG activity with high fidelity under skin deformation-induced motion, which stems from the unique and robust skin-electrode interface. They can be used to localize innervation zones (IZs), detect motor unit propagation, and capture EMG signals with consistent quality during large muscle movements. Reconfiguring the electrode arrangement of DoS MEAs to match and extend the coverage of the forearm flexors enables localization of the muscle activity and prevents missed information such as IZs. In addition, DoS MEAs customized to the specific anatomy of subjects produce highly informative data, leading to accurate finger gesture detection and prosthetic control compared with conventional technology.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/EMBC46164.2021.9630300
