Assessment of Impaired Finger Independence of Stroke Survivors: A Preliminary study

Jiahao Fan, Henry Shin, Xiaogang Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Hand impairment is prevalent in individuals after stroke. Regaining independent finger control remains challenging in stroke rehabilitation. An efficient rehabilitation program should be able to have the clinicians informed and enable them to prescribe targeted therapies accordingly. To that end, an objective and continuous assessment of finger impairment is highly demanding. The objective of this preliminary work was to quantify the neuromuscular factors that contribute to impairment in independent finger control in chronic stroke survivors. Ten subjects, including five neurologically as control participants and five chronic stroke survivors, participated in our experiments. We obtained high-density electromyographic (HD-EMG) signals of extrinsic finger muscles and fingertip forces, while both stroke survivors 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) and control fingers independently on the affected side of the stroke survivors. 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 could 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.

Original languageEnglish (US)
Title of host publication11th International IEEE/EMBS Conference on Neural Engineering, NER 2023 - Proceedings
PublisherIEEE Computer Society
ISBN (Electronic)9781665462921
StatePublished - 2023
Event11th International IEEE/EMBS Conference on Neural Engineering, NER 2023 - Baltimore, United States
Duration: Apr 25 2023Apr 27 2023

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554


Conference11th International IEEE/EMBS Conference on Neural Engineering, NER 2023
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Mechanical Engineering

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