Clinical Use of Surface Electromyography to Track Acute Upper Extremity Muscle Recovery after Stroke: A Descriptive Case Study of a Single Patient
| Autor: | Christina Papazian, Heather A. Feldner, Katherine M. Steele, Keshia M. Peters, Claire J. Creutzfeldt |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
030506 rehabilitation
medicine.medical_specialty Technology medicine.medical_treatment Wearable computer Electromyography surface electromyography Industrial and Manufacturing Engineering Session (web analytics) Article 03 medical and health sciences case study 0302 clinical medicine Physical medicine and rehabilitation Artificial Intelligence Acute care medicine upper extremity Stroke Neurorehabilitation T57-57.97 neurorehabilitation Rehabilitation Applied mathematics. Quantitative methods medicine.diagnostic_test business.industry Applied Mathematics medicine.disease sub-acute rehabilitation stroke Human-Computer Interaction acute care Control and Systems Engineering 0305 other medical science business Stroke recovery 030217 neurology & neurosurgery Information Systems |
| Zdroj: | Applied system innovation Applied System Innovation, Vol 4, Iss 32, p 32 (2021) Applied System Innovation; Volume 4; Issue 2; Pages: 32 |
| ISSN: | 2571-5577 |
| Popis: | Arm recovery varies greatly among stroke survivors. Wearable surface electromyography (sEMG) sensors have been used to track recovery in research; however, sEMG is rarely used within acute and subacute clinical settings. The purpose of this case study was to describe the use of wireless sEMG sensors to examine changes in muscle activity during acute and subacute phases of stroke recovery, and understand the participant’s perceptions of sEMG monitoring. Beginning three days post-stroke, one stroke survivor wore five wireless sEMG sensors on his involved arm for three to four hours, every one to three days. Muscle activity was tracked during routine care in the acute setting through discharge from inpatient rehabilitation. Three- and eight-month follow-up sessions were completed in the community. Activity logs were completed each session, and a semi-structured interview occurred at the final session. The longitudinal monitoring of muscle and movement recovery in the clinic and community was feasible using sEMG sensors. The participant and medical team felt monitoring was unobtrusive, interesting, and motivating for recovery, but desired greater in-session feedback to inform rehabilitation. While barriers in equipment and signal quality still exist, capitalizing on wearable sensing technology in the clinic holds promise for enabling personalized stroke recovery. |
| Databáze: | OpenAIRE |
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