Robotic Exoskeleton Gait Training During Acute Stroke Inpatient Rehabilitation

Karen J. Nolan, Kiran K. Karunakaran, Kathleen Chervin, Michael R. Monfett, Radhika K. Bapineedu, Neil N. Jasey, Mooyeon Oh-Park

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Stroke is the leading cause of severe disability in adults resulting in mobility, balance, and coordination deficits. Robotic exoskeletons (REs) for stroke rehabilitation can provide the user with consistent, high dose repetition of movement, as well as balance and stability. The goal of this intervention study is to evaluate the ability of a RE to provide high dose gait therapy and the resulting effect on functional recovery for individuals with acute stroke. The investigation included a total of 44 participants. Twenty-two participants received RE gait training during inpatient rehabilitation (RE+SOC Group), and a matched sample of 22 individuals admitted to the same inpatient rehabilitation facility-receiving conventional standard of care treatment (SOC group). The effect of RE training was quantified using total distance walked during inpatient rehabilitation and functional independence measure (FIM). The total distance walked during inpatient rehabilitation showed a significant difference between the SOC and RE+SOC groups. RE+SOC walked twice the distance as SOC during the same duration (time spent in inpatient rehabilitation) of training. In addition, the average change in motor FIM showed a significant difference between the SOC and RE+SOC groups, where the average difference in motor FIM was higher in RE+SOC compared to the SOC group. The results suggest that RE provided increased dosing of gait training without increasing the duration of training during acute stroke rehabilitation. The RE+SOC group increased their motor FIM score (change from admission to discharge) compared to SOC group, both groups were matched for admission motor FIM scores suggesting that increased dosing may have improved motor function.

Original languageEnglish (US)
Article number581815
JournalFrontiers in Neurorobotics
Volume14
DOIs
StatePublished - Oct 30 2020
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Artificial Intelligence

Keywords

  • dosing
  • exoskeleton
  • functional independence measure
  • gait
  • rehabilitation
  • stroke
  • wearable robotics

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