A Tailored Music-Motor Therapy and Real-Time Biofeedback Mobile Phone App (‘GotRhythm’) to Promote Rehabilitation Following Stroke: A Pilot Study

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Abstract

Background: Stroke persists as an important cause of long-term disability world-wide with the need for rehabilitation strategies to facilitate plasticity and improve motor function in stroke survivors. Rhythm-based interventions can improve motor function in clinical populations. This study tested a novel music-motor software application ‘GotRhythm’ on motor function after stroke. Methods: Participants were 22 stroke survivors undergoing inpatient rehabilitation in a subacute stroke ward. Participants were randomised to the GotRhythm intervention (combining individualised music and augmented auditory feedback along with wearable sensors to deliver a personalised rhythmic auditory stimulation training protocol) or usual care. Intervention group participants were offered 6-weeks of the GotRhythm intervention, consisting of a supervised 20-minute music-motor therapy session using GotRhythm conducted 3 times a week for 6 weeks. The primary feasibility outcomes were adherence to the intervention and physical function (change in the Fugl-Meyer Assessment of Motor Recovery score) measured at baseline, after 3-weeks and at end of the intervention period (6-weeks). Results: Three of 10 participants randomised to the intervention did not receive any of the GotRhythym music-motor therapy. Of the remaining 7 intervention group participants, only 5 completed the 3-week mid-intervention assessment and only 2 completed the 6-week post-intervention assessment. Participants who used the intervention completed 5 (IQR 4,7) sessions with total ‘dose’ of the intervention of 70 (40, 201) minutes. Conclusion: Overall, adherence to the intervention was poor, highlighting that application of technology assisted music-based interventions for stroke survivors in clinical environments is challenging along with usual care, recovery, and the additional clinical load.

Original languageEnglish
Number of pages6
JournalNeuroscience Insights
Volume17
DOIs
Publication statusPublished - 19 May 2022

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