Background
The rhythm of music can entrain neurons in motor cortex by way of direct connections between auditory and motor brain regions.
Objective
We
sought to automate an individualized and progressive music-based,
walking rehabilitation program using real-time sensor data in
combination with decision algorithms.
Methods
A
music-based digital therapeutic was developed to maintain high sound
quality while modulating, in real-time, the tempo (ie, beats per minute,
or bpm) of music based on a user’s ability to entrain to the tempo and
progress to faster walking cadences in-sync with the progression of the
tempo. Eleven individuals with chronic hemiparesis completed one
automated 30-minute training visit. Seven returned for 2 additional
visits. Safety, feasibility, and rehabilitative potential (ie, changes
in walking speed relative to clinically meaningful change scores) were
evaluated.
Results
A single, fully automated training visit resulted in increased usual (∆ 0.085 ± 0.027 m/s, P = .011) and fast (∆ 0.093 ± 0.032 m/s, P
= .016) walking speeds. The 7 participants who completed additional
training visits increased their usual walking speed by 0.12 ± 0.03 m/s
after only 3 days of training. Changes in walking speed were highly
related to changes in walking cadence (R2 > 0.70).
No trips or falls were noted during training, all users reported that
the device helped them walk faster, and 70% indicated that they would
use it most or all of the time at home.
Conclusions
In
this proof-of-concept study, we show that a sensor-automated,
progressive, and individualized rhythmic locomotor training program can
be implemented safely and effectively to train walking speed after
stroke. Music-based digital therapeutics have the potential to
facilitate salient, community-based rehabilitation.
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