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.

中文翻译：

---

基于音乐的数字治疗：中风后渐进式和个性化的基于节奏的步行训练计划的概念验证自动化

背景音乐的节奏可以通过听觉和运动大脑区域之间的直接连接来带动运动皮层中的神经元。目标 我们寻求使用实时传感器数据结合决策算法，使基于音乐的个性化渐进式步行康复计划自动化。方法 开发了一种基于音乐的数字疗法，以保持高音质，同时实时调节音乐的节奏（即每分钟节拍数，或 bpm），这是基于用户对节奏的掌握能力并加快速度的能力。步行节奏与节奏的进展同步。11 名慢性偏瘫患者完成了一次 30 分钟的自动化培训访问。七人又回来了 2 次。安全性、可行性和康复潜力（即，评估步行速度相对于临床上有意义的变化评分的变化。结果 一次完全自动化的培训访问导致通常 (∆ 0.085 ± 0.027 m/s, P = .011) 和快速 (∆ 0.093 ± 0.032 m/s, P = .016) 步行速度增加。完成额外培训访问的 7 名参与者仅在培训 3 天后就将他们通常的步行速度提高了 0.12 ± 0.03 m/s。步行速度的变化与步行节奏的变化高度相关（R2 > 0.70）。训练期间没有出现绊倒或跌倒的情况，所有用户都报告说该设备帮助他们走得更快，70% 的人表示他们大部分时间或所有时间都在家里使用它。结论在这项概念验证研究中，我们展示了一种传感器自动化、渐进式、并且可以安全有效地实施个性化有节奏的运动训练计划，以训练中风后的步行速度。基于音乐的数字疗法有可能促进显着的、基于社区的康复。