脑卒中康复中音乐生物反馈的技术框架
A Technical Framework for Musical Biofeedback in Stroke Rehabilitation
摘要：
我们在这里提出了一个广义的低层次的技术框架，旨在提供音乐生物反馈中风后的平衡和步态康复，建立一个迭代的以用户为中心的过程。该框架包括无线可穿戴惯性传感器和使用廉价和开源工具开发的软件界面。该界面支持分层和可调节的音乐合成，在多种训练模式下实时控制生物反馈参数，以及广泛的补充功能。我们评估了系统的技术性能，发现系统具有足够低的环路延迟（~90 ms），良好的传感器范围（>9 m）和低计算负载，即使在其最苛刻的操作模式。在一系列专家访谈中，临床医生认为使用该系统进行的选定培训交互是有意义的，并且与临床协议相关，具有广泛的患者人口统计学可理解的反馈（尽管有时令人不快或不安）。未来的研究将集中在使用这个框架与真实的患者，以进一步发展的相互作用，并衡量其在治疗过程中的影响。
英文摘要：
We here present work a generalized low-level technical framework aimed to provide musical biofeedback in post-stroke balance and gait rehabilitation, built by an iterative user-centered process. The framework comprises wireless wearable inertial sensors and a software interface developed using inexpensive and open-source tools. The interface enables layered and adjustable music synthesis, real-time control over biofeedback parameters in several training modes, and extensive supplementary functionality. We evaluated the system in terms of technical performance, finding that the system has sufficiently low loop delay (~90 ms), good sensor range (>9 m) and low computational load even in its most demanding operation mode. In a series of expert interviews, selected training interactions using the system were deemed by clinicians to be meaningful and relevant to clinical protocols with comprehensible feedback (albeit sometimes unpleasant or disturbing) for a wide patient demographic. Future studies will focus on using this framework with real patients to both develop the interactions further and measure their effects during therapy.
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