Department of Physical Therapy, College of Health and Rehabilitation Sciences, Sargent College, Boston University, Boston, MA, USA.
MedRhythms, Portland, ME, USA.
Neurorehabil Neural Repair. 2023 May;37(5):255-265. doi: 10.1177/15459683231174223. Epub 2023 Jun 5.
Post-stroke care guidelines highlight continued rehabilitation as essential; however, many stroke survivors cannot participate in outpatient rehabilitation. Technological advances in wearable sensing, treatment algorithms, and care delivery interfaces have created new opportunities for high-efficacy rehabilitation interventions to be delivered autonomously in any setting (ie, clinic, community, or home).
We developed an autonomous rehabilitation system that combines the closed-loop control of music with real-time gait analysis to fully automate patient-tailored walking rehabilitation. Specifically, the mechanism-of-action of auditory-motor entrainment is applied to induce targeted changes in the post-stroke gait pattern by way of targeted changes in music. Using speed-controlled biomechanical and physiological assessments, we evaluate in 10 individuals with chronic post-stroke hemiparesis the effects of a fully-automated gait training session on gait asymmetry and the energetic cost of walking.
Post-treatment reductions in step time (Δ: -12 ± 26%, = .027), stance time (Δ: -22 ± 10%, = .004), and swing time (Δ: -15 ± 10%, = .006) asymmetries were observed together with a 9 ± 5% reduction ( = .027) in the energetic cost of walking. Changes in the energetic cost of walking were highly dependent on the degree of baseline energetic impairment ( =- .90, < .001). Among the 7 individuals with a baseline energetic cost of walking larger than the normative value of healthy older adults, a 13 ± 4% reduction was observed after training.
The closed-loop control of music can fully automate walking rehabilitation that markedly improves walking after stroke. Autonomous rehabilitation delivery systems that can safely provide high-efficacy rehabilitation in any setting have the potential to alleviate access-related care gaps and improve long-term outcomes after stroke.
脑卒中后护理指南强调持续康复至关重要;然而,许多脑卒中幸存者无法参与门诊康复。可穿戴传感器、治疗算法和护理传递接口方面的技术进步为在任何环境(即诊所、社区或家庭)中自主提供高效康复干预措施创造了新的机会。
我们开发了一种自主康复系统,该系统将音乐的闭环控制与实时步态分析相结合,以实现患者量身定制的步行康复的完全自动化。具体而言,听觉-运动同步作用的作用机制被应用于通过音乐的靶向变化来诱导脑卒中后步态模式的靶向变化。我们使用速度控制的生物力学和生理评估,在 10 名慢性脑卒中偏瘫患者中评估完全自动化的步态训练对步态不对称和行走能量成本的影响。
治疗后观察到步时(Δ:-12 ± 26%,=.027)、站立时间(Δ:-22 ± 10%,=.004)和摆动时间(Δ:-15 ± 10%,=.006)不对称性的减少,以及行走能量成本降低 9 ± 5%(=.027)。行走能量成本的变化与基线能量损害程度高度相关(= -.90,<.001)。在 7 名基线行走能量成本大于健康老年人的正常参考值的患者中,训练后观察到 13 ± 4%的降低。
音乐的闭环控制可以完全自动化步行康复,显著改善脑卒中后的步行能力。能够在任何环境中安全提供高效康复的自主康复输送系统有潜力缓解与获取相关的护理差距,并改善脑卒中后的长期结果。