Robotic therapy for stroke patients

Strokes leave 5 million people with long-term impairments each year, and a growing shortage of physical therapists makes it hard for them to get the care they need. A new approach tries to solve that problem by combining artificial intelligence and human therapy.

每年中风导致 500 万人留下长期残疾，而物理治疗师日益短缺，使得患者难以获得所需的护理。一种新的方法试图通过结合人工智能和人类治疗来解决这个问题。

Johannes Lachner, a former MIT postdoc who is now an assistant professor at Purdue University, and Noah Geiger, a former visiting student at MIT, developed a robotic system that uses generative AI and real-time force feedback to learn from real therapists. Drawing on what it’s learned, it gives patients just the right amount of assistance during physical rehabilitation exercises like reaching, lifting their arms, and performing tasks of daily living.

曾任麻省理工学院博士后、现为普渡大学助理教授的 Johannes Lachner 与曾任麻省理工学院访问学生的 Noah Geiger 开发了一套机器人系统，该系统利用生成式人工智能和实时力反馈向真正的治疗师学习。通过运用所学知识，它能在患者进行伸展、抬臂和执行日常生活任务等物理康复训练时，提供恰到好处的辅助。

The goal is “not to replace therapists, but to extend their reach,” Lachner says. “Initial robotic experiments have already demonstrated the feasibility of this approach,” he reports. “The next phase of the project aims to develop therapist-specific models and evaluate them in a long-term clinical study with the same patients who previously received manual therapy.” Beyond that, he envisions possible applications in contact-rich industrial settings or collaborative workspaces.

Lachner 表示，其目标“不是取代治疗师，而是扩展他们的服务范围”。他报告称：“初步的机器人实验已经证明了这种方法的可行性。该项目的下一阶段旨在开发针对特定治疗师的模型，并在之前接受过人工治疗的同一批患者身上进行长期临床研究评估。”此外，他还设想了该技术在接触密集型工业环境或协作工作空间中的潜在应用。