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Innovative Wearable Robot Adapts to Individual Movement Patterns for Stroke and ALS Patients

Innovative Wearable Robot Adapts to Individual Movement Patterns for Stroke and ALS Patients

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A new wearable robotic device personalizes support for stroke and ALS patients by adapting to individual arm movement patterns through advanced machine learning, improving daily function and independence.

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Researchers from Harvard University have developed a groundbreaking soft, wearable robotic device designed to assist individuals with movement impairments due to conditions such as stroke and amyotrophic lateral sclerosis (ALS). This advanced technology personalizes support by dynamically adapting to each user's unique arm movement patterns, thanks to the integration of machine learning algorithms.

The device features a sensor-laden vest with an inflatable balloon positioned under the arm, which inflates and deflates to provide mechanical assistance during movement. A major upgrade in its software now allows the robot to learn from sensors that track both motion and pressure, enabling it to deliver assistance tailored precisely to each user's capabilities. This personalization enhances the natural feel of support, making everyday activities like eating or reaching more manageable.

The research, led by Conor Walsh and published in Nature Communications, involved collaboration with clinicians at Massachusetts General Hospital and Harvard Medical School. The team tested the device with individuals suffering from stroke and ALS, including patient advocate Kate Nycz, who has been living with ALS since 2018. Nycz has actively participated in user testing, providing feedback that has contributed to multiple iterations of the device.

Significant improvements include the robot's ability to accurately distinguish individual shoulder movements with 94% accuracy and significantly reduce the effort required to lower the arm. Users experienced increased ranges of motion across multiple joints, resulting in more precise and efficient movements without compensatory body adjustments.

The core advancement lies in the application of machine learning combined with a physics-based model that estimates the minimum pressure required for effective support. This combination allows the robot to adapt instantly, offering more nuanced assistance tailored to each movement, which is particularly beneficial for tasks like eating or drinking.

Extensive testing with nine volunteers, including those with stroke and ALS, demonstrated promising results. The device not only improved functional movements but also increased comfort and ease of use, emphasizing its potential for widespread clinical and home use.

The developers see this technology as applicable to a broad spectrum of upper limb impairments, aiming to eventually enable patients to operate the device independently at home. Ongoing refinements are focused on making the system more versatile and accessible for everyday life.

This innovation represents a significant step forward in assistive robotics, offering personalized movement support that could dramatically improve quality of life for those with neurological impairments.

Source: https://medicalxpress.com/news/2025-08-wearable-robot-individual-arm-movement.html

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