We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App

New Robotic System Assesses Mobility After Stroke

By HospiMedica International staff writers
Posted on 23 Nov 2023
Print article
Image: The robotic arm provides precise 3D spatial information to help stroke survivors (Photo courtesy of USC Viterbi)
Image: The robotic arm provides precise 3D spatial information to help stroke survivors (Photo courtesy of USC Viterbi)

Worldwide, strokes affect over 15 million individuals annually, leaving three-quarters of survivors with arm and hand limitations, including weakness and paralysis. Overcoming the tendency to underuse the affected arm, a phenomenon known as "arm nonuse" or "learned nonuse," is crucial for rehabilitation, but gauging arm usage outside clinical environments poses a significant challenge. Observing natural behavior often requires discreet monitoring methods. Addressing this need, researchers have now designed an innovative robotic system that collects accurate data on how stroke survivors spontaneously use their arms.

Developed by a team at USC Viterbi in Los Angeles, CA, USA, this cutting-edge approach employs a robotic arm to gather 3D spatial data about arm movements. The system utilizes machine learning algorithms to analyze this data, producing a reliable "arm nonuse" metric that can greatly assist clinicians in assessing rehabilitation progress. To make the experience engaging and supportive, a socially assistive robot (SAR) offers instructions and encouragement throughout the process. In their study, the USC Viterbi team worked with 14 participants who had been right-hand dominant prior to experiencing a stroke. The participants began by placing their hands on a 3D-printed box equipped with touch sensors, which served as the system's starting position. The SAR introduced the system's functionality and provided positive feedback. The robot arm would then move a button to various predetermined locations, initiating the "reaching trial" when the button lit up and the participant was cued to move.

The trial consisted of two phases: first, participants used their naturally preferred hand, mimicking typical daily activities. In the second phase, they were instructed to use their stroke-affected arm, akin to exercises performed in therapy or clinical settings. The team's machine learning analysis focused on three key metrics: the probability of arm use, the time taken to reach the target, and the successful completion of the reach. The study revealed significant differences in hand preference and time taken to reach targets among chronic stroke survivors. The method proved reliable over multiple sessions, with participants finding it easy to use and scoring it highly in terms of user experience.

Additionally, all participants deemed the interaction safe. The team received feedback suggesting that future enhancements could include personalized features, integrating additional behavioral data, and varying the tasks. This innovative approach not only demonstrated consistency and positive user experiences but also highlighted variations in arm use among participants. These insights are vital for healthcare professionals to more accurately monitor and facilitate stroke recovery.

“This work brings together quantitative user-performance data collected using a robot arm, while also motivating the user to provide a representative performance thanks to a socially assistive robot,” said Maja Matarić, study co-author and Chan Soon-Shiong Chair and Distinguished Professor of Computer Science, Neuroscience, and Pediatrics. “This novel combination can serve as a more accurate and more motivating process for stroke patient assessment.”

Related Links:
USC Viterbi 

Gold Member
Disposable Protective Suit For Medical Use
Disposable Protective Suit For Medical Use
Gold Member
SARS‑CoV‑2/Flu A/Flu B/RSV Sample-To-Answer Test
SARS‑CoV‑2/Flu A/Flu B/RSV Cartridge (CE-IVD)
Silver Member
Compact 14-Day Uninterrupted Holter ECG
Ultrasound Needle Guide
Ultra-Pro II

Print article


Surgical Techniques

view channel
Image: Real-time navigation is a useful tool for ablation procedures to destroy tumors in the liver (Photo courtesy of University of Cincinnati)

Real-Time Navigation Found To Be Useful Tool for Liver Cancer Procedures

Liver cancer, ranking as the world's fourth most common cause of cancer-related deaths, presents a significant health challenge. For certain patients, ablation offers a less invasive alternative to traditional... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The new eye-safe laser technology can diagnose traumatic brain injury (Photo courtesy of 123RF)

Novel Diagnostic Hand-Held Device Detects Known Biomarkers for Traumatic Brain Injury

The growing need for prompt and efficient diagnosis of traumatic brain injury (TBI), a major cause of mortality globally, has spurred the development of innovative diagnostic technologies.... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.