MIT and Massachusetts General Hospital researchers have created a system that tracks movement and engages muscles for unattended physical recovery, which could help with injury healing and good mobility more for the elderly and athletes, they said.
WHY IT IMPORTANT
Disabilities benefit from physical rehabilitation, but there are not enough physiotherapists to go around.
To better support data-driven unsupervised rehabilitation for athletes during injury recovery, patients currently undergoing physical therapy, or those with limited physical physical, the MIT Computer Science and Artificial Intelligence Laboratory and MGH researchers have created a sensor-based wearable and virtual reality platform, MuscleRehab.
The system calculates muscle involvement and displays it on a virtual skeletal muscle avatar. It uses an imaging technique called electrical impedance tomography to measure how muscles interact with a VR headset and tracking suit that allows patients to watch themselves perform alongside a physical therapist. physical.
The researchers, who are preparing to present their work for the first time, say studies of the system show that monitoring and visualizing muscle involvement in physical recovery unsupervised may improve the accuracy of therapy and post-rehabilitation assessment, and may prevent re-injury.
“By proactively measuring deep muscle engagement, we were able to observe whether the data showed any abnormalities,” said Junyi Zhu, MIT CSAIL PhD student and lead author of the MuscleRehab paper. often compared to the patient’s base or not, to provide insight into the potential trajectory of the muscle. notification.
The system includes a training mode with pre-recorded baselines for that mode and streaming of avatars with muscle engagement in real time.
Patients wear VR and tracking suits to collect their 3-D motion data, then perform various exercises such as lunges, knee flexions, weight lifts, leg lifts, knee extensions, sitting squat, fire hose and bridge measure quadriceps, sartorius, hamstring and supplemental activity.
The EIT sensor board comes with two electrode-filled straps that are slid into the user’s upper thigh to capture 3D volumetric data. Using a motion capture system, EIT-sensing data shows actively activated muscles on the screen, where the muscles become darker with more interaction.
The team compared exercise accuracy with and without a wearable EIT device. In both cases, their avatars performed alongside a physical therapist.
A professional PT explained which muscle groups are supposed to work in each exercise. They compared the two results – with only motion tracking data overlaid on their patient avatars, and added EIT sensor straps that provide information and visualization of muscle movement and engagement.
By visualizing both muscle engagement and movement data during these unsupervised exercises rather than mere movement, the overall accuracy of the exercises improved by 15% among test subjects.
The researchers also compared the amount of time during exercises where the exact muscle group was activated with and without the wearable.
By monitoring and recording data most interactively, reported PTs have a much better understanding of the quality of their patients’ exercise and that helps to better assess their current and exercise regimens based on on those stats.
Zhu is interested in finding a better way than electromyography used by some wearables to sense the engagement (blood flow, stretching, contraction) of different muscle layers. and was inspired by EIT, which measures muscle electrical conductivity and is commonly used to monitor lung function, detect chest tumors, and diagnose pulmonary embolism.
Currently, MuscleRehab focuses on the upper thighs and major internal muscle groups but can extend to the glutes.
The paper’s co-authors include scientist Hamid Ghaednia, lecturer in the Department of Orthopedic Surgery at Harvard Medical School and co-director of the Center for Physical Artificial Intelligence at Mass General Hospital, and Dr. Joseph Schwab , director of the Center for Orthopedic Spine, director of spinal oncology and co-director of the Stephan L. Harris Chordoma Center and associate professor of orthopedic surgery at Harvard Medical School.
TREND TO BIGGER WOMAN
There is an increasing trend to use technologies such as remote patient monitoring to care for patients and ease the burden on hospitals and service providers.
Dr Waqaas Al-Siddiq, president, CEO and founder of Biotricity, said: IT news about healthcare March.
“We were able to raise RPM by looking at existing diagnostic devices for each condition, finding sensors that could be integrated into wireless devices, and creating solutions,” he said. continuously, clinically relevant.
Just as RPM can dramatically reduce hospital visits and emergency room visits, new sensor-based technologies can enhance home healthcare approaches and have potential to improve outcomes and reduce in-person visits.
ON PROFILE
“This work advances EIT, a conventional approach used in medical settings, with a view to improving the quality of life,” said Yang Zhang, assistant professor of electrical and computer engineering at the UCLA Samueli School of Engineering. ingenious and unique combination with virtual reality.
“Rehabilitation support apps can have a wide impact across society to help patients safely and effectively conduct physical rehabilitation at home.
Andrea Fox is the senior editor of Healthcare IT News.
Email: [email protected]
Healthcare IT News is a HIMSS publication.
