Physical therapy could be useful for many chronic impairments, but since there aren't enough physical therapists around, almost 75% of the years spent with chronic disability go untreated, according to Interesting Engineering.
The issues facing the profession are getting worse as a result of the documenting of cases of major illnesses and the fact that the number of patients is growing at a similar rate to population growth and aging.
Hence, a physical rehabilitation system that is unsupervised was developed as a result of the deficit in the muscle-motion treatment plans or the language a physical therapist (PT) is taught to understand.
The Birth of MuscleRehab
Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital (MGH) have developed a program called MuscleRehab that aims to assist patients in finding relief even without a PT, as reported first by Interesting Engineering.
Three types of capture are used: motion tracking to record movement, a muscle activity measurement imaging technology called Electrical Impedance Tomography (EIT), and a virtual reality (VR) headset and tracking suit.
The patient can witness their performance alongside a physical therapist thanks to VR and a special suit.
The researchers were able to assess the exercise's accuracy under those two circumstances and had a licensed therapist review the outcomes. The physical therapist could then describe which muscle groups should be used for each exercise.
The total accuracy of the workouts increased by 15% with the visualization of both muscle engagement and motion data during an unsupervised exercise program.
IoT and AI
These systems are made up of various sensors that collaborate in an Internet of Things (IoT) environment.
Artificial intelligence systems use inference modeling to evaluate how each muscle moves and, from the data, which muscle groups, such as surface or deep, are performing the most beneficial workout, as per Interesting Engineering.
This type of exercise imaging is comparable in using an image of the activity and superimposing it on a muscle area. After recording the motion and engagement, a licensed physical therapist will analyze the information and make exercise recommendations.
The EIT sensor board serves as MuscleRehab's brain. Two straps with electrodes are fastened to the upper thigh of the suit to gather 3D volumetric data.
The researchers employed OptiTrack, which combines 39 markers and a variety of cameras to detect motion at extremely high frame rates for motion capture.
This then displays the highlighted muscle that was stimulated on the VR screen by changing its color to a darker shade than the surrounding muscles.
"We wanted our sensing scenario to not be limited to a clinical setting, to better enable data-driven unsupervised rehabilitation for athletes in injury recovery, patients currently in physical therapy, or those with physical limiting ailments, to ultimately see if we can assist with not only recovery but perhaps prevention" Junyi Zhu, MIT CSAIL Ph.D. student and lead author of the MuscleRehab study, said in a statement.
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Written by Joaquin Victor Tacla
