Development and Evaluation of an Internet of Things Based Wearable Sensor System for Real-Time Monitoring and Remote Management of Musculoskeletal Rehabilitation Patients

Abstract

Musculoskeletal rehabilitation needs people to keep track of how patients are moving after they leave the clinic. The usual way of following up with patients after they leave the clinic has some problems. Patients can only visit the clinic often they have to tell us how they are feeling and some patients live really far from the clinic. This paper looks at twenty-one studies that were published between 2019 and 2025. These studies are about using Internet of Things based sensor systems to monitor musculoskeletal rehabilitation patients in real time. The patients in these studies were recovering from things like knee arthroplasty, post-stroke upper-limb impairment and hip and knee osteoarthritis. The systems that were studied have three parts: sensing, edge or network and cloud or application layers. The paper examines how these systems operate, such as how they detect movement, how they communicate with one another and how they interpret data. The paper also examines the tracking capabilities of these systems – such as movement, muscle activity, patient feelings and how they communicate this information to doctors. The paper compares these systems and discovers that some systems are more adept at tracking leg motion, and others, arm motion. Systems with inertial measurement units, for instance, are able to follow leg motion, while systems with surface electromyography and accelerometers are able to follow arm motion in stroke patients. In one study, they looked at many studies and found that patients who used remote monitoring systems were less likely to require rehospitalization, and they were not in the hospital as long. They were also not required to come into the clinic frequently, and were more likely to adhere to their treatment plan. In a few small studies, which used an inertial platform to track the patients after knee replacement surgery, it was determined that these devices were effective and there was no loss of accuracy if utilized within the home environment. The ability to interact with other computers, and learn from the result of the data collected, is the key to making these systems effective, it concludes the paper. The biggest problems that are still preventing these systems from being widely used are that they do not work well with systems they are not secure and there are problems, with how they will be paid for through 2025. Although the rehabilitation of musculoskeletal and the Internet of Things based sensor systems are improving, they still have some challenges to be addressed. In the future, the Internet of Things (IoT) sensor systems will continue to be employed in musculoskeletal rehabilitation.