Osteoarthritis is one of the most prevalent joint disease in people above 65 years of age. This disease primarily effects the joint, while eroding the surrounding bone and cartilage. It is one of the most common musculo-skeletal diseases in the world and will impact over half of all people at some point in their lives. Specifically, knee osteoarthritis outnumbers all other mobility-related disabilities in people

The only treatment so far, discovered for this disease is comprising of intensive physical muscle strengthening exercises, of which no solid track can be maintained. But now scientists have engineered a wearable sensor that can predict how patients with osteoarthritis might show improvement with physical therapy.

A group of adults with osteoarthritis were a part of study taken place at University of Calgary. The study comprised of data collected from wearable sensors attached to a patient’s back, thigh, shank, or foot, which predicted physiotherapy outcomes. To compare improvement before and after physiotherapy, researchers had the participants fill out a Knee injury and Osteoarthritis Outcome Score (KOOS) – a standardized self-administered questionnaire to quantify symptoms such as pain and their ability to function in daily life.

The group was then advised to complete a six week hip strengthening exercise that was focused upon hip specifically. The exercise was conducted under the supervision of Board Certified Athletic therapist who also monitored patient pain and exercise frequency.

The results were later on analyzed and the following conclusion was drawn: the most accurate test required data from the back, thigh, and shank sensors, with 81.7% accuracy. Back and thigh only were statistically just as good, with 80.0% accuracy. Out of all the sensor placements, the thigh was the most predictive of improvement, at 74.4% accuracy, while the back was the worst, with only 66.7% accuracy.

The team thinks that more data collected from wearable sensors can help more in diagnostic purposes. Furthermore, by predicting the outcome of treatment, the patients can be offered better health care, optimized treatment modalities and faster improvement in prognosis.