Abstract
Ankle sprains are among the most common musculoskeletal ailments treated. In the general population, almost 2.15 per 1000 persons will experience some form of ankle joint sprain or injury annually. Although the patients go on to heal without long term consequences in many cases, some may develop chronic ankle instability which is a debilitating condition incorporating recurrent sprains, persistent pain and repeated instances of giving way. Wearable ankle braces or assistive devices are designed to support the injured joint and help the user get back to the normal life style while the joint is healing and recovering its normal function. Although such devices have been shown to be useful, they will bring a lot of other limitations to user's lifestyle by preventing them to pursue occupational or normal day activities due to joint impairment. Lengthy recovery time due to lack of joint's natural activity is an example of such limitations. In this paper, we not only discuss the current status of our new dynamic wearable smart brace, but we also present the features implemented in the mobile application, including 3D modeling for brace-human interaction and machine learning algorithms for stability control. The design of the wearable smart brace uses Micro-Electro-Mechanical Systems (MEMS) to interact with the mobile application and the MEMS is a printed circuit board (PCB) with sensors.
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