An AI-based ambulatory ankle brace with wearable sensor used for preventing ankle sprains

Abstract

Ankle sprain is one of the most common injuries in the game of basketball. The ankle sprain may bring tremendous time and cost loss, and patients with a history of ankle sprain are susceptible to further ankle injuries. This paper proposes an AI-based ambulatory ankle brace with wearable sensors that can be used for ankle-sprain prevention. The equipment consists a sensor, a microcomputer, a Bluetooth module, and a muscle stimulator. Ten volunteers performed twelve basketball moves with the ankle brace on, and the twelve basketball moves were labeled as high-risk and low-risk. The sensor on the ankle brace measured the 3-dimensional angular velocity and angular displacement of the subjects ankle in real-time, and the data were then fed to different machine learning algorithms to create models to predict future ankle motions. The model with the best performance created by the Random Forest algorithm was imported into the microcomputer. Once the model predicts a high-risk move, the microcomputer sends a Bluetooth signal to the muscle stimulator. The one end of the stimulator is a pair of electrodes attached to the peroneal muscles to restrict ankle motion. When the stimulator receives the high-risk signal, its activated and the spraining motion would be alleviated. In this way, the ankle brace doesnt restrict normal ankle movement while providing adequate protection for potential ankle sprain cases.