Designing an Automated System using Wearable Devices for Compliance Monitoring and Activity Detection in Scoliosis Patients

Abstract

The use of wearable devices in healthcare and rehabilitation programs is growing exponentially. This thesis focuses on wearable sensors and technology used to monitor treatment compliance in patients with a medical condition known as Adolescent Idiopathic Scoliosis (AIS). Patients with AIS are prescribed to wear a thoracolumbosacral orthosis (TLSO) – a type of back brace, to help prevent worsening of their condition. Scoliosis is a medical condition which occurs in adolescents, where an individual's spine develops curvature. Adolescent Idiopathic Scoliosis (AIS) occurs in children aged 16 years or younger. Brace treatment with TLSO is known as one of the most effective non-surgical treatment for scoliosis. The brace is designed to be worn continuously for long periods of time without any supervision. Therefore, it is vital to carry out the proper procedures for measuring the effectiveness of the treatment, and to accurately evaluate the amount of time of the brace being worn. To successfully monitor compliance with brace treatment, a wearable multi-modal sensor solution is to be embedded into the patient's brace. This thesis proposes an end-to-end system to help improve monitoring brace treatment by continuously observing the amount of force inside the brace. In addition to compliance monitoring, my research is extended to detecting the patient’s daily activities by implementing a novel data-mining method to identify different trends and patterns associated with the activities performed by the patient. This thesis attempts to implement wearables in such an application, and anticipates realizing a successful relationship between monitoring and improving compliance.