Scoliosis is a medical condition which occurs in adolescents, where an individual’s spine develops curvature. A Thoracolumbosacral orthosis (TLSO) is a type of brace used to control the lateral curvature of the spine in scoliosis. To successfully monitor the brace treatment, a multi-modal sensor board is attached to the patient’s brace. Our team worked on developing state of the art signal processing and data mining techniques to evaluate the effectiveness of the brace treatment. We have submitted 5 research papers to international conferences related to data mining. Each paper represents a unique analysis to evaluate different aspects of the treatment that are important to the physicians. List of papers submitted are:
- Omid Dehzangi, Omar Iftikhar, Bhavani Anantapur Bache, Jeffrey Wensman, Ying Li submitted”Pervasive Monitoring of Adolescent Idiopathic Scoliosis Brace Treatment using a Context-Aware Sensor Solution”, to the IEEE Journal of Biomedical and Health Informatics.
- Omid Dehzangi, Omar Iftikhar, Bhavani Anantapur Bache, Jeffrey Wensman, Ying Li submitted “Brace treatment Monitoring Solution for Idiopathic Scoliosis Patients”, to 16th IEEE International conference on Machine learning and Applications (ICMLA), Cancun, Mexico, December 2017.
- Omid Dehzangi, Omar Iftikhar, Bhavani Anantapur Bache, Jeffrey Wensman, Ying Li submitted “Force and activity monitoring System for Scoliosis patients wearing back braces”, to The IEEE International conference on consumer electronics (ICCE), Las Vegas, 2018.
- Omid Dehzangi, Bhavani Anantapur Bache, Omar Iftikhar, Jeffrey Wensman, Ying Li submitted “Context-Aware Sensor solution for remote monitoring of adolescent idiopathic scoliosis brace treatment” to 12th International Conference on Body Area Networks, Dalian, People’s republic of China, 2017.
- Omid Dehzangi, Bhavani Anantapur Bache, Omar Iftikhar, Ying Li, Jeffrey Wensman submitted “Context-Aware remote monitoring of brace treatment compliance for adolescent idiopathic scoliosis patients”, to International conference on Data Mining, New Orleans, 2017.