Multimodal Gait Training and Evaluation with Smartphone

Gait training is pivotal in accessing the degree of recovery in walking ability of patients after treatment. Potential gait issues must be detected early in order to prevent falls while walking. In order to enable convenient and continuous gait training, we propose a solution called Gaitroid using multimodal sensors and smartphone to enable self-guided training via adaptive audio feedback and automated gait assessment using sensors to recognize important gait phases and clinical parameters. Initial experiments on evaluating gait phases detection and abnormality recognition with healthy subjects achieved average accuracy of about 90%. With the help of Gaitroid, users can continue gait training conveniently at home while allowing therapists evaluate gait performance and manage personalized therapy remotely, thus shortening the recovery time.