Wearable Technologies

Wearable sensors for gait assessment in lower extremity disability population.

Patients impaired with neuro-musculoskeletal disorders such as cerebral palsy, stroke and Parkinson disease dramatically impact quality of life. The clinical needs of patients with gait disorders are typically addressed through rehabilitation. During the treatment process, a therapist evaluates and iteratively prescribes rehabilitation based on general guidelines and clinical judgement. Current clinical practice lacks patient-specific prescriptions based on quantitative measures, so outcomes are often suboptimal. We propose a novel approach to address the limitations of current ‘best practice’ rehabilitation for gait disorders by exploiting recent advances in the field of wearable sensors, computational modelling and machine learning. This innovative, miniature, wireless and low-cost IMU-based system provides a portable, quantitative and precise approach to assess 3 dimensional gait analysis. In addition to providing accurate and timely information about movement strategy, our system can be used outside the clinic, producing relevant information for assessment and intervention. Enabling home-based monitoring and rehabilitation can improve patient compliance and present the patient with critical feedback on their progress.

Julie Choisne
Thor Besier
Justin Fernandez
Ted Yeung

• NSC Science for Technological Innovation
• The Robertson foundation (Aotearoa fellowship)