An autonomously controlled ankle exoskeleton for gait rehabilitation. This project addresses a critical problem in gait rehabilitation; predicting unstable locomotion and designing interventions to augment limb-joint function. The project will develop an autonomous ankle-foot assistive device to actively increase ground clearance when high-risk foot trajectory is detected. Using wearable sensor data, machine learning algorithms will predict high-risk gait and compute an actuator-induced ankle to ....An autonomously controlled ankle exoskeleton for gait rehabilitation. This project addresses a critical problem in gait rehabilitation; predicting unstable locomotion and designing interventions to augment limb-joint function. The project will develop an autonomous ankle-foot assistive device to actively increase ground clearance when high-risk foot trajectory is detected. Using wearable sensor data, machine learning algorithms will predict high-risk gait and compute an actuator-induced ankle torque to maintain safe foot-ground clearance. A wearable autonomous joint-actuation system will contribute significantly to rehabilitation across a range of gait-impaired populations. The project's scientific and technological innovations will provide the opportunity for future developments in assistive technologies. Read moreRead less
Predictive Biomechanics for Modelling Gait Stability and Falls Prediction. Efficient, adaptive locomotion is critical to our independence, but it is adversely affected by neuromuscular disorders due to trauma, ageing and other impairments that increase the risk of balance loss and falling. This project investigates the extraordinary possibilities of advancing from the traditional laboratory-based, retrospective, gait research paradigm, to real-world gait monitoring using predictive biomechanics. ....Predictive Biomechanics for Modelling Gait Stability and Falls Prediction. Efficient, adaptive locomotion is critical to our independence, but it is adversely affected by neuromuscular disorders due to trauma, ageing and other impairments that increase the risk of balance loss and falling. This project investigates the extraordinary possibilities of advancing from the traditional laboratory-based, retrospective, gait research paradigm, to real-world gait monitoring using predictive biomechanics. By employing artificial intelligence, wearable sensors' data will predict balance loss and alert the user. The outcome will be fundamental knowledge for developing wearable systems to reduce the catastrophic impact of falls, with public health cost savings and improved quality of life for people with restricted mobility.Read moreRead less