Flagship 5: Augmentation of Upper Arm Stroke Rehabilitation

In this Flagship, the team is working to develop a predictive, subject-specific computational model of the upper limb that can be used to augment existing rehabilitation devices and provide input for other assistive devices to restore hand and arm function in patients who have recently suffered a stroke. Our existing EMG-driven musculoskeletal models (Besier) will be combined with computational neuroscience models (Sagar) to decipher „intention decoding‟ from EMG in healthy and stroke- affected individuals. We will incorporate novel, wearable sensors from our industry partners (Stretchsense and IMeasureU) to develop a closed-loop feedback controller that represents the underlying biomechanics and motor control strategy of the patient. The Flagship will rely upon Platform Technology developments in sensing and remote monitoring, software and modelling.

In particular, the design team is mapping the human experience related to upper-limb stroke rehabilitation. One of our PhD students is investigating how to design a system to facilitate constraint-induced therapy in a home environment. Constraint-induce therapy is highly successful, but rarely applied due to high costs of clinician’s engagement.

Investigators: UoA: Besier, Byblow, Sagar; AUT: Signal; Callaghan Innovation: King. VUW: Rodriguez-Ramirez, Chan, Browne.


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