Abstract
Electrical stimulation electrode arrays are an emerging technology that enables muscles to be artificially contracted through the activation of their associated motor neurons. A principal application of electrical stimulation is to assist human motion for orthotic or therapeutic purposes. This paper develops a framework for the design of model-based electrode array feedback controllers that balance joint angle tracking performance with the degree of disturbance and modeling mismatch that can exist in the true underlying biomechanical system. This framework is used to develop a simplified control design procedure that is suitable for application in a clinical setting. Experimental results evaluate the feasibility of the control design approach through tests on ten participants using both fabric and polycarbonate electrode arrays.
Highlights
There is a pressing need for novel technologies to support recovery of arm function following neurological conditions such as stroke and multiple sclerosis
This paper has developed a robust control design framework for electrode array based stimulation
Robust performance bounds were derived which allowed performance and robustness to be balanced in a transparent, principled manner, giving rise to a pragmatic control design procedure
Summary
There is a pressing need for novel technologies to support recovery of arm function following neurological conditions such as stroke and multiple sclerosis. These devices help support the affected limb using various training modalities, and help reduce muscle fatigue or provide functionality that ES cannot (e.g. to assist with forearm supination or help stabilize the scapula). The recent emergence of transcutaneous electrode arrays has potential to improve selectivity, automate placement, and reduce fatigue and discomfort compared with single pad ES electrodes [7,8] The freedom they embed to adjust the size and shape of the electrode means they can isolate smaller muscle groups, and thereby enable the user to perform a variety of functional tasks including walking [9,10], and hand/wrist motion [8,11]
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