Abstract
Purpose: Validate and test a method for automatic detection of painful electrical stimulation using computer vision techniques. Context: In rehabilitation of stroke patients with motor deficits, functional electrical stimulation (FES) of muscles and nerves is a method used for activating the muscles and assisting body movements [1]. The stimulation can be painful, e.g. if the intensity is too high, electrode positioning is wrong or if the electrode/skin contact becomes poor. This is not desirable as it, most likely, discourages the patient to continue using the system. Therefore, a tele-rehabilitation FES system should incorporate methods for automatic detection of painful stimulation and ask the patient to reassess electrode contact and/or positioning upon detection.
Highlights
Validate and test a method for automatic detection of painful electrical stimulation using computer vision techniques
Context: In rehabilitation of stroke patients with motor deficits, functional electrical stimulation (FES) of muscles and nerves is a method used for activating the muscles and assisting body movements [1]
For automatic detection of the pain level, we applied the algorithm of [2], which is based on energy released by facial expressions
Summary
Validate and test a method for automatic detection of painful electrical stimulation using computer vision techniques. Integrative Neuroscience group, SMI, Aalborg University, Denmark Visual Analysis of People Laboratory, Aalborg University, Denmark Purpose: Validate and test a method for automatic detection of painful electrical stimulation using computer vision techniques.
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