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Wearable orthoses can function both as assistive devices, which allow theuser to live independently, and as rehabilitation devices, which allow the userto regain use of an impaired limb. To be fully wearable, such devices must haveintuitive controls, and to improve quality of life, the device should enablethe user to perform Activities of Daily Living. In this context, we explore thefeasibility of using electromyography (EMG) signals to control a wearableexotendon device to enable pick and place tasks. We use an easy to don,commodity forearm EMG band with 8 sensors to create an EMG patternclassification control for an exotendon device. With this control, we are ableto detect a user's intent to open, and can thus enable extension and pick andplace tasks. In experiments with stroke survivors, we explore the accuracy ofthis control in both non-functional and functional tasks. Our results supportthe feasibility of developing wearable devices with intuitive controls whichprovide a functional context for rehabilitation.

EMG Pattern Classification to Control a Hand Orthosis for Functional Grasp Assistance after Stroke