Assistive devices, like exoskeletons or orthoses, often make use of physiological data that allow the detection or prediction\r\nof movement onset. Movement onset can be detected at the executing site, the skeletal muscles, as by means of\r\nelectromyography. Movement intention can be detected by the analysis of brain activity, recorded by, e.g.,\r\nelectroencephalography, or in the behavior of the subject by, e.g., eye movement analysis. These different approaches\r\ncan be used depending on the kind of neuromuscular disorder, state of therapy or assistive device. In this work we\r\nconducted experiments with healthy subjects while performing self-initiated and self-paced arm movements. While other\r\nstudies showed that multimodal signal analysis can improve the performance of predictions, we show that a sensible\r\ncombination of electroencephalographic and electromyographic data can potentially improve the adaptability of assistive\r\ntechnical devices with respect to the individual demands of, e.g., early and late stages in rehabilitation therapy. In earlier\r\nstages for patients with weak muscle or motor related brain activity it is important to achieve high positive detection rates\r\nto support self-initiated movements. To detect most movement intentions from electroencephalographic or\r\nelectromyographic data motivates a patient and can enhance her/his progress in rehabilitation. In a later stage for\r\npatients with stronger muscle or brain activity, reliable movement prediction is more important to encourage patients to\r\nbehave more accurately and to invest more effort in the task. Further, the false detection rate needs to be reduced. We\r\npropose that both types of physiological data can be used in an and combination, where both signals must be detected to\r\ndrive a movement. By this approach the behavior of the patient during later therapy can be controlled better and false\r\npositive detections, which can be very annoying for patients who are further advanced in rehabilitation, can be avoided.
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