A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction.

ABSTRACT: A current trend in the development of assistive devices for rehabilitation, for example exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality and usability, for example by predicting the patient's upcoming movements using electroencephalography (EEG) or electromyography (EMG). However, these modalities have different temporal properties and classification accuracies, which results in specific advantages and disadvantages. To use physiological data analysis in rehabilitation devices, the processing should be performed in real-time, guarantee close to natural movement onset support, provide high mobility, and should be performed by miniaturized systems that can be embedded into the rehabilitation device. We present a novel Field Programmable Gate Ar

SUBMITTER: Wohrle H 

PROVIDER: S-EPMC5539567 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature