Design of FPGA-Based Rehabilitation Effect Assessment Headband

Stroke is an emergency cerebrovascular event, resulting in damage to cranial nerves, and the subsequent rehabilitation is necessary to restore neurological function and improve patient outcomes. In clinical settings, the rehabilitation effectiveness is assessed subjectively by experienced physicians or through the use of performance assessment scales. Although several techniques, such as electroencephalography (EEG), cardiopulmonary exercise testing (CPET), and functional magnetic resonance imaging (fMRI), may also be utilized in the evaluation of rehabilitation effectiveness, they require higher costs and the expertise of professional medical staff for experienced operation and post-analysis. Based on the technique of near-infrared spectroscopy (NIRS), a field programmable gate array (FPGA)-based rehabilitation effect assessment headband was proposed. The designed headband could monitor the change in cerebral blood flow non-invasively and continuously under exercise. From the changes in cerebral blood flow, eight perfusion indexes were also extracted in real time and utilized to assess the cardiopulmonary function status of middle-aged and older adults before and after rehabilitation. The analysis algorithm would be completed in the wireless and wearable headband to greatly improve the convenience of use. The experimental results showed that the cardiopulmonary function status could be effectively classified from defined perfusion indexes, and the differences between defined perfusion indexes and the neural network output before and after rehabilitation were also significant.