Intelligent Rehabilitation Aid System on Stroke Patients--Subproject I: Development of Biomedical Circuits

With the raise of life pressure in modern society, the number of stroke patients increases year by year. It makes stroke have become the second leading cause of death in Taiwan. Comparing to cardiovascular diseases, stroke usually incurs more serious sequela, because one third of the stroke patients have consequence of disability after stroke attack in their following lives. According to previous medical reports, around 90% stroke patients who accepted traditional rehabilitation have only minor improvements in their mobile capabilities. Daily care of these disabled people costs huge economic burden to both society and families which makes stroke become the most expensive disease. Accordingly, we aim to develop a new intelligent rehabilitation aid system which combines transcranial electric stimulation (tES) and artificial muscle – based assistive device. This proposal includes the main project and the subproject I of the intelligent rehabilitation aid system, in charge of developing tES device, wireless electroencephalography (EEG) system, edge computing of brain computer interface, and sensing circuit for the rehabilitation assistive device. The design of our system will start from two aspects. First, we will evaluate the rehabilitation status of patient’s brain from whole-head EEG using deep learning network, so that the strategy of tES for improving neural activities and plasticity can be confirmed. For the aspect of rehabilitation assistive device, we design deep learning network based brain computer interface (BCI) to detect subject’s movement intentions, and the detected intentions will be used to help patient’s manipulate the HASEL artificial muscle to achieve their limb movements. The research outcome of our intelligent rehabilitation aid system can be used as prototype to design mobile assistive device for disabled patients in the future.