應用於居家照護之智慧型互動平台-應用於醫療場域及居家照護之智慧型互動平台-以人工智慧為核心之腦波人機介面開發(4/4)

This project aims to develop artificial intelligence (AI) – basedElectroencephalography (EEG) recognition technology. The AI-based braincomputer interface (BCI) developments are constructed based on thesubstantial research capabilities of Department of ElectricalEngineering, National Central University, from EEG, medical electronics,to biomarkers. With the help of AI, the proposed BCI system willaccurately detect user’s intention or mental status and then applybiofeedback to enhance user’s specific brain function. In this project,three application fields are proposed, including medical care, homecareand scientific education. For medical care aspect, we will designclosed-loop BCI for rehabilitation treatments in stroke and cognitiveimpairment patients. By detecting patients’ brain statuses using AI,transcranial electric stimulation (tES) will be utilized as biofeedbackto restore patient’s brain functions. In homecare aspect, we willdesign AI-based BCI for sever paralyzed patients to communicate withexternal environments using EEG signals recorded from motor cortex. Inaddition, vital signs will be also detected to manage patient’sphysiological status. In the third part, a real-time BCI withbiofeedback system in education environments will be developed.Students’ cognitive loads and emotional statues will be detected usingdeep learning networks. The mental statues will be feedback to teacheras reference information so that teachers are able to handle students’classroom performance. With the provision of student’s mentalinformation, teachers can modify their teaching strategy in classroomenvironment to achieve better teaching performances. The researchoutcomes of this project will also establish database for strokepatients, cognitive impairment patients, imagery motor EEG databases,and database for student’s cognitive and emotional statuses inclassroom environment. For industrial benefits, the establishedtechnologies and databases of our AI-based BCIs can be applied toindustry of medical care for stroke and cognitive impairment patients,industry of homecare for BCI rehabilitation system and healthcare, andindustry of education for achieving better learning performance instudents. With accurate detection of user’s intention mental statuses,novel applications using AI-based BCI will be established.