Technical Name An integrated system of AI affective computingmultimodal physiological signal in patients with high-risk of cardiovascular disorder.
Project Operator Kaohsiung Medical University
Project Host 方偉騏、余松年、林宜美
Summary The technology aims to develop an AI-based integrated system for emotional detections (anger, sadness, happiness,neutral)multimodal physiological signals (ECG, EEG,PPG),apply to patients with cardiovascular disease. Patients monitor their emotionalphysical statusadminister bio-neuro-feedback to improve their well-being, track disease progression,prevent adverse prognosis.
Scientific Breakthrough (1)Adding Baseline NormalizationCNN accelerated chip to recognize different emotions between subjects. (2) Using 8 electrocardiography channels of frontaltemporal to choose feature selection method with a small operation load which is suitable for a real hardware system. (3) Combined with 28 nm prospective cell-based processes to produce fast, low power consumptionsmall deep learning arithmetic unit.
Industrial Applicability The AI-based integrated system uses AI-algorithm, Bluetooth transmission,data analysis on affective computing, multimodal physiological signal measuring,bio-neuro-feedback intervention for patients with cardiovascular disease. The technology moves forward from hospital to home-based self-monitoring on mentalphysical health, shorten the medical process, improve treatment effectiveness, reduced medicalsocial costs.
Keyword Cardiovascular disease emotion recognition biofeedbcak electroencephalography electrocardiography photoplethysmography multiple physiological signals artificial intelligence affective computing CNN model
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