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.

(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.

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.