以AI為基礎的情緒辨識與生理訊號整合平台應用在心血管疾病

2019 -10 -01

The technology aims to develop an integrated system of artificial intelligence affective computing and multimodal physiological signals detection in order to detect the emotional and physiological responses of high-risk patients with cardiovascular disease. To achieve personal mental and physical health status, and to track and prevent disease, by monitoring emotional and physiological responses and carrying out bio-neuro-feedback modules. This study develops an integrated system of artificial intelligence affective computing (included anger, sadness, happiness, and neutral emotion) and multimodal physiological signals detection included electrocardiography (ECG), photoplethysmography (PPG), electroencephalography (EEG). This study optimizes emotional and physiological parameters for bio-neuro-feedback treatment modules by algorithm of mechanism learning and deep learning. This system combines cutting-edge technologies, including wearable device, smartphone, blue-tooth, artificial intelligent emotion recognition, and genetic algorithm, which combines with a guided breathing biofeedback training program. Therefore, constructing an individualized, mobile, high efficient and real-time smartphone-based bio-neuro-feedback training system for personal health management and home-based training.

本技術獲選為2019未來科技展「未來科技突破獎」，了解更多：

心血管疾病高風險病人在人工智慧情緒偵測與多模態健康生理訊號整合系統之反應暨居家生理回饋治療模組之發展