Innovations An integrated system of AI affective computing & multimodal physiological signals in patients with high-risk of cardiovascular disorder
■Technology Introduction

The technology aims to develop an AI-based emotional detections (anger, sadness, happiness, and neutral) and multimodal physiological signals (ECG, EEG, and PPG) integrated system, and apply to patients with cardiovascular disease. Patients monitor their emotional and physical status and administer bio-neuro-feedback to improve their well-being, track disease progression, and prevent adverse prognosis.
 
■Scientific Innovation

 
  1. An improved CNN/RNN architecture was developed to perform the AI online training and inferences for physical and mental monitoring. It was implemented as an AISoC chip with the TSMC-28nm process.
  2. An EEG-ECG-PPG multimodal intelligent computing platform was developed to perform a variety of system functions for emotion recognition. This system combines IoMT concept and network security technologies, integrating into the cloud and terminal environment to build a diverse healthcare field effectively.
  3. A high-performance emotion recognition AI algorithm was developed. The accuracies of our proposed emotion recognition system with ECG-PPG and EEG signals achieved 87.5% and 77.68%, respectively.
 
■This technology won the Futuretech Breakthrough Award in 2019 Future Tech Expo. 


■Institutes
Kaohsiung Medical University, National Chung Cheng University, National Chiao Tung University
I-Mei Li /lin1123@gmail.com

 
An integrated system of AI affective computing & multimodal physiological signals in patients with high-risk of cardiovascular disorder
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