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

Institute of Electronics     2019/09/24
An integrated system of AI affective computing and multimodal physiological signals in patients with high-risk of cardiovascular disorder
  • INDUSTRY, INNOVATION, AND INFRASTRUCTURE
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  • An integrated system of AI affective computing and multimodal physiological signals in patients with high-risk of cardiovascular disorder

R&D UNIT

Kaohsiung Medical University / Professor I-Mei Lin

National Chung Cheng University / Professor Wai-Chi Fang

National Chiao Tung University / Professor Sung-Nien Yu

 

Technical  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 Breakthrough

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.

 

Industrial Application

(1)The AI-based integrated system uses AI-algorithm on affective computing for bio-neuro-feedback intervention. The technology  moves  forward  from  hospital  to  home-based  self-monitoring  on  mental  and  physical  health  and  has profound potential for the home care and medical industry. (2) With this technology, we would cooperate with MedKing company to develop a validated AISOC chip  and multimodal affective computing platform. The product combines IoMT and network security technologies to meet the commercial demands of high-security home-based healthcares and clinical psychotherapy.