Research and Development on Algorithms for Evaluating Mental Wellness Using Heart Rate Variability Measured by Wearable Devices

Professor Wong, Kenneth Kwan Yee   (Project Coordinator (PC))

Miss Abbasi Kendy   (Co-Investigator)

Mr Lau Ho Yuen   (Co-Investigator)

Dr Choi Yi King   (Co-Investigator)

12

2020-02-26

2021-02-28

267641

Research and Development on Algorithms for Evaluating Mental Wellness Using Heart Rate Variability Measured by Wearable Devices

Algorithms, Development, Heart Rate Variability, Mental Wellness, Research, Wearable Devices

Others - Computing Science and Information Technology

Engineering (E)

InP/049/20

Innovation and Technology Fund Internship Programme

2020

Completed

This project aims to study and develop algorithms for evaluating mental wellness of people using heart rate variability (HRV) measured by wearable devices, and to optimize such algorithms for integration with mobile application or firmware of wearable devices. HRV is a measurement of the continuous interplay between sympathetic and parasympathetic influences on heart rate that yields information about autonomic flexibility and thereby represents the capacity for regulating emotional responses. In this project, HRV data of recruited participants will be collected under conditions of designed activities to represent various mental states. Methodology of digital signal processing, digital filtering and machine learning will be applied to develop algorithms that are integrable to the firmware of a wearable. Our goal is to determine the mental state of a person based on HRV metrics under different scenarios. Categorization accuracy (CA) will be used as a metric for quantitative comparison of performance in evaluating the developed algorithms. Empowered by the developed algorithms, we will produce the world's first wearable with a convenient form factor that is able to distinguish mental stress, physical stress and recovery states of persons without any intervention to their daily life.