Abstract

Purpose This paper aims to design a vision-based non-contact real-time accurate heart rate (HR) measurement framework for home nursing assistant. Design/methodology/approach The study applied Second-Order Blind Signal Identification (SOBI) algorithm to extract remote HR signal and analyzed it with Fast Fourier Transform (FFT). Multiple regions of interest are chosen and analyzed to obtain a more accurate result. Findings An accurate non-contact hear rate (HR) measurement framework is proposed and proved to be efficient. Originality/value The contributions of this HR measurement framework are as follows: accurate measurement of HR, real-time performance, robust under various scenes such as conversation, lightweight computation which is suitable and necessary for home nursing assistance. This framework is designed to be flexibly used in various real-life scenes such as domestic health assistance and affectively intelligent agents and is proved to be robust under such scenes.

Highlights

  • Heart rate (HR) is an important physiological index reflecting both health condition and emotional state

  • In conclusion, a non-contact real-time framework designed for home nursing assistant robots is proposed and validated to be efficient

  • The framework can detect human HR from a distance under various circumstances including during daily conversation and is robust even with body swing and head motions allowing the users to be at ease

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Summary

Introduction

Heart rate (HR) is an important physiological index reflecting both health condition and emotional state. Activities like physical exercise, sleep, illness and emotional swings like anxiety, stress and excitement can result in HR changes. Monitoring HR can obviously play an important role in keeping track of the health condition of the elderly. When it comes to home nursing assistant robots, this monitoring process requires accuracy and user-friendliness, which means causing as less disturbance as possible. Under such circumstances, vision-based non-contact methods are preferred to other measurement methods

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