Noncontact heart rate measurement via period detection methods of periodic signals

noncontact heart rate measurement;period detection;signal processing

Tabak, Gizem ; Singer ; Andrew C.

关键词: noncontact heart rate measurement;    period detection;    signal processing;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/95621/TABAK-THESIS-2016.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Conventional heart rate measurement techniques, including manual measurement by placing two fingers on the wrist or side of the neck, electrocardiogram (ECG) or pulse oximetry devices require direct physical contact to the subject and this has the potential to cause inconveniences in cases when the subject has skin irritations or severe burns, contagious disease or intensive care conditions. Hence, there is a need for noncontact heart rate measurement. Previous research on noncontact heart rate measurement utilizes either a complex hardware setup, such as laser illuminators or high-speed cameras, or expensive computational methods, such as independent component analysis. The aim of this work is to apply different signal processing methods utilized in pitch detection problems of periodic signals, namely zero-crossings, autocorrelation, maximum likelihood and Fourier-based methods, to the signal obtained from the average pixel values of the frames of a video recording of the subject’s face obtained using a standard webcam in order to find simple yet effective methods and compare them to previous works, under the same stability assumptions of the subject and illumination of the environment. For this purpose, first, the noncontact heart rate measurement problem is posed as a sinusoidal parameter estimation problem in order to analyze it from a sinusoidal parameter estimation problem point of view. Then, nonparametric methods that are used in period detection of periodic signal problems is presented and their performances are compared with each other as well as previous research. Algorithms are tested on both synthetically generated data and data obtained from input video files. Findings indicate that under stability conditions, inexpensive pitch detection techniques perform almost as well or better compared to computationally expensive methods. Finally, a different approach is taken from the oscillator devices perspective, and an oscillator circuit is used in a similar fashion to an injection locking problem in order to find the period of the input signal from the output of the oscillator circuit. In cases where the circuit parameters such as resistor and capacitor values are tuned accordingly based on the input signal, it is possible to extract heart rate information from the falling edge occurrences of output oscillator voltage with high accuracy.