Differential Enhancement Method for Robust and Accurate Heart Rate Monitoring via Microwave Vital Sign Sensing

• Published in: IEEE transactions on instrumentation and measurement Vol. 69; no. 9; pp. 7108 - 7118
• Main Authors: Xiong, Yuyong, Peng, Zhike, Gu, Changzhan, Li, Songxu, Wang, Dong, Zhang, Wenming
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Differential enhancement (DE); Harmonic analysis; Heart beat; Heart rate; heart rate (HR) variability (HRV); heart rate monitoring; Interference; Mathematical analysis; Microwave filters; microwave radar; Monitoring; Periodic variations; Power harmonic filters; Respiration; respiration harmonic interference; Robustness (mathematics); Telemedicine; vital sign detection
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2020.2978347

Noncontact vital sign detection based on microwave sensing has attracted much interest for its important application potential in many fields, especially in the field of healthcare. However, robust and accurate heart rate (HR) tracking remains a challenge due to the tricky and universal respiration harmonic interference in real scenarios. In this article, a novel method, called differential enhancement (DE), was proposed, which can effectively eliminate the effects of the respiration harmonic interference on HR estimation, including the likely adjacent harmonic interference. The basic idea underlying our proposed method is that the differential operation can significantly enhance the heartbeat components, especially high-order heartbeat harmonics, and it is very useful to locate the true value of HR by combining with the autocorrelation-based periodicity extraction technique. The detailed procedures for performing the DE method were described, which can be simply implemented and have low computational complexity. In addition, a rigorous mathematical analysis was provided for demonstrating the robustness and accuracy of the algorithm. Experimental results with various scenarios validated the performance of the proposed method, and we investigated the HR variability (HRV) monitoring capability of the DE method with a short sliding window length.