Heartbeat frequency detection algorithm of non-contact vital sign detection system

Abstract

The invention provides a heartbeat frequency detection algorithm of a non-contact vital sign detection system; the steps are: respectively doing bandpass filtering for I and Q two way signals outputted by a continuous wave doppler radar; using a center estimate algorithm to carry out useful dc component recovery; using a complete cluster experience modal decomposition algorithm to separate a heartbeat signal from a human body jitter signal, a breathing signal and environment interference noises; resolving a Hilbert marginal spectrum of each decomposition signal and doing peak value detection; finding out the Hilbert marginal spectrum corresponding to the heartbeat signal according to a marginal spectrum peak position and energy concentration degree close to the spectrum peak; obtaining heartbeat frequency information according to the spectrum peak position. The heartbeat frequency detection algorithm can effectively extract the heartbeat signal under unstable human body and large environment interference noises, thus obtaining accurate heartbeat frequency information, improving anti-interference property of the non-contact vital sign detection system, and satisfying heartbeat frequency detection accuracy demands of medical affairs personnel.

Description

technical field [0001] The invention relates to a signal processing algorithm of a non-contact vital sign detection system based on radar technology, especially a heartbeat frequency detection algorithm. Background technique [0002] Non-contact vital signs detection technology integrates radar technology and biomedical engineering technology, and uses electromagnetic waves to detect vital signs such as human breathing and heartbeat in a non-contact manner. Electromagnetic waves have the characteristics of penetrating non-metallic media, so the non-contact vital signs monitoring system can penetrate clothes and bedding to detect life signals without direct contact with human skin. This advantage makes it suitable for infants, patients with sleep disorders, and adults. It has been applied in the monitoring of vital signs of special groups such as area burn patients and mental patients. In addition, the specially designed biological radar can detect the micro-movement signals...

AI Technical Summary

Problems solved by technology

In addition, since the human body is likely to perform random movements during the monitoring process, such as shaking, turning over, etc., the disturbance signals generated by these random movements are non-stationary, and their frequency is likely to be within the heartbeat frequency range. Therefore, the traditional The filtering method cannot filter out these disturbances, and because the traditional FFT method has low concentration and poor resolution, the FFT frequency measurement method cannot accurately measure the heartbeat frequency

Images