Signal processing method for health monitoring and signal processing device

Abstract

The invention provides a signal processing method for health monitoring and a signal processing device. The signal processing method comprises the steps: receiving radar wave signals reflected from a target person, so as to obtain vibration phase signals of the target person; filtering respiratory signal harmonics from the vibration phase signals through a moving-target-detection-based filter; and estimating heartbeat frequency of the target person from the phase signals obtained after the respiratory signal harmonics are filtered. The signal processing device comprises a radar signal module and a signal processing module. The radar signal module is configured for receiving the signals reflected from the target person so as to obtain the vibration phase signals of the target person. The signal processing module is configured for filtering the respiratory signal harmonics from the vibration phase signals through the moving-target-detection-based filter, and estimating the heartbeat frequency of the target person from the phase signals obtained after the respiratory signal harmonics are filtered.

Description

technical field [0001] The present application relates to a signal processing method and a device thereof, in particular to a signal processing method and a device thereof based on frequency modulated continuous wave (FMCW) millimeter wave radar. Background technique [0002] As the problem of aging society becomes increasingly prominent, the health problems of empty nesters, especially chronic and sudden diseases such as cardiovascular and cerebrovascular diseases, have received widespread attention. At the same time, with the acceleration of the pace of life, people's life pressure becomes greater, and more people are in a sub-health state. Therefore, how to monitor human health indicators such as breathing and heartbeat in an indoor environment in real time has become an important issue that needs to be considered when paying attention to human health. Most of the existing breathing and heartbeat detection methods are contact detection, which mainly use wearable sensors ...

AI Technical Summary

Problems solved by technology

Most of the existing breathing and heartbeat detection methods are contact detection, which mainly use wearable sensors or sticky electrodes to directly contact the human body for detection. The detection process will cause psychological or physiological constraints to the tester, and cannot accurately and truly reflect the physiological state of the tester. Changes

And contact detection has certain application limitations, such as when skin damage or other conditions that do not allow contact measurement

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