| Vital signs such as breathing and heartbeat can indicate the health status ofthe human body, which provide important proof for disease diagnosis andprevention in clinic. There are two methods to detect the heartbeat andrespiration signals. The first one named contact method, which needs theelectrode or sensor touching the human body, which restricts the humansubject in some unconventional conditions such as burns or infections, etc.Another method named non-contact method, which can be used to detect thevital signs without any electrodes or sensors touching the body surface of humansubject. The commonly used non-contact detection method, such as infrared andlaser, could be affected by temperature and environmental obstacles, thus theirapplications were limited. The radar vital signs monitor (RVSM) emittedelectromagnetic waves to the human body, the received echo signals wereprocessed to extract the breathing and the heartbeat signals. This technology candetect the vital signs of human subjects without touching the body from adistance, the electromagnetic wave also can penetrating obstacles. With thedevelopment of radar and microelectronic technology, the technology of RVSMwas paid more attention all over the world.Nowadays, RVSM is mainly used to detect respiration and heartbeatsignals, but there are some technical problems as below: Firstly, it is very difficult to improve the acquisition system stability andanti-interferences capability according to the characteristics of heartbeat andother vital signs, they are very tiny, low frequency, non-stationary andsusceptible to interference. And what’s more, the background noise of the radarsystem will affect the quality of the echo signal of radar systems.Secondly, it is very difficult to separate the heartbeat signal from the radarechoes because the amplitude of the minute movement of chest caused bybreathing activity is much larger than that caused by the heartbeat, and thespectrum of the harmonic components of the respiratory signal is overlappedwith that of the heartbeat.According to these problems mentioned above, this paper focus on theseparation of respiration and heartbeat signals based on our group’s early studies.The study mainly involves as follows:1）Analysised the physiological characteristics of the respiration/heartbeatand studied the correspondence between respiration, heartbeat and micro-surfacethorax.2）Based on the characteristics of the breathing and heartbeat, as well as theprinciple of adaptive cancellation algorithm, this study proposed an offsetalgorithm based on LMS adaptive harmonic signal model. By using Matlabalgorithm, the heartbeat signal is separated from the body movement signal, theoutput results suggest that the simulation results were quite well.3）Designed and completed some related experiments, established thesynchronous contact detection experiment system of ECG, also verified thefeasibility of the algorithm. The experiments include: the first experiment,simulated clinical monitoring lying down experiments; the second experiment,simulated household monitoring sitting experiments (divided into two modes of take a deep breath and breathe freely). Dynamic signal of breathing and bodymoving were collected under different experimental conditions, the output of theadaptive harmonic cancellation algorithm and the synchronous detecting ECGsignal were compared and analyzed, the results suggest that there is a strongcorrelation between both frequencies, suggests that the heartbeat can beisolated by using this algorithm.The innovation of this subject:1）An analysis of the corresponding relationship between breathing/heartbeat signal and body surface thoracic micro, clarified the basis of thephysiology of breathing and heartbeat signals of radar detection.2）An LMS adaptive harmonic cancellation algorithm, which was based onLMS adaptive harmonic, and harmonic combination of the breathing signal wasproposed. The improved algorithm has a good effect on the separation ofrespiration and heartbeat signals. |
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