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A feature extraction method of vital signals based on line spectrum tracking
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A life signal and feature extraction technology, applied in the field of signal processing, can solve problems such as secondary damage to electrodes or sensors, restricted applications, and discomfort of monitored objects
Active Publication Date: 2022-02-11
SOUTHEAST UNIV
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[0003] Most of the above methods are based on contact, and need to be in contact with human skin to measure vital sign parameters, which limits their application in some special occasions
For example, in the monitoring of the elderly, wearing equipment for a long time will cause discomfort to the monitoring object; for patients with extensive burns, electrodes or sensors may cause secondary damage; in the search and rescue process after some disasters, through contact It is obviously impractical to detect vital signs by means of a method, so the development of non-contact vital signal feature extraction technology has very important value
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Embodiment 1
[0116] like figure 1 As shown, the present invention discloses a vital signal feature extraction method based on line spectrum tracking. The vital signal in the present invention is a respiratory signal and a heartbeat signal, and the frequency of the respiratory signal and the heartbeat signal is extracted. The method comprises the steps of:
[0117] Step 1. Model the thorax movement caused by the target's life signal, and obtain the distance between the target and the radar as:
[0118] R(t)=R 0 -a(t)
[0119] Among them, R 0 is the initial distance of the target, a(t) is the model of the thorax movement caused by the vital signal;
[0120] In this embodiment, the model of thorax movement caused by vital signals is:
[0121]
[0122] Among them, R ai Indicates the magnitude of the i-th harmonic of the respiratory waveform, f r Indicate the respiratory rate, which is 20 times / minute in the present embodiment, and the magnitude of change is 2 times, that is, 20 ± 2 t...
Embodiment 2
[0203] In order to check the anti-interference performance of the present invention, on the basis of embodiment 1, the simulation to human body shaking is added, and the specific steps are as follows:
[0204] Assuming that the shaking signal of the human body is a triangle wave, the expression is as follows:
[0205]
[0206] Wherein n represents the number of time units with body shaking, and the present embodiment takes 20% of the total time units, and each time unit is 4s; T 1 ,...,T n Respectively, the duration of each unit is set to 4s in this example; A 1 ,...,A n They are the maximum jitter amplitude of each unit, in this example, it is set to a random value between [0 10]mm, the jitter signal is as follows Figure 6 shown.
[0207] At this time, the model of the thorax movement caused by the vital signal is:
[0208]
[0209] The distance between the target and the radar is:
[0210]
[0211] The line spectrum tracking results obtained after processing ...
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Abstract
The invention discloses a life signal feature extraction method based on line spectrum tracking, which includes: modeling the chest cavity movement of the target; continuously transmitting N frequency modulation signals by the radar, mixing the echo signals to obtain the IF signal and obtaining the target phase, forming A phase vector Φ with a length of N; perform STFT on Φ to obtain a time-spectrum matrix P s ; Construct the first HMM model Γ 1 ; put P s Divided into Q groups, each group of data is used as an observation sequence, and the Viterbi algorithm is used to calculate Γ 1 The optimal state sequence corresponding to the observation sequence can be used to obtain the frequency unit of the respiratory frequency at each moment; the P s The elements of multiple harmonic components corresponding to the respiratory frequency are set to zero, and the second time-spectrum matrix P' is obtained s , construct the second HMM model Γ 2 ; put P' s Divided into Q groups, each group of data is used as an observation sequence, and the Viterbi algorithm is used to calculate Γ 2 The optimal state sequence corresponding to the observation sequence is obtained to obtain the frequency unit of the heartbeat frequency at each moment. This method can accurately extract the breathing and heart rate of the target without contact.
Description
technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a feature extraction method of vital signals. Background technique [0002] Respiration and heartbeat are important indicators of vital sign information. On the one hand, cardiopulmonary sign information can be used to judge whether there is a living body, and the basic state of the living body; on the other hand, abnormal cardiopulmonary activity parameters are often accompanied by medical emergencies. Therefore, real-time monitoring of cardiopulmonary signs has very important practical value in many occasions. Among the common vital sign signal detection methods, the methods used for human respiration detection mainly include: pressure sensor method, temperature sensor method, electrical impedance respiration measurement method, respiratory induction plethysmography method; detection methods related to heartbeat include: electrocardiogram, Heart sound, p...
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