CN112617786A - Heart rate detection device and method based on tof camera - Google Patents
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
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Abstract
The invention relates to the technical field of health monitoring, in order to realize heartbeat signal detection and reduce the cost of a detection device, the heart rate detection device based on a tof camera comprises: the heart rate detection method based on the tof camera comprises the following steps: 1. acquiring human body information to be detected and acquiring distance change data generated by human body distance according to the human body information, wherein the distance change data form an original signal; 2. separating and reconstructing heartbeat signals according to the original signals by adopting a wavelet transform method to determine the heartbeat value of the human body; 3. the heartbeat value is compared with a preset comparison value. By adopting the structure, non-contact detection can be realized, and the cost of the detection device is reduced.
Description
Technical Field
The invention relates to the technical field of health monitoring, in particular to a heart rate detection device and method based on a tof camera.
Background
Monitoring of physiological parameters of the human body is commonly required in homes, hospitals, nourishing homes and the like. Most of the currently adopted monitoring devices are suitable for measuring electrodes, are directly contacted with the skin, measure physiological parameters such as electrocardio, blood pressure and the like, and directly display the parameters on a screen. In this way, the electrodes and wiring lead to inconvenience to the subject, particularly in the long-term monitoring of chronically ill patients and elderly, where it is often not feasible, or desirable, to place the electrodes on the patient, particularly for neonates or burn patients.
In the related art, there are two non-contact monitoring methods without electrodes, one is to use a pressure sensor to detect minute motion signals caused by respiration and heartbeat, and further analyze the respiration and heartbeat signals. However, the pressure change caused by respiration and heartbeat is small, the sensitivity of the pressure sensor is limited, and the heart rate detection precision of the detection method is low so far and cannot reach the clinical application level.
The second uses doppler radar or ultra wideband radar to measure the respiration and heartbeat induced chest fluctuations and separate the respiration, heartbeat and motion from the fluctuation signal. The radar generates and transmits a detection signal, receives an echo signal with human body physiological information reflected by a target, and analyzes and extracts the physiological information of the detection target from the echo signal. At present, the radar has a high price and is not easy to popularize.
Disclosure of Invention
The invention provides a heart rate detection device and method based on a tof camera, aiming at realizing detection of heart rate signals of a human body and reducing the cost of a heart rate signal acquisition device.
The technical scheme adopted by the invention for solving the problems is as follows:
heart rate detection device based on tof camera includes:
the signal acquisition module is used for acquiring human body information to be detected and acquiring distance change data generated by human body distance according to the human body information, wherein the distance change data form an original signal;
the signal processing module is used for separating and reconstructing heartbeat signals according to the original signals by adopting a wavelet transform method so as to determine the heartbeat value of the human body;
and the index reminding module is used for displaying a comparison result of the heartbeat value and a preset comparison value and giving an alarm according to the comparison result.
Further, the signal acquisition module comprises at least one tof camera.
Further, the index reminding module comprises a display screen and a loudspeaker.
Further, the signal processing module includes:
a signal processing unit: the system is used for acquiring a curve of the human body distance along with time change according to an original signal;
sign signal detection unit: and decomposing the curve by adopting a wavelet transform method to separate the heartbeat signal.
A heart rate detection method based on a tof camera comprises the following steps:
step 2, separating and reconstructing heartbeat signals according to the original signals by adopting a wavelet transform method to determine the heartbeat value of the human body;
and 3, comparing the heartbeat value with a preset comparison value.
Further, the step 1 comprises:
step 11, carrying out data processing on the acquired target information by taking a frame as a unit to acquire a distance sequence;
and step 12, obtaining the distance sequence change data generated by the multi-frame target information to form an original signal.
Further, the step 2 comprises:
step 21, according to
Carrying out signal decomposition;
step 22, according to
Carrying out signal reconstruction;
step 23, obtaining a heartbeat value according to the reconstructed signal period;
wherein the content of the first and second substances,
for the scale function, ψ (t) is a wavelet function, h (k) and g (k) respectively represent a low-pass filter and a high-pass filter in the decomposition process, Φ (t) represents the process of signal decomposition, the inverse can be used for signal reconstruction, l represents the number of layers of decomposition, k is a translation variable, and t is time.
Further, during the decomposition, the original signal is subjected to 6-layer decomposition, and the 6 th node to the 12 th node of the sixth layer are selected to be reconstructed to obtain a heart rate signal HR (t).
Further, between step 22 and step 23, the method further includes: step 221, optimizing the reconstructed heartbeat signal, including:
step 2211, shifting the obtained heart rate signal HR (t) along the time axis by an interval td to obtain a translated heart rate signal HR (t + td);
step 2212, calculating autocorrelation coefficients of the heart rate waveforms before and after translation by using an autocorrelation algorithm:
wherein σ2Representing a normalization factor, mu is an overall mean value, and E is an expected value;
step 2213, obtaining a plurality of autocorrelation coefficients by adjusting the translation time interval td until the time interval covers the whole time axis;
step 2214, obtaining the heart rate cycle according to the autocorrelation coefficient and solving the heart beat value: the signal shift interval coincides with the heart rate cycle when the autocorrelation coefficient is maximum.
Compared with the prior art, the invention has the beneficial effects that: this application uses the tof high accuracy camera to measure and is surveyed person's chest motion, obtains the heartbeat signal of being surveyed person through handling and analysis to chest motion signal, realizes contactless detection. The application provides a rhythm of heart detection device of tof camera is complete noiseless, the random portable quick rhythm of heart detection device of locating position, and application scope is wide, and is with low costs.
Drawings
FIG. 1 is a view showing the structure of a detecting unit according to the present invention;
FIG. 2 is a graph of distance waveform data;
fig. 3 is a schematic diagram of separating heartbeat signals by a wavelet transform method.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, the heart rate detection device based on the tof camera comprises:
the signal acquisition module is used for acquiring human body information to be detected and acquiring distance change data generated by human body distance according to the human body information, wherein the distance change data form an original signal;
the signal processing module is used for separating and reconstructing heartbeat signals according to the original signals by adopting a wavelet transform method so as to determine the heartbeat value of the human body;
and the index reminding module is used for displaying a comparison result of the heartbeat value and a preset comparison value and giving an alarm according to the comparison result.
Specifically, the signal acquisition module includes at least one tof camera, and in order to make the testing result more accurate, can adopt the tof camera array that a plurality of tof cameras are constituteed to carry out information acquisition. The index reminding module comprises a display screen and a loudspeaker, the display screen can display the detection result in real time and can also display other information related to the detection result, so that the related conditions of the detected person can be known at any time; the loudspeaker can give an alarm according to the comparison result of the heartbeat value and the preset comparison value, so that the heartbeat is prompted to be abnormal, and emergency measures can be taken conveniently.
Preferably, the signal processing module includes:
a signal processing unit: the system is used for acquiring a curve of the human body distance along with time change according to an original signal;
sign signal detection unit: and decomposing the curve by adopting a wavelet transform method to separate the heartbeat signal.
A heart rate detection method based on a tof camera comprises the following steps:
step 2, separating and reconstructing heartbeat signals according to the original signals by adopting a wavelet transform method to determine the heartbeat value of the human body;
and 3, comparing the heartbeat value with a preset comparison value.
Specifically, the step 1 includes:
step 11, carrying out data processing on the acquired target information by taking a frame as a unit to acquire a distance sequence;
and step 12, obtaining the distance sequence change data generated by the multi-frame target information to form an original signal.
Data processing is performed in units of frames, each frame time interval is 16ms, and the distance between a plurality of points and the tof camera is included. Assuming that the distance of the target relative to the camera does not change within one frame time, the distance information of the camera at different points between two frames is consistent. Traversing data acquired by a tof camera at a certain moment, and traversing the data in a picture line by taking a picture as an example; and then tracking the coordinates of a specific target in the data frame sequence to obtain the distance sequence of the target. The present embodiment mainly acquires the motion of the chest of the human body to acquire the heartbeat information, and for the chest vibrating with the heartbeat, 60 distance data per second form distance waveform data as in fig. 3. The data of the variation of the chest distance includes the heartbeat signal.
The chest distance variation data sequence from the signal processing module contains the distance transformation caused by the heartbeat. The heart beat signal is characterized in that the heart beat frequency is 0.9-2.0 Hz. Therefore, the heartbeat signal is separated using the wavelet transform method. The wavelet transform method can divide the time-frequency domain in more detail in both low frequency and high frequency than the wavelet decomposition. The method specifically comprises the following steps:
step 21, according to
Carrying out signal decomposition;
step 22, according to
Reconstructing the signal, wherein the expression is mainly used for reconstructing the decomposed signal according to the corresponding frequency range;
step 23, obtaining a heartbeat value according to the reconstructed signal period;
wherein the content of the first and second substances,
for the scale function, ψ (t) is a wavelet function, h (k) and g (k) respectively represent a low-pass filter and a high-pass filter in the decomposition process, Φ (t) represents the process of signal decomposition, the inverse can be used for signal reconstruction, l represents the number of layers of decomposition, k is a translation variable, and t is time.
In this embodiment, the original signal is decomposed by 6 layers during signal decomposition, frequency difference between adjacent nodes after 6 layers of decomposition can be known to be 0.15625Hz according to nyquist theorem, the frequency range is gradually increased with the increase of nodes, and the 6 th to 12 th nodes of the sixth layer are selected according to the heartbeat frequency to reconstruct and obtain the heart rate signal hr (t).
It can be understood that the heartbeat signal is relatively weak and is easily interfered by the clutter, and in order to improve the reconstruction accuracy and reliability of the heartbeat signal, the heartbeat signal is further processed by adopting an autocorrelation algorithm, so that the periodic signal covered by the clutter is effectively highlighted. Specifically, optimizing the reconstructed heartbeat signal includes:
step 2211, shifting the obtained heart rate signal HR (t) along the time axis by an interval td to obtain a translated heart rate signal HR (t + td);
step 2212, calculating autocorrelation coefficients of the heart rate waveforms before and after translation by using an autocorrelation algorithm:
wherein σ2Expressing a normalization factor, mu is a population mean value, E is an expected value, and it needs to be noted that the method is the prior art;
step 2213, obtaining a plurality of autocorrelation coefficients by adjusting the translation time interval td until the time interval covers the whole time axis;
step 2214, obtaining heart rate cycle according to the autocorrelation coefficient and calculating the heartbeat: the signal shift interval coincides with the heart rate cycle when the autocorrelation coefficient is maximum.
Claims (9)
1. Heart rate detection device based on tof camera, its characterized in that includes:
the signal acquisition module is used for acquiring human body information to be detected and acquiring distance change data generated by human body distance according to the human body information, wherein the distance change data form an original signal;
the signal processing module is used for separating and reconstructing heartbeat signals according to the original signals by adopting a wavelet transform method so as to determine the heartbeat value of the human body;
and the index reminding module is used for displaying a comparison result of the heartbeat value and a preset comparison value and giving an alarm according to the comparison result.
2. The tof camera-based heart rate detection apparatus according to claim 1, wherein the signal acquisition module comprises at least one tof camera.
3. The tof camera-based heart rate detection device according to claim 1, wherein the index reminding module comprises a display screen and a speaker.
4. The tof camera based heart rate detection apparatus according to claim 1, wherein the signal processing module comprises:
a signal processing unit: the system is used for acquiring a curve of the human body distance along with time change according to an original signal;
sign signal detection unit: and decomposing the curve by adopting a wavelet transform method to separate the heartbeat signal.
5. Heart rate detection method based on tof camera, which is characterized by comprising the following steps:
step 1, collecting human body information to be detected and acquiring distance change data generated by human body distance according to the human body information, wherein the distance change data form an original signal;
step 2, separating and reconstructing heartbeat signals according to the original signals by adopting a wavelet transform method to determine the heartbeat value of the human body;
and 3, comparing the heartbeat value with a preset comparison value.
6. The tof camera-based heart rate detection method according to claim 5, wherein the step 1 comprises:
step 11, carrying out data processing on the acquired target information by taking a frame as a unit to acquire a distance sequence;
and step 12, obtaining the distance sequence change data generated by the multi-frame target information to form an original signal.
7. The tof camera-based heart rate detection method according to claim 5, wherein the step 2 comprises:
step 21, according to
Carrying out signal decomposition;
step 22, according to
Carrying out signal reconstruction;
step 23, obtaining a heartbeat value according to the reconstructed signal period;
wherein the content of the first and second substances,
for the scale function, ψ (t) is a wavelet function, h (k) and g (k) respectively represent a low-pass filter and a high-pass filter in the decomposition process, Φ (t) represents the process of signal decomposition, the inverse can be used for signal reconstruction, l represents the number of layers of decomposition, k is a translation variable, and t is time.
8. The tof camera-based heart rate detection method according to claim 7, wherein during the decomposition, the original signal is decomposed by 6 layers, and the 6 th to 12 th nodes of the sixth layer are selected to reconstruct to obtain a heart rate signal HR (t).
9. The tof camera-based heart rate detection method according to claim 8, wherein the step 22 and the step 23 further comprise: step 221, optimizing the reconstructed heartbeat signal, including:
step 2211, shifting the obtained heart rate signal HR (t) along the time axis by an interval td to obtain a translated heart rate signal HR (t + td);
step 2212, calculating autocorrelation coefficients of the heart rate waveforms before and after translation by using an autocorrelation algorithm:
wherein σ2Representing a normalization factor, mu is an overall mean value, and E is an expected value;
step 2213, obtaining a plurality of autocorrelation coefficients by adjusting the translation time interval td until the time interval covers the whole time axis;
step 2214, obtaining the heart rate cycle according to the autocorrelation coefficient and solving the heart beat value: the signal shift interval coincides with the heart rate cycle when the autocorrelation coefficient is maximum.
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Cited By (1)
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