CN111297343A - Motion artifact elimination system for PPG heart rate measurement and implementation method thereof - Google Patents
Motion artifact elimination system for PPG heart rate measurement and implementation method thereof Download PDFInfo
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- CN111297343A CN111297343A CN202010198984.4A CN202010198984A CN111297343A CN 111297343 A CN111297343 A CN 111297343A CN 202010198984 A CN202010198984 A CN 202010198984A CN 111297343 A CN111297343 A CN 111297343A
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- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000009532 heart rate measurement Methods 0.000 title claims abstract description 22
- 230000008030 elimination Effects 0.000 title claims abstract description 10
- 238000003379 elimination reaction Methods 0.000 title claims abstract description 10
- 238000013507 mapping Methods 0.000 claims abstract description 31
- 238000012545 processing Methods 0.000 claims abstract description 10
- 239000008280 blood Substances 0.000 claims abstract description 8
- 210000004369 blood Anatomy 0.000 claims abstract description 8
- 238000001228 spectrum Methods 0.000 claims abstract description 8
- 238000012549 training Methods 0.000 claims description 9
- 210000003205 muscle Anatomy 0.000 claims description 8
- 230000000149 penetrating effect Effects 0.000 claims description 4
- 230000002093 peripheral effect Effects 0.000 claims description 2
- 238000002474 experimental method Methods 0.000 abstract description 2
- 230000001360 synchronised effect Effects 0.000 abstract description 2
- 238000013186 photoplethysmography Methods 0.000 description 29
- 230000003287 optical effect Effects 0.000 description 6
- 238000000354 decomposition reaction Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 238000012880 independent component analysis Methods 0.000 description 2
- 230000005693 optoelectronics Effects 0.000 description 2
- 230000035515 penetration Effects 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000017531 blood circulation Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
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- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
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- 239000011159 matrix material Substances 0.000 description 1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- 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
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02416—Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
- A61B5/7207—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts
Abstract
The invention relates to a motion artifact elimination system for PPG heart rate measurement and an implementation method thereof, and the motion artifact elimination system is technically characterized in that: the system comprises two groups of light sources capable of generating different light intensities and light spectrums, a photoelectric sensor and a system control circuit, wherein the system control circuit is respectively connected with the two groups of light sources and the photoelectric sensor; the two groups of light sources are close to each other and are arranged at equal intervals relative to the center of the photoelectric sensor, and the system control circuit alternately collects light intensity data corresponding to the two groups of light sources through the photoelectric sensor and carries out motion artifact elimination processing. The invention collects the intensity of reflected light electric signals corresponding to two lights in real time, obtains the mapping relation between two groups of photoelectric signals through a plurality of experiments, maps a reference signal into the range of an original PPG signal through numerical value mapping, removes motion artifacts in the original PPG signal even tissue reflection signals through a synchronous difference method, thereby obtaining a clear blood volume change signal, and finally measures the accurate heart rate under the condition of motion.
Description
Technical Field
The invention belongs to the technical field of photoelectric measurement, and particularly relates to a motion artifact elimination system for PPG heart rate measurement and an implementation method thereof.
Background
In heart rate measurement based on photoplethysmography (PPG), accurate heart rate measurements cannot be made while in motion due to the presence of motion artifacts. Particularly, when a person is tested to walk or run, the exercise frequency and the heart rate value are relatively close to each other, so that aliasing is caused to a certain degree, and the heart rate method of PPG cannot be accurately and continuously acquired.
The current method for eliminating motion artifacts generally uses an acceleration sensor as a reference input signal and is implemented by using some numerical algorithms, which mainly include the following two algorithms: (1) adaptive filtering algorithms, such as: least squares (LMS), Recursive Least Squares (RLS), Kalman filters (Kalman-Filter), and the like; (2) signal decomposition algorithms such as: independent Component Analysis (ICA), Empirical Mode Decomposition (EMD), Singular Spectrum Analysis (SSA) and the like, and the photoelectric signal is filtered or reconstructed according to the reference signal to achieve the aim of removing the motion artifact.
However, the above algorithm has problems: (1) the reference signals of the above two algorithms are typically motion signals (motion data acquired by a 6, 9-axis accelerometer) external to the optoelectronic system, and there is no explicit dependency relationship with the acquired optoelectronic signals. (2) Because the sampling frequency of the signals is in the millisecond level (less than 100Hz), the synchronism of the two signals cannot be ensured at all. (3) The adaptive filtering algorithm is very sensitive to the reference signal, while the signal decomposition algorithm usually requires matrix operation, and has huge calculation amount and storage amount, which are not suitable for being implemented in an embedded system with limited energy consumption and storage space.
In summary, the existing method performs secondary correction on the measured value from the data processing perspective, but cannot fundamentally eliminate the motion artifact problem in the PPG heart rate measurement, and is difficult to transplant into an embedded system.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a motion artifact elimination system for PPG heart rate measurement and an implementation method thereof.
The technical problem to be solved by the invention is realized by adopting the following technical scheme:
a motion artifact elimination system for PPG heart rate measurement comprises two groups of light sources capable of generating different light intensities and light spectrums, a photoelectric sensor and a system control circuit, wherein the system control circuit is respectively connected with the two groups of light sources and the photoelectric sensor; the two groups of light sources are close to each other and are arranged at equal intervals relative to the center of the photoelectric sensor, and the system control circuit alternately collects light intensity data corresponding to the two groups of light sources through the photoelectric sensor and carries out motion artifact elimination processing.
Further, the two groups of light sources are two light sources as follows: the first light source has the capability of penetrating skin and muscle tissues, and the signal contains motion artifact and blood volume change information; the second type of light source does not have the ability to penetrate skin and muscle tissue, and only motion artifact information is present in the signal.
Further, the light source adopts an LED lamp.
Furthermore, the system control circuit is formed by connecting the MCU and peripheral circuits thereof.
An implementation method of a motion artifact cancellation system for PPG heart rate measurement comprises the following steps:
step 1, a system control circuit controls two groups of light sources to alternately emit light rays with different light intensities and light frequency spectrums, and two paths of sensor data respectively comprising original PPG signals and reference signals are acquired through a photoelectric sensor;
step 2, the system control circuit learns a mapping model of the reference signal by an off-line training method for the two paths of sensor data;
step 3, mapping the original reference signal data by using a mapping model of the reference signal to obtain mapped reference data;
and 4, carrying out differential processing on the mapped reference data and the original PPG signal, removing motion artifact information in the PPG signal, and finally obtaining processed clean PPG data for subsequent signal processing.
Further, the light source adopts an LED lamp.
Further, the raw PPG signal contains motion artifact and blood volume change information, the reference signal motion artifact information.
Further, the specific implementation method of step 2 is as follows: collecting data of two paths of sensors, storing a batch of paired off-line data, and learning a mapping model of a reference signal by using a data training method.
Further, the off-line training of the two paths of sensor data is realized by adopting a least square method.
Further, the mapping model of the reference signal uses a linear mapping model, a piecewise linear mapping model or a nonlinear mapping model.
The invention has the advantages and beneficial effects that:
the invention has reasonable design, alternately emits two lights with different light intensities and light frequency spectrums by controlling two adjacent LED lamps, acquires the intensity of reflected photoelectric signals corresponding to the two lights in real time by using a photoelectric sensor, obtains the mapping relation between two groups of photoelectric signals by a plurality of experiments, maps a reference signal into the range of an original PPG signal by numerical value mapping, removes motion artifact or even tissue reflection signal in the original PPG signal by a synchronous difference method, thereby obtaining a clear blood volume change signal, and finally measures the accurate heart rate under the motion condition.
Drawings
FIG. 1 is a schematic diagram of the system connections of the present invention;
FIG. 2 is a timing diagram of the operation of the system of the present invention;
FIG. 3 is a block diagram of the system process flow of the present invention;
FIG. 4 is a piecewise-linear mapping model trained in an embodiment.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
A motion artifact eliminating system for PPG heart rate measurement comprises A, B two groups of LED lamps and a photoelectric sensor PD and a system control circuit, wherein the system control circuit is respectively connected with A, B two groups of LED lamps and photoelectric sensors PD. Wherein A, B the two sets of LED lamps are located adjacent to and equidistant from the center of the photosensor PD to ensure the similarity of the light paths of the two sets of LED lamps. A. The two groups of LED lamps are driven by different types of LED lamps through different driving currents, so that light rays with different light intensities and light spectrums are generated to ensure different PPG illumination effects, wherein the A type of light rays have the capability of penetrating through skin and muscle tissues, and signals contain movement artifact and blood volume change information; the B light has no ability to penetrate skin and muscle tissue, and only motion artifact information is in the signal. The photoelectric sensor PD is located the central point of LED lamp and puts, gathers A, B the corresponding light intensity data of two sets of LED lamps through system control circuit to ensure that two sets of LED lamps are driven luminous normally and photoelectric sensor correctly obtains the light intensity array in the light path.
In this embodiment, the system control circuit adopts a control circuit with a single chip as a core, and is used for controlling the working time sequence of two groups of LED lamps to work, collecting the data of the photoelectric sensor, and eliminating the motion artifact of the collected data.
As shown in fig. 2, a typical timing cycle (in microseconds) of the system control circuit is composed of two parts, an operating interval and a sleep interval, wherein the sleep interval is much longer than the operating interval. In the working interval, two time slots A and B work, in each time slot, the LED is lightened by the circuit in a specified time sequence to emit light, the work of photoelectric induction, analog-to-digital conversion, noise removal, data acquisition and the like of the PD is carried out immediately, and finally output data reflects the intensity of reflected light corresponding to the light emission. And the group A of lights and the PD in the time slot A are matched to carry out photoelectric acquisition, and the group B of lights and the PD in the time slot B are matched to carry out photoelectric acquisition. Because the A, B two groups of lamps and the PD are very close to each other, and the sampling interval is more than ten microseconds, compared with the human body movement (generally in the order of seconds), the light path change of A, B two groups of sampling values in the same working interval is very small; and because A, B has difference of light intensity and wavelength between two sets of optical path systems, the penetration capacity is different. In practice, the group B lamps can be controlled to have weak penetration capability, and the returned light signal only contains the motion artifact signal in the light path. Whereas group a lamps are normally configured so that their returned light signals contain both useful PPG signals and motion artifact signals caused by motion. A signal mapping model can be constructed through learning of A, B two groups of signals, a B group of reference signals are mapped to an A group of space, and a PPG signal with motion artifacts removed is obtained through a simple difference method.
The invention also provides an implementation method of a motion artifact removal system for PPG heart rate measurement, as shown in fig. 3, comprising the following steps:
step 1, a system control circuit controls two groups of LED lamps to alternately emit light rays with different light intensities and light spectrums, and two paths of sensor data are collected through a photoelectric sensor PD.
In the step, the system control circuit controls the two groups of LED lamps to emit light with different light intensity and light frequency, wherein the group A of the LED lamps have the capability of penetrating through skin and muscle tissues, and signals contain movement artifact and blood volume change information; group B lights do not have the ability to penetrate skin and muscle tissue, and only motion artifact information is in the signal. And controlling the photoelectric sensor to sample alternately in microsecond time slices to obtain a PPG signal with reference information (in the embodiment, the A group data represents the original PPG signal, and the B group data represents the reference information). The original PPG signal contains blood flow information, optical path change information, and random noise, while the reference signal contains only the optical path change information and random noise. Because the A, B two groups of optical paths are close and the acquisition time is close (microsecond level), the variation trend of the optical path variation information in the two paths of data generated by the two groups of optical paths is basically consistent and only has difference in amplitude.
And 2, learning a mapping model of the reference signal by the system control circuit by adopting an off-line training method for the two paths of sensor data.
In this step, the system controls a single channel to collect two channels of sensor data, stores a batch of paired off-line data (each pair of data includes a PPG data point and a reference data point), and learns a mapping model of a reference signal using a data training method. The mapping model of the reference signal can be selected from a simple linear mapping model, a piecewise linear mapping model and a nonlinear mapping model.
In this embodiment, a piecewise linear model is used, and model training is performed by spline transformation, and the trained piecewise linear model is shown in fig. 4.
And 3, mapping the B group of data by using a mapping model of the reference signal to obtain the B group of mapped reference data. The mapping model can map the amplitude of the reference signal to the PPG raw signal space by a numerical transformation.
And 4, carrying out differential processing on the mapped B group reference data and the A group original PPG data, removing motion artifact information in the PPG signal, and finally obtaining processed clean PPG data for subsequent signal processing.
Nothing in this specification is said to apply to the prior art.
It should be emphasized that the embodiments described herein are illustrative rather than restrictive, and thus the present invention is not limited to the embodiments described in the detailed description, but also includes other embodiments that can be derived from the technical solutions of the present invention by those skilled in the art.
Claims (10)
1. A motion artifact cancellation system for PPG heart rate measurement, characterized by: the system comprises two groups of light sources, photoelectric sensors and a system control circuit, wherein the two groups of light sources can generate different light intensities and light spectrums; the two groups of light sources are close to each other and are arranged at equal intervals relative to the center of the photoelectric sensor, and the system control circuit alternately collects light intensity data corresponding to the two groups of light sources through the photoelectric sensor and then carries out motion artifact elimination processing.
2. A motion artifact cancellation system for PPG heart rate measurement according to claim 1, characterized in that: the two groups of light sources are as follows: the first light source has the capability of penetrating skin and muscle tissues, and the signal contains motion artifact and blood volume change information; the second type of light source does not have the ability to penetrate skin and muscle tissue, and only motion artifact information is present in the signal.
3. A motion artifact cancellation system for PPG heart rate measurement according to claim 1 or 2, characterized in that: the light source adopts an LED lamp.
4. A motion artifact cancellation system for PPG heart rate measurement according to claim 1 or 2, characterized in that: the system control circuit is formed by connecting an MCU and peripheral circuits thereof.
5. A method of implementing a motion artifact cancellation system for PPG heart rate measurement according to any of claims 1 to 4, characterized by the steps of:
step 1, a system control circuit controls two groups of light sources to alternately emit light rays with different light intensities and light frequency spectrums, and two paths of sensor data respectively comprising original PPG signals and reference signals are acquired through a photoelectric sensor;
step 2, the system control circuit learns a mapping model of the reference signal by an off-line training method for the two paths of sensor data;
step 3, mapping the original reference signal data by using a mapping model of the reference signal to obtain mapped reference data;
and 4, carrying out differential processing on the mapped reference data and the original PPG signal, removing motion artifact information in the PPG signal, and finally obtaining processed clean PPG data for subsequent signal processing.
6. A method of implementing a motion artifact cancellation system for PPG heart rate measurement according to claim 5, characterized by: the light source adopts an LED lamp.
7. A method of implementing a motion artifact cancellation system for PPG heart rate measurement according to claim 5, characterized by: the raw PPG signal contains motion artifact and blood volume change information, and the reference signal motion artifact information.
8. A method of implementing a motion artifact cancellation system for PPG heart rate measurement according to claim 5, characterized by: the specific implementation method of the step 2 comprises the following steps: collecting data of two paths of sensors, storing a batch of paired off-line data, and learning a mapping model of a reference signal by using a data training method.
9. A method of implementing a motion artifact cancellation system for PPG heart rate measurement according to claim 5, characterized by: and the off-line training of the two paths of sensor data is realized by adopting a least square method.
10. A method of implementing a motion artifact cancellation system for PPG heart rate measurement according to claim 5, characterized by: the mapping model of the reference signal uses a linear mapping model, a piecewise linear mapping model or a nonlinear mapping model.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111887858A (en) * | 2020-08-04 | 2020-11-06 | 西安电子科技大学 | Ballistocardiogram signal heart rate estimation method based on cross-modal mapping |
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| CN108042107A (en) * | 2017-11-28 | 2018-05-18 | 南京邮电大学 | A kind of PPG signals puppet difference correcting method |
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Application publication date: 20200619 |