CN105997043B - A kind of pulse frequency extracting method based on wrist wearable device - Google Patents

Abstract

The invention discloses a pulse rate extraction method based on a wrist wearable device. The present invention first classifies the current motion state by analyzing the acceleration information collected by the acceleration sensor. For different exercise states, different algorithms are used to obtain pulse rate information. For the test under exercise, it is also analyzed whether its movement is regular. For regular exercise and irregular exercise, different algorithms are used to obtain pulse rate information. This classification method makes the acquisition of pulse rate more accurate. At the same time, the problem that the pulse rate cannot be obtained for the noise signal is also solved.

Description

A pulse rate extraction method based on wrist wearable device

technical field

The invention relates to the field of wrist wearable devices, in particular to a pulse rate extraction method based on wrist wearable devices.

Background technique

With the development of low power consumption technology and physiological parameter monitoring technology, wearable devices have started a revolution in the field of medical equipment. Among the various parameters monitored by wearable devices, pulse rate is particularly important. Because pulse rate monitoring can not only prevent sudden heart attacks during exercise, but also provide guidance in daily training. Usually, people realize pulse rate monitoring by obtaining ECG through the pulse rate belt that is tied on the chest. This kind of pulse rate belt needs to tighten the chest to obtain a reliable signal, and the comfort is poor.

The PPG (photoelectric solvent pulse wave) signal is a physical quantity that characterizes changes in blood volume in capillaries. As the heart beats, blood flows into the capillaries, causing changes in the volume of blood in the vessels. Therefore, as a physiological signal, PPG has the same biological significance as the ECG (cardiac electricity) signal. The ability of hemoglobin in human blood vessels to absorb green light is stronger than that of other light. According to this characteristic, PPG signals can be obtained by emitting green light to the epidermis and then detecting changes in the intensity of green light reflected by capillaries. The generation and detection of green light can be realized by photoelectric sensors. In the prior art, there has been a method of extracting the pulse rate by replacing the ECG signal collected by the pulse rate belt with the PPG signal collected by the watch, which greatly improves the comfort.

However, the PPG signal is easily disturbed by motion-generated noise, most of which are generated by the sliding of the sensor relative to the skin during motion, which is periodic and has a frequency close to the pulse rate. Therefore, it is very difficult to extract the pulse rate from the PPG signal in the state of exercise. It is difficult for common wrist devices to accurately measure the pulse rate during exercise.

Contents of the invention

In view of this, the present invention provides a pulse rate extraction method based on a wrist-type wearable device, which can obtain a more accurate pulse rate in an exercise state and a non-exercise state.

A pulse rate extraction method based on a wrist-type wearable device, the wrist-type wearable device is mainly composed of an acceleration sensor and a photoelectric sensor; the extraction method specifically includes the following steps:

Step 1. Turn on the wrist wearable device, and the acceleration sensor and the photoelectric sensor perform collection work respectively; after the acceleration sensor collects n acceleration values, store the sampled n acceleration data in the array d; perform step 2;

Step 2. Calculate the modulus of the n acceleration values collected in step 1, and compare them with the threshold q in turn; if the number of modulus values greater than the threshold q exceeds the set value x, and x=n×10%, then it means Currently in a state of motion, go to step 4; if the number of modulus values greater than the threshold q does not exceed the set value x, it means that you are currently in a static state, go to step 3;

Step 3, using the photoelectric sensor to extract the pulse rate to obtain the photoplethysmography PPG signal, and obtain the pulse rate in the static state by the interval algorithm of the adjacent R points in the PPG signal;

Step 4, according to the motion classification algorithm, the motion state is divided into regular motion and irregular motion, and its determination method is as follows;

S41, select the maximum value a _max from the acceleration modulus

S42. Normalize the acceleration data in the array d;

S43. Select the maximum value p _max in the normalized array d;

S44. Set the threshold value P, take p _max as the reference value, traverse other values on the left side of the reference value in the normalized array d, obtain the first value exceeding the threshold value P, and define it as p _b ; similarly, traverse For other values on the right side of the reference value, obtain the first value that exceeds the threshold P, which is defined as p _c ; after traversing all the values, once the value is not obtained on one side, it is judged as an irregular motion state; perform step 6; if Both p _b and p _c are obtained, then perform step S45;

S45. Define the distance between p _b and p _max as L ₁ , and the distance between p _max and p _c as L ₂ ; if L ₁ and L ₂ are equal, it means that you are doing regular exercise and go to step 5; otherwise, determine For irregular exercise, perform step 6;

Step 5. For the pulse rate extraction method under the regular exercise state, the photoelectric sensor is used to collect the PPG signal, and the pulse rate is extracted;

Step 6. For the pulse rate extraction method in the state of irregular exercise:

First, the photoelectric sensor is used to collect the PPG signal, and then the ANC algorithm is used to denoise the PPG signal, and the pulse rate is obtained by extracting the interval between adjacent P points in the PPG signal.

Beneficial effect:

The present invention first classifies the current motion state by analyzing the acceleration information collected by the acceleration sensor. For different exercise states, different algorithms are used to obtain pulse rate information. For the test under exercise, it is also analyzed whether its movement is regular. For regular exercise and irregular exercise, different algorithms are used to obtain pulse rate information. This classification method makes the acquisition of pulse rate more accurate. At the same time, the problem that the pulse rate cannot be obtained for the noise signal is also solved.

Description of drawings

Fig. 1 is a schematic diagram of the present invention.

Figure 2 is the resting state heart rate extraction.

Figure 3 is a schematic diagram of the motion classification algorithm.

Figure 4 is a schematic diagram of the ANC algorithm.

Fig. 5 is a schematic diagram of frequency domain processing.

Detailed ways

The present invention will be described in detail below with reference to the accompanying drawings and examples.

The present invention provides a pulse rate extraction method based on a wrist wearable device, the main idea of which is:

Due to the presence of noise in the image collected by the photoelectric sensor and the acceleration sensor in the state of irregular motion, it is impossible to extract the pulse rate in the state of irregular motion. Therefore, based on this, the present invention proposes a new pulse rate extraction method. Firstly, the present invention firstly analyzes the data extracted by the acceleration sensor, and judges its motion state and motion law. For the signal collected under the state of irregular motion, denoise processing is performed to obtain a more accurate pulse rate value. That is: the present invention realizes the classification processing of the signals extracted by the photoelectric sensor and the acceleration sensor, and then can adopt different processing methods (the processing method is the prior art) for the signals in different states, and then obtain a more accurate pulse rate.

Wherein, the wrist wearable device of the present invention is composed of an acceleration sensor module, a photoelectric sensor and a processing module.

The specific implementation is as follows, as shown in Figure 1:

Step 1. Turn on the wrist wearable device. At this time, the acceleration sensor and photoelectric sensor will start to work. The photoelectric sensor collects the photoplethysmography (PPG) signal of the current subject in real time, and the acceleration sensor module samples the acceleration signal for a total of n times, and stores the sampled n data in the array d. Go to step 2. In order to ensure the accuracy of the data, the present invention sets a time threshold, counting from the first collection time, once the time threshold is reached, the data in the data d will be cleared, and the collection will be carried out again, and the array will always store the latest period of time acceleration information.

Step 2. Analyze the acceleration signal collected in step 1 to determine the current motion state:

First, according to the previous experimental data and experience, set a threshold q for judging the current motion state;

After that, the n acceleration values in the array d are calculated modulo, and compared with the threshold q in turn. If the number of modulus values greater than the threshold q exceeds the set value x, x<n, and x=n×10%, it means that the current state is in motion, and step 4 is performed; if the number of modulus values greater than the threshold q does not exceed When the value x is set, it means that it is currently in a static state, and step 3 is performed.

Step 3. The pulse rate extraction method in a static state:

Since the PPG signal is a physical quantity representing the change of blood volume in the capillary, along with the beating of the heart, the blood flows to the capillary, resulting in the change of the blood volume in the blood vessel. Therefore, the waveform of PPG in the static state is as stable as ECG, as shown in Figure 2, so the pulse rate extraction method in the static state is: use a photoelectric sensor to extract the pulse rate, obtain the PPG signal, and extract the adjacent pulse rate in the PPG signal. At point R, use the RR interval algorithm to calculate its repetition period T _RR (RR interval), and the reciprocal of T _RR is the current pulse rate. This method is a prior art, and will not be repeated here.

Step 4. When in a motion state, classify the motion state into regular motion and irregular motion according to a motion classification algorithm. The specific identification method is as follows:

S41, select the maximum value a _max from the acceleration modulus

S42. According to the formula (1), normalize the array d to obtain new data p={p ₁ ,p ₂ ,...,p _i ,...,p _n };

S43. In the data p, select the maximum value p _max in the data p;

S44. Set the threshold value P, take p _max as the reference value, sequentially traverse other values on the left side of the reference value in the data p, and obtain the first value exceeding the threshold value P, which is respectively defined as p _b ; similarly, traverse the reference values in the data p For other values on the right side of the value, get the first value that exceeds the threshold P, which is defined as p _c respectively; after traversing all the values, once the value is not obtained on one side, it is judged as an irregular motion state; perform step 6; if Both p _b and p _c are obtained, then perform step S45;

S45. Further judge the current motion state through p _b , p _max and p _c :

Define the distance between p _b and p _max as L ₁ , and the distance between p _max and p _c as L ₂ ; as shown in Figure 3, L ₁ and L ₂ actually represent p _b and p _max , p _max and p max The time difference between _pc . If L ₁ and L ₂ are equal, it means doing regular exercise, go to step 5. Otherwise, it is judged as irregular motion, and go to step 6.

Step 5. For the pulse rate extraction method in the state of regular exercise:

Using the existing conventional technology, the photoelectric sensor is used to collect the PPG signal, and the pulse rate can be obtained after the acceleration signal of the obtained PPG signal is processed according to the following method.

In the case of regular motion, usually as shown in Figure 5, the power spectrum curve corresponding to the acceleration signal usually has two peaks, which correspond to the fundamental wave and harmonics generated by regular motion, and these two peaks will also It also appears in the power spectrum curve of the PPG signal, so as long as the acceleration signal power spectrum is filtered out from the PPG signal power spectrum, an ideal PPG signal can be obtained. Therefore:

In the first step, fast Fourier transform is performed on the acceleration signal and the photoplethysmography signal respectively to obtain respective frequency spectra F _acc , F _ppg .

The second step is to convert F _acc and F _ppg into power spectra X _acc and X _ppg , and find out the corresponding maximum amplitudes A _max and B _max respectively.

The third step, normalization processing, obtained and Afterwards, differential processing is performed to obtain the point with the largest amplitude in the spectrum.

The fourth step, the frequency corresponding to the point with the largest amplitude in the frequency spectrum is the pulse rate.

Since the method is a conventional technology, the focus of the present invention is not here, and the present invention is only briefly introduced.

Step 6. For the pulse rate extraction method in the state of irregular exercise:

Because in the state of irregular motion, the photoelectric sensor will also collect noise interference signals in addition to collecting PPG signals, as shown in Figure 4. For this reason, the present invention adopts ANC algorithm to carry out denoising processing. Since the ANC algorithm is an existing conventional technical means, details are not repeated here. The basic principle of the ANC algorithm is: the acceleration signal generates an optimal estimation signal of the noise interference signal, and the ideal PPG can be obtained by filtering the noise estimation signal from the signal obtained by the photoelectric sensor.

After obtaining an ideal PPG signal, the PP interval T _PP is calculated, and the reciprocal of T _PP is the current pulse rate. This method is a prior art, and will not be repeated here.

To sum up, the above are only preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (1)

1. a pulse rate extraction method based on wrist-type wearable equipment, described wrist-type wearable equipment is mainly made of acceleration sensor and photoelectric sensor; It is characterized in that, extraction method specifically comprises the steps: Step 1. Turn on the wrist wearable device, and the acceleration sensor and the photoelectric sensor perform collection work respectively; after the acceleration sensor collects n acceleration values, store the sampled n acceleration data in the array d; perform step 2; Step 2. Calculate the modulus of the n acceleration values collected in step 1, and compare them with the threshold q in turn; if the number of modulus values greater than the threshold q exceeds the set value x, and x=n×10%, then it means Currently in a state of motion, go to step 4; if the number of modulus values greater than the threshold q does not exceed the set value x, it means that you are currently in a static state, go to step 3; Step 3, using the photoelectric sensor to extract the pulse rate to obtain the photoplethysmography PPG signal, and obtain the pulse rate in the static state by the interval algorithm of the adjacent R points in the PPG signal; Step 4, according to the motion classification algorithm, the motion state is divided into regular motion and irregular motion, and its determination method is as follows; S41, select the maximum value a _max from the acceleration modulus S42. Normalize the acceleration data in the array d; S43. Select the maximum value p _max in the normalized array d; S44. Set the threshold value P, take p _max as the reference value, traverse other values on the left side of the reference value in the normalized array d, obtain the first value exceeding the threshold value P, and define it as p _b ; similarly, traverse For other values on the right side of the reference value, obtain the first value that exceeds the threshold P, which is defined as p _c ; after traversing all the values, once the value is not obtained on one side, it is judged as an irregular motion state; perform step 6; if Both p _b and p _c are obtained, then perform step S45; S45. Define the distance between p _b and p _max as L ₁ , and the distance between p _max and p _c as L ₂ ; if L ₁ and L ₂ are equal, it means that you are doing regular exercise and go to step 5; otherwise, determine For irregular exercise, perform step 6; Step 5. For the pulse rate extraction method under the regular exercise state, the photoelectric sensor is used to collect the PPG signal, and the pulse rate is extracted; Step 6. For the pulse rate extraction method in the state of irregular exercise: First, the photoelectric sensor is used to collect the PPG signal, and then the ANC algorithm is used to denoise the PPG signal, and the pulse rate is obtained by extracting the interval between adjacent P points in the PPG signal.