CN113940637B - Pulse wave signal quality evaluation method, device and storage medium - Google Patents
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Abstract
The invention discloses a pulse wave signal quality evaluation method, a device and a storage medium, which comprise the steps of obtaining an original pulse wave signal; performing band-pass filtering processing on the original pulse wave signals to obtain first pulse wave signals; performing peak detection on the first pulse wave signal, and determining the peak position and the initial position in the first pulse wave signal to obtain first detection data; after the first detection data are cached, waveform characteristic extraction is carried out according to the first detection data, and multiple waveform characteristic data are obtained; and calculating the mass fraction according to the characteristic data of the multiple waveforms to obtain the mass fraction. According to the pulse wave signal quantitative evaluation method, the pulse wave signal is quantitatively evaluated according to the waveform characteristic data, so that the interference components in the pulse wave signal can be quantitatively evaluated to a certain extent, and the method can assist in clinical monitoring.
Description
Technical Field
The present invention relates to the field of medical technologies, and in particular, to a pulse wave signal quality evaluation method, apparatus, and storage medium.
Background
Pulse signals are physiological signals inherent to the human body, which contain very rich physiological information, and information required for clinical monitoring, such as pulse rate, blood oxygen value, etc., can be extracted from the pulse signals. However, in practical applications, the pulse wave signals acquired from the human body by the sensor are prone to various noise and interference, such as ambient light interference, power frequency interference, patient respiration or movement interference, etc., and particularly in neonatal monitoring, limb movements of the neonate are difficult to avoid. At present, although high-frequency or low-frequency interference signals which are not in the range of the human pulse rate can be filtered by a filtering mode, interference components such as motion interference in the range of the human pulse rate cannot be filtered. The quality of the pulse signals can have a certain influence on clinical monitoring, but a pulse wave signal quality evaluation method is still lacking at present, so as to quantitatively evaluate the quality (Signal Quality Index, SQI) of the pulse wave signals.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides a pulse wave signal quality evaluation method, a pulse wave signal quality evaluation device and a storage medium, which can quantitatively evaluate the quality of pulse wave signals.
In a first aspect, a pulse wave signal quality evaluation method according to an embodiment of the present invention includes the steps;
acquiring an original pulse wave signal;
performing band-pass filtering processing on the original pulse wave signals to obtain first pulse wave signals;
performing peak detection on the first pulse wave signal, and determining the peak position and the initial position in the first pulse wave signal to obtain first detection data;
after the first detection data are cached, waveform characteristic extraction is carried out according to the first detection data, and multiple waveform characteristic data are obtained;
and calculating the mass fraction according to the waveform characteristic data to obtain the mass fraction.
The pulse wave signal quality evaluation method according to the embodiment of the invention has at least the following beneficial effects:
according to the pulse wave signal quantitative evaluation method, the pulse wave signal is quantitatively evaluated according to the waveform characteristic data, so that the interference components in the pulse wave signal can be quantitatively evaluated to a certain extent, and the method can assist in clinical monitoring.
According to some embodiments of the invention, the plurality of waveform characteristic data includes a start position of the pulse wave, a peak position, a peak amplitude, an adjacent peak interval, a systolic time, and a diastolic time.
According to some embodiments of the present invention, the calculating the mass fraction according to the plurality of waveform characteristic data to obtain the mass fraction includes the steps of:
normalizing the multiple waveform characteristic data to obtain first data;
and converting the quality score of the first data to obtain the quality score.
According to some embodiments of the present invention, the normalizing the plurality of waveform feature data to obtain first data includes the steps of:
standard deviation calculation is carried out on the waveform characteristic data to obtain standard deviation values;
converting the corresponding waveform characteristic data into a value one under the condition that the standard deviation value is smaller than or equal to a first threshold value;
converting corresponding waveform characteristic data to a numerical value of zero if the standard deviation value is greater than a second threshold value, wherein the second threshold value is greater than the first threshold value;
determining a first difference value according to the standard deviation value and a first threshold value under the condition that the standard deviation value is larger than the first threshold value and smaller than or equal to the average value of the first threshold value and the second threshold value; determining a second difference value according to a second threshold value and the first threshold value; determining a first value from the first difference and the second difference; converting the corresponding waveform characteristic data into the first numerical value;
determining a third difference value according to the standard deviation value and a second threshold value under the condition that the standard deviation value is smaller than or equal to the second threshold value and larger than the average value of the first threshold value and the second threshold value; determining a fourth difference value according to the second threshold value and the first threshold value; determining a second value from the third difference and the fourth difference; and converting the corresponding waveform characteristic data into the second numerical value.
According to some embodiments of the invention, the determining a first value from the first difference and the second difference comprises:
performing proportional operation and square operation on the first difference value and the second difference value to obtain a first operation value;
and carrying out difference operation on the first operation value of which the value is one and two times to obtain the first value.
According to some embodiments of the invention, the determining a second value from the third difference and the fourth difference comprises:
performing proportional operation and square operation on the third difference value and the fourth difference value to obtain a second operation value;
and determining the second operation value which is doubled as the second numerical value.
In a second aspect, a pulse wave signal quality evaluation apparatus according to an embodiment of the present invention includes: the filtering unit is used for carrying out band-pass filtering processing on the original pulse wave signals to obtain first pulse wave signals; the wave crest detection unit is used for carrying out wave crest detection on the first pulse wave signal, determining the wave crest position and the initial position in the first pulse wave signal and obtaining first detection data; the characteristic extraction unit is used for carrying out waveform characteristic extraction according to the first detection data after caching the first detection data to obtain multiple waveform characteristic data; and the quality score conversion unit is used for carrying out quality score calculation according to the plurality of waveform characteristic data to obtain quality scores.
The pulse wave signal quality evaluation device provided by the embodiment of the invention has at least the following beneficial effects:
according to the pulse wave signal quantitative evaluation method, the pulse wave signal is quantitatively evaluated according to the waveform characteristic data, so that the interference components in the pulse wave signal can be quantitatively evaluated to a certain extent, and the method can assist in clinical monitoring.
In a third aspect, a pulse wave signal quality evaluation device according to an embodiment of the present invention includes a processor, where the processor is configured to perform the pulse wave signal quality evaluation method described above.
In a fourth aspect, according to an embodiment of the present invention, there is provided a computer-readable storage medium storing a computer program which, when executed by a processor, implements a pulse wave signal quality evaluation method as described above.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a flowchart illustrating a pulse wave signal quality evaluation method according to an embodiment of the present invention;
fig. 2 is a waveform diagram of pulse wave signals of a monitored person according to embodiment 1 of the present invention;
fig. 3 is a waveform diagram of the pulse wave signal shown in fig. 2 after peak detection;
fig. 4 is a waveform diagram of pulse wave signals of a monitored person without interference components;
fig. 5 is a waveform diagram of a pulse wave signal of a monitored person with motion disturbance components;
fig. 6 is a schematic block diagram of a pulse wave signal quality evaluation device according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
In the description of the present invention, the meaning of "several" means one or more, the meaning of "a plurality of" means two or more, greater than, less than, exceeding, etc. are understood to not include the present number, and "above", "below", "within", etc. are understood to include the present number. If any, the terms "first," "second," etc. are used for distinguishing between technical features only, and should not be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
Referring to fig. 1, the present embodiment discloses a pulse wave signal quality evaluation method, which includes steps S100, S200, S300, S400 and S500, and each step is described in detail below.
S100, acquiring an original pulse wave signal.
In this embodiment, the original pulse wave signal is acquired by the pulse oximeter using the photoplethysmograph. Wherein, the blood oxygen probe of the pulse oximeter respectively sends out a red light signal and an infrared light signal through two luminous tubes, the red light signal and the infrared light signal are partially absorbed after being transmitted through the finger of the detected human body, and periodically fluctuate along with the fluctuation of the pulse of the human body. According to lambert-beer law, the optical signal received by the receiver of the blood oxygen probe also changes periodically, and the optical signal received by the receiver can be converted into an original pulse wave signal after being converted, amplified, sampled and the like. Because the luminotrons of the red light signal and the infrared light signal are arranged on the same side of the blood oxygen probe and are positioned on the same plane, the influence of the interference component in the signals on the red light signal and the infrared light signal is consistent, and therefore, the pulse wave signal obtained through one of the red light signal and the infrared light signal can be selected for quality evaluation. Of course, pulse wave signals obtained through red light signals and infrared light signals can be selected simultaneously for quality evaluation.
S200, performing band-pass filtering processing on the original pulse wave signals to obtain first pulse wave signals.
Because the components of the original pulse wave signal are complex, there may be low-frequency interference components and high-frequency interference components which are not in the range of the pulse rate of the human body, the band-pass filtering processing is performed on the original pulse wave signal, so that the low-frequency interference components and the high-frequency interference components in the first pulse wave signal can be reduced, and the subsequent peak detection is facilitated, wherein fig. 2 shows a section of the filtered infrared light waveform data. The bandpass filtering process may be a hardware process or a software process, where the hardware process may be a process performed by hardware such as an existing bandpass filtering circuit or an integrated bandpass filter, and the software process may be a process performed by an existing bandpass filtering algorithm.
And S300, performing peak detection on the first pulse wave signal, and determining the peak position and the initial position in the first pulse wave signal to obtain first detection data.
And S400, after the first detection data are cached, waveform characteristic extraction is carried out according to the first detection data, and multiple waveform characteristic data are obtained.
Since the pulse signal quality is evaluated for the pulse wave signal waveform in a period of time, the first detection data needs to be buffered, and the buffering time can be set to 5 seconds or 10 seconds, etc., so as to obtain the detection data in a preset time length. The plurality of waveform characteristic data in the present embodiment includes a start position of a pulse wave, a peak position, a peak amplitude, an adjacent peak interval, a systolic time, a diastolic time, and the like. When an interference component is mixed in the pulse wave signal, there may be a difference in the degree of influence of different interference components on different waveform characteristics. According to the embodiment, the mass fraction calculation is performed by integrating the waveform characteristic data, the influence of the interference components on the pulse wave signals can be reflected from multiple angles, and the reliability of the pulse wave signal quality analysis is improved.
S500, calculating the mass fraction according to the characteristic data of the multiple waveforms to obtain the mass fraction.
According to the embodiment, the pulse wave signals are quantitatively estimated according to the waveform characteristic data, so that the interference components in the pulse wave signals can be quantitatively estimated to a certain extent, the clinical monitoring can be assisted, for example, when monitored personnel, such as newborns, are in a calm state, the pulse wave signals have few interference components, the mass fraction is high, and at the moment, the required information can be accurately extracted from the pulse wave signals; when the monitored person is in a state of frequent turning over or moving arms or kicking, the interference component in the pulse wave signal is relatively high, the mass fraction is relatively low, and the required information is difficult to accurately extract from the pulse wave signal, so that the mass fraction monitoring can be performed. When the quality score is lower than a preset score threshold, alarm information is sent out to warn that the reliability of the currently displayed pulse parameter result is lower, and the frequent confirmation of the pulse parameter result by a guardian is reduced, so that the working intensity of the guardian is reduced.
In step S500 of the present embodiment, mass fraction calculation is performed according to a plurality of waveform feature data to obtain mass fractions, including the steps of:
s510, carrying out normalization processing on the multiple waveform characteristic data to obtain first data.
The embodiment has a plurality of waveform characteristic data, the units of different items of data are inconsistent, and normalization processing is needed to convert the waveform characteristic data with dimension into dimensionless values ranging from 0 to 1.
S520, performing quality score conversion on the first data to obtain quality scores.
The waveform characteristic data is normalized to obtain dimensionless values ranging from 0 to 1, and the dimensionless values are multiplied by a fraction coefficient and added to obtain the mass fraction. The mass fraction range of the embodiment is between 0 and 100, wherein a mass fraction of 0 indicates that the ratio of the interference component in the pulse wave signal is too high to analyze the correct pulse parameters; the mass fraction of 100 shows that the waveform characteristics of the pulse wave signals are obvious, the ratio of interference components in the pulse wave signals is very low, and the pulse parameters can be accurately analyzed. In the mass fraction conversion, it is necessary to perform a weighting process according to the degree of influence of different waveform characteristics on the pulse wave signal. For example, the initial fractional coefficient is 100, the degree of influence of the pulse wave amplitude on the pulse wave signal is higher, the fractional coefficient is a1×100 if a higher weight is assigned, the degree of influence of the contraction time on the pulse wave signal is lower, and the fractional coefficient is a2×100 if a lower weight is assigned.
Step S510, performing normalization processing on the multiple waveform feature data to obtain first data, including the steps of:
s511, respectively carrying out standard deviation calculation on the waveform characteristic data to obtain standard deviation values;
for example, the waveform characteristic data includes a plurality of items such as a start position, a peak amplitude, an adjacent peak interval, a contraction time and a relaxation time of a pulse wave, each item of waveform characteristic data includes a plurality of pieces of sampling data within a preset time length, and standard deviation calculation is performed by using the plurality of pieces of sampling data, so that a standard deviation value corresponding to each item of waveform characteristic data can be obtained.
S512, converting the corresponding waveform characteristic data into a value I under the condition that the standard deviation value is smaller than or equal to a first threshold value;
s513, converting the corresponding waveform characteristic data into a numerical value of zero under the condition that the standard deviation value is larger than a second threshold value, wherein the second threshold value is larger than the first threshold value;
s514, determining a first difference value according to the standard deviation value and the first threshold value under the condition that the standard deviation value is larger than the first threshold value and smaller than or equal to the average value of the first threshold value and the second threshold value; determining a second difference value according to the second threshold value and the first threshold value; determining a first value according to the first difference and the second difference; converting the corresponding waveform characteristic data into a first numerical value;
s515, determining a third difference value according to the standard deviation value and the second threshold value under the condition that the standard deviation value is smaller than or equal to the second threshold value and larger than the average value of the first threshold value and the second threshold value; determining a fourth difference value according to the second threshold value and the first threshold value; determining a second value according to the third difference value and the fourth difference value; the corresponding waveform characteristic data is converted to a second value.
Step S514, determining the first value according to the first difference and the second difference, includes:
performing proportional operation and square operation on the first difference value and the second difference value to obtain a first operation value;
and carrying out difference operation on the first operation value of the first and the second times of the numerical value to obtain a first numerical value.
Step S515, determining a second value according to the third difference and the fourth difference, includes:
performing proportional operation and square operation on the third difference value and the fourth difference value to obtain a second operation value;
and determining the second operation value of the double as a second numerical value.
For ease of understanding, steps S511 to S515 are described below in terms of Z functions.
Wherein x represents standard deviation values calculated by using different waveform characteristic data, a represents a first threshold value, b represents a second threshold value, and the first threshold value and the second threshold value need to be configured according to specific pulse characteristics and experience of technicians. Wherein x is less than or equal to a, the pulse wave data in the current analysis window is stable and basically has no influence of interference components, b < x is larger fluctuation and larger influence of interference components, and x is positioned between a and b, and the pulse wave data in the current analysis window is interfered to a certain extent. The boundary of the quality of the pulse wave signal is fuzzy, and the embodiment normalizes the extracted waveform characteristic data through a membership function (namely a Z function) based on a fuzzy mathematic membership theory, so that the dimensional waveform characteristic data can be converted into dimensionless numerical values, the pulse signal quality can be quantitatively evaluated, and the method is easy to understand.
Referring to fig. 4 and 5, fig. 4 is a section of pulse wave signal without interference signal, and the signal quality score of each second obtained by the pulse wave signal quality method of the present embodiment is marked in fig. 4. It can be seen from fig. 4 that the signal quality score of the clean pulse signal is above 95 minutes. Fig. 5 is a section of pulse signal with body movement interference, the signal quality score of each second obtained by the pulse wave signal quality method of the embodiment is marked in fig. 5, and as can be seen from fig. 5, the signal quality corresponding to the place with interference is less than 60 minutes, and the signal quality of the signal section without obvious interference is generally more than 80 minutes. Therefore, the pulse wave signal quality can be quantitatively evaluated, and the device can play an auxiliary role in clinical monitoring.
Example 2
Referring to fig. 6, the present embodiment discloses a pulse wave signal quality evaluation device, which includes a filtering unit 610, a peak detection unit 620, a feature extraction unit 630 and a quality score conversion unit 640, wherein the filtering unit 610 is configured to perform band-pass filtering processing on an original pulse wave signal to obtain a first pulse wave signal, the peak detection unit 620 is configured to perform peak detection on the first pulse wave signal, determine a peak position and a starting position in the first pulse wave signal, obtain first detection data, the feature extraction unit 630 is configured to perform waveform feature extraction according to the first detection data after buffering the first detection data, obtain multiple waveform feature data, and the quality score conversion unit 640 is configured to perform quality score calculation according to the multiple waveform feature data, so as to obtain a quality score.
The mass fraction conversion unit 640 of the present embodiment includes a first conversion module and a second conversion module, where the first conversion module is configured to normalize the multiple waveform feature data to obtain first data, and the second conversion module is configured to perform mass fraction conversion on the first data to obtain a mass fraction.
The first conversion module comprises a standard deviation operation module, a first comparison module, a second comparison module, a third comparison module and a fourth comparison module, wherein the standard deviation operation module is used for respectively carrying out standard deviation calculation on the multiple waveform characteristic data to obtain a standard deviation value; the first comparison module is used for converting the corresponding waveform characteristic data into a value I under the condition that the standard deviation value is smaller than or equal to a first threshold value; the second comparison module is used for converting the corresponding waveform characteristic data into a numerical value of zero under the condition that the standard deviation value is larger than a second threshold value, wherein the second threshold value is larger than the first threshold value; the third comparison module is used for determining a first difference value according to the standard deviation value and the first threshold value under the condition that the standard deviation value is larger than the first threshold value and smaller than or equal to the average value of the first threshold value and the second threshold value; determining a second difference value according to the second threshold value and the first threshold value; determining a first value according to the first difference and the second difference; converting the corresponding waveform characteristic data into a first numerical value; the fourth comparison module is used for determining a third difference value according to the standard deviation value and the second threshold value under the condition that the standard deviation value is smaller than or equal to the second threshold value and larger than the average value of the first threshold value and the second threshold value; determining a fourth difference value according to the second threshold value and the first threshold value; determining a second value according to the third difference value and the fourth difference value; the corresponding waveform characteristic data is converted to a second value.
Wherein determining the first value from the first difference and the second difference comprises: performing proportional operation and square operation on the first difference value and the second difference value to obtain a first operation value; and carrying out difference operation on the first operation value of the first and the second times of the numerical value to obtain a first numerical value.
Determining a second value from the third difference and the fourth difference, comprising: performing proportional operation and square operation on the third difference value and the fourth difference value to obtain a second operation value; and determining the second operation value of the double as a second numerical value.
According to the embodiment, the pulse wave signal is quantitatively estimated according to the waveform characteristic data, so that the interference component in the pulse wave signal can be quantitatively estimated to a certain extent, and the method can assist in clinical monitoring. The details not related to this embodiment can refer to embodiment 1, and this embodiment will not be described in detail.
Example 3
The embodiment discloses a pulse wave signal quality evaluation device, which comprises a processor, wherein the processor is used for the pulse wave signal quality evaluation method. According to the embodiment, the pulse wave signal is quantitatively estimated according to the waveform characteristic data, so that the interference component in the pulse wave signal can be quantitatively estimated to a certain extent, and the method can assist in clinical monitoring. The details not related to this embodiment can refer to embodiment 1, and this embodiment will not be described in detail.
Example 4
The present embodiment discloses a computer-readable storage medium storing a computer program which, when executed by a processor, implements the pulse wave signal quality evaluation method as described above. According to the embodiment, the pulse wave signal is quantitatively estimated according to the waveform characteristic data, so that the interference component in the pulse wave signal can be quantitatively estimated to a certain extent, and the method can assist in clinical monitoring. The details not related to this embodiment can refer to embodiment 1, and this embodiment will not be described in detail.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of one of ordinary skill in the art without departing from the spirit of the present invention.
Claims (6)
1. A pulse wave signal quality assessment method, characterized by comprising the steps of:
acquiring an original pulse wave signal;
performing band-pass filtering processing on the original pulse wave signals to obtain first pulse wave signals;
performing peak detection on the first pulse wave signal, and determining the peak position and the initial position in the first pulse wave signal to obtain first detection data;
after the first detection data are cached, waveform characteristic extraction is carried out according to the first detection data, and multiple waveform characteristic data are obtained, wherein the multiple waveform characteristic data comprise the starting position, the wave crest amplitude, the adjacent wave crest interval, the contraction time and the relaxation time of pulse waves;
normalizing the multiple waveform characteristic data to obtain first data;
performing mass fraction conversion on the first data to obtain the mass fraction;
the normalization processing is performed on the multiple waveform characteristic data to obtain first data, and the method comprises the following steps:
standard deviation calculation is carried out on the waveform characteristic data to obtain standard deviation values;
converting the corresponding waveform characteristic data into a value one under the condition that the standard deviation value is smaller than or equal to a first threshold value;
converting corresponding waveform characteristic data to a numerical value of zero if the standard deviation value is greater than a second threshold value, wherein the second threshold value is greater than the first threshold value;
determining a first difference value according to the standard deviation value and a first threshold value under the condition that the standard deviation value is larger than the first threshold value and smaller than or equal to the average value of the first threshold value and the second threshold value; determining a second difference value according to a second threshold value and the first threshold value; determining a first value from the first difference and the second difference; converting the corresponding waveform characteristic data into the first numerical value;
determining a third difference value according to the standard deviation value and a second threshold value under the condition that the standard deviation value is smaller than or equal to the second threshold value and larger than the average value of the first threshold value and the second threshold value; determining a fourth difference value according to the second threshold value and the first threshold value; determining a second value from the third difference and the fourth difference; and converting the corresponding waveform characteristic data into the second numerical value.
2. The pulse wave signal quality assessment method according to claim 1, wherein said determining a first value from said first difference and said second difference comprises:
performing proportional operation and square operation on the first difference value and the second difference value to obtain a first operation value;
and carrying out difference operation on the first operation value of which the value is one and two times to obtain the first value.
3. The pulse wave signal quality assessment method according to claim 2, wherein said determining a second value from said third difference and said fourth difference comprises:
performing proportional operation and square operation on the third difference value and the fourth difference value to obtain a second operation value;
and determining the second operation value which is doubled as the second numerical value.
4. A pulse wave signal quality evaluation device, characterized by comprising:
the filtering unit is used for carrying out band-pass filtering processing on the original pulse wave signals to obtain first pulse wave signals;
the wave crest detection unit is used for carrying out wave crest detection on the first pulse wave signal, determining the wave crest position and the initial position in the first pulse wave signal and obtaining first detection data;
the characteristic extraction unit is used for carrying out waveform characteristic extraction according to the first detection data after caching the first detection data to obtain multiple waveform characteristic data, wherein the multiple waveform characteristic data comprise the initial position, the peak amplitude, the adjacent peak interval, the contraction time and the relaxation time of pulse waves;
the quality score conversion unit is used for carrying out normalization processing on the multiple wave form characteristic data to obtain first data, and carrying out quality score conversion on the first data to obtain the quality score;
the normalization processing is performed on the multiple waveform characteristic data to obtain first data, and the method comprises the following steps:
standard deviation calculation is carried out on the waveform characteristic data to obtain standard deviation values;
converting the corresponding waveform characteristic data into a value one under the condition that the standard deviation value is smaller than or equal to a first threshold value;
converting corresponding waveform characteristic data to a numerical value of zero if the standard deviation value is greater than a second threshold value, wherein the second threshold value is greater than the first threshold value;
determining a first difference value according to the standard deviation value and a first threshold value under the condition that the standard deviation value is larger than the first threshold value and smaller than or equal to the average value of the first threshold value and the second threshold value; determining a second difference value according to a second threshold value and the first threshold value; determining a first value from the first difference and the second difference; converting the corresponding waveform characteristic data into the first numerical value;
determining a third difference value according to the standard deviation value and a second threshold value under the condition that the standard deviation value is smaller than or equal to the second threshold value and larger than the average value of the first threshold value and the second threshold value; determining a fourth difference value according to the second threshold value and the first threshold value; determining a second value from the third difference and the fourth difference; and converting the corresponding waveform characteristic data into the second numerical value.
5. A pulse wave signal quality assessment device comprising a processor, characterized in that the processor is adapted to perform the pulse wave signal quality assessment method of any one of claims 1 to 3.
6. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the pulse wave signal quality evaluation method according to any one of claims 1 to 3.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102270264A (en) * | 2010-06-04 | 2011-12-07 | 中国科学院深圳先进技术研究院 | Physiological signal quality evaluation system and method |
| CN103169456A (en) * | 2013-03-29 | 2013-06-26 | 深圳职业技术学院 | Processing method and processing system for pulse wave signals |
| CN104706337A (en) * | 2015-02-11 | 2015-06-17 | 华东师范大学 | Automatic pulse wave crest and trough detection method |
| WO2019062595A1 (en) * | 2017-09-30 | 2019-04-04 | 深圳市岩尚科技有限公司 | Method for quality evaluation of photoplethysmogram |
| CN110464321A (en) * | 2018-07-25 | 2019-11-19 | 北京动亮健康科技有限公司 | A kind of mass analysis method of arterial pulse waveform, device and system |
| CN110974189A (en) * | 2019-10-25 | 2020-04-10 | 广州视源电子科技股份有限公司 | Method, device, equipment and system for detecting signal quality of pulse wave |
| CN112183354A (en) * | 2020-09-29 | 2021-01-05 | 上海中医药大学 | Single-period pulse wave signal quality evaluation method based on support vector machine |
-
2021
- 2021-09-30 CN CN202111169203.XA patent/CN113940637B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102270264A (en) * | 2010-06-04 | 2011-12-07 | 中国科学院深圳先进技术研究院 | Physiological signal quality evaluation system and method |
| CN103169456A (en) * | 2013-03-29 | 2013-06-26 | 深圳职业技术学院 | Processing method and processing system for pulse wave signals |
| CN104706337A (en) * | 2015-02-11 | 2015-06-17 | 华东师范大学 | Automatic pulse wave crest and trough detection method |
| WO2019062595A1 (en) * | 2017-09-30 | 2019-04-04 | 深圳市岩尚科技有限公司 | Method for quality evaluation of photoplethysmogram |
| CN109598180A (en) * | 2017-09-30 | 2019-04-09 | 深圳市岩尚科技有限公司 | The method for evaluating quality of photoplethysmographic |
| CN110464321A (en) * | 2018-07-25 | 2019-11-19 | 北京动亮健康科技有限公司 | A kind of mass analysis method of arterial pulse waveform, device and system |
| CN110974189A (en) * | 2019-10-25 | 2020-04-10 | 广州视源电子科技股份有限公司 | Method, device, equipment and system for detecting signal quality of pulse wave |
| CN112183354A (en) * | 2020-09-29 | 2021-01-05 | 上海中医药大学 | Single-period pulse wave signal quality evaluation method based on support vector machine |
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