CN113440109A - Human physiological parameter detection and monitoring system - Google Patents
Human physiological parameter detection and monitoring system Download PDFInfo
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- CN113440109A CN113440109A CN202110881332.5A CN202110881332A CN113440109A CN 113440109 A CN113440109 A CN 113440109A CN 202110881332 A CN202110881332 A CN 202110881332A CN 113440109 A CN113440109 A CN 113440109A
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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
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
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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
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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
- A61B5/117—Identification of persons
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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
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
Abstract
The invention relates to a human body physiological parameter detection and monitoring system, which comprises: the data acquisition module is used for acquiring and inputting human physiological parameters of a user in real time; the data processing and transmitting module is used for processing the acquired and recorded human physiological parameters, matching the identity information of the human physiological parameters and transmitting the processed human physiological parameter data in real time; and the monitoring center module is used for receiving the processed human physiological parameter data in real time, analyzing the human physiological parameters of the user and monitoring. The invention can display the data of the physiological parameters of the user in real time, when the acquired physiological parameters of the human body are abnormal, the monitoring center module can generate an automatic alarm signal, and simultaneously can transmit the acquired physiological parameters of the human body to a remote monitoring center or a server, so that the invention can help the user to predict the trend of the body health in medical treatment and carry out rehabilitation treatment.
Description
Technical Field
The invention relates to the technical field of physiological parameter monitoring, in particular to a human physiological parameter detecting and monitoring system.
Background
With the acceleration of the pace of social life, people's health conditions are not optimistic under the influence of bad life styles and environmental pollution. According to survey, only 5% of the population in the world really reaches the health standard, about 20% of patients needing treatment, and the rest of the large population is in a state between health and disease, namely a sub-health state.
In addition, China is gradually entering an aging society; according to the global report of the world health organization on aging and health, the aged people over 60 will account for one third of the total population by the middle of the 20 th century; in the next two decades, China is expected to be one of the countries with the fastest population aging speed, and since the last few years, the incidence rate of chronic diseases such as diabetes, hypertension and the like is continuously increased, so that the chronic diseases become one of the main diseases which harm the health and the life of people.
In the prior art, a monitoring system for multiple aspects of human physiological parameters is not perfect, continuous real-time detection for multiple people cannot be realized, and meanwhile, each human physiological parameter detection method has certain limit requirements on application environment and human states.
Disclosure of Invention
In order to overcome the technical defects in the prior art, the invention provides a human body physiological parameter detection and monitoring system, which can effectively solve the problems in the background art.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
the embodiment of the invention discloses a human body physiological parameter detection and monitoring system, which comprises:
the data acquisition module is used for acquiring and inputting human physiological parameters of a user in real time;
the data processing and transmitting module is used for processing the acquired and recorded human physiological parameters, matching the identity information of the human physiological parameters and transmitting the processed human physiological parameter data in real time;
and the monitoring center module is used for receiving the processed human physiological parameter data in real time, analyzing the human physiological parameters of the user and monitoring.
In any of the above schemes, preferably, the data acquisition module acquires human physiological parameters for the user through the sensor, and the human physiological parameters include a body temperature value, an ECG signal and a pulse signal.
In any of the above aspects, preferably, the data acquisition module includes:
the ZigBee module is used for finishing data centralized processing, information transceiving control, node communication, routing protocol and power consumption management of the whole node;
the sensor module is used for detecting and collecting human physiological parameters;
and the power supply module is used for providing energy for each module.
In any of the above schemes, preferably, the data processing and transmitting module performs identity matching on the human physiological parameter data by extracting features of the electrocardiosignals.
In any of the above schemes, preferably, the data processing and transmitting module includes a processing module, an identification module and a template library; when the users register, after the human physiological parameter data input by each user are processed by the processing module, a human physiological parameter template of each user is established, the human physiological parameter template of each user is stored in the template library, and when human physiological parameters of all users are detected and monitored, the human physiological parameter data acquired at the same time and the human physiological parameter templates in the template library are identified and judged by the identification module, so that identity matching of all the acquired human physiological parameter data is realized.
In any of the above schemes, preferably, the noise of the acquired ECG signal is removed, and the ECG signal after noise removal is preprocessed to obtain a processed QRS wave, where the preprocessing includes R peak detection and waveform segmentation; and further extracting and fusing time domain and frequency domain features of the preprocessed electrocardiosignals, and completing the electrocardio identity recognition through feature matching.
In any of the above aspects, it is preferable that the QRS wave is detected by:
carrying out difference operation on the preprocessed ECG signal x to obtain a signal y1，y1[n]＝x[n]-x[n-4]；
Will signal y1Transmitted to a low-pass filter to output a signal y2，
At y2Is determined to be a threshold value nthi+And nthf+To define the starting position of the time window, nthi+And nthf+The conditions are satisfied: y is2[n]＞Th,Th＝0.6max(y2[n])；
Setting a window W with the duration of 160ms, the starting point is set at the signal y2Middle threshold nthf+Corresponds to y within the duration corresponding to the window W2The maximum value found by the part of the adaptive search which is less than zero is the R point.
In any of the above schemes, preferably, the electrocardiographic signals extracted from the individuals are subjected to autocorrelation, discrete cosine transform, wavelet transform and discrete cosine transform to obtain fusion features as features of the classifier, the feature vector of each electrocardiographic signal obtained by feature extraction is a 1 × N-dimensional vector, the electrocardiographic signals are classified and identified by a K-nearest neighbor algorithm, and the measurement function is:
wherein X is a sample in the electrocardiosignal characteristic vector registration set, and Y is the characteristic vector of the electrocardiosignal of the person to be identified.
In any of the above embodiments, preferably, in the identification, an euclidean distance between the input feature vector of the electrocardiographic signal and the feature vector of the electrocardiographic signal in the template library is calculated, and the euclidean distance is closest to the euclidean distance between the input feature vector of the electrocardiographic signal and the feature vector of the electrocardiographic signal in the template library as the distance between the input feature vector of the electrocardiographic signal and the feature vector of the electrocardiographic signal in the template library is smaller.
In any of the above schemes, preferably, the monitoring center module includes a database for storing human physiological changes corresponding to each physiological parameter of a human body;
and the analysis module is used for analyzing the processed human physiological parameter data according to the data in the database, grading the human physiological parameter data which is beyond or below a normal range if the data is abnormal, converting the data and the historical data into a time-physiological parameter line graph, and adding a grade degree early warning in the time-physiological parameter line graph.
The prediction module is used for generating a human body physiological trend report for the user according to the time-physiological parameter line graph;
the output module is used for sending the acquired human physiological parameter data, the time-physiological parameter line graph and the human physiological trend report to the terminal and the user side;
and the alarm module is used for sending an alarm signal to the terminal when the human body physiological parameter data of the user is abnormal.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a human body physiological parameter detection and monitoring system which is used for acquiring and inputting human body physiological parameters of a user in real time through a data acquisition module; the data processing and transmitting module is used for processing the acquired and recorded human physiological parameters, matching the identity information of the human physiological parameters and transmitting the processed human physiological parameter data in real time; the monitoring center module is used for receiving the processed human physiological parameter data in real time, analyzing the human physiological parameters of the user and monitoring; the data of the physiological parameters of the user can be displayed in real time, a doctor or the user can judge the physical condition of the user through observation of the data of the physiological parameters of the human body, when the acquired physiological parameters of the human body are abnormal, the monitoring center module can generate an automatic alarm signal, and meanwhile, the acquired physiological parameters of the human body can be sent to a remote monitoring center or a server, so that the medical treatment can help the user to predict the trend of the physical health and carry out rehabilitation treatment.
Drawings
The drawings are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification.
FIG. 1 is a block diagram of a human physiological parameter detecting and monitoring system according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is 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.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element.
In the description of the present invention, it is to be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships illustrated in the drawings, and are used merely for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, are not to be construed as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
For better understanding of the above technical solutions, the technical solutions of the present invention will be described in detail below with reference to the drawings and the detailed description of the present invention.
The invention provides a human body physiological parameter detection and monitoring system, as shown in figure 1, the system comprises a data acquisition module, a data acquisition module and a data processing module, wherein the data acquisition module is used for acquiring and recording human body physiological parameters of a user in real time;
the data processing and transmitting module is used for processing the acquired and recorded human physiological parameters, matching the identity information of the human physiological parameters and transmitting the processed human physiological parameter data in real time;
and the monitoring center module is used for receiving the processed human physiological parameter data in real time, analyzing the human physiological parameters of the user and monitoring.
The data acquisition module acquires human physiological parameters of a user through a sensor, and the acquired human physiological parameter data comprises a body temperature value, an ECG signal and a pulse signal; the data acquisition module comprises a ZigBee module, a sensor module and a power supply module, and preferably, the ZigBee module takes a CC2530 chip integrating RF and MCU as a main device.
Further, the ZigBee module is used for finishing data centralized processing, information receiving and transmitting control, node communication, routing protocol and power consumption management of the whole node;
the sensor module is used for detecting and collecting human physiological parameters;
and the power supply module is used for providing energy for each module.
Furthermore, the user carries the ZigBee node, namely the small portable physiological parameter monitoring device, physiological parameters of the body such as body temperature, heart rate and pulse are accurately monitored in real time, measured data are sent to the router nodes in the ZigBee network in a wireless mode, then data of all the router nodes or data of the terminal nodes are sent to the coordinator, and the data are transmitted in a wireless mode.
The data on the coordinator is sent to the monitoring center module in a serial port mode, the data of the physiological parameters of the user are displayed in real time, and a doctor or the user can judge the physical condition of the user by observing the data of the physiological parameters of the human body. When the acquired human physiological parameters are abnormal, the monitoring center module can generate automatic alarm signals, and meanwhile, the acquired human physiological parameter data can be sent to a remote monitoring center or a server, so that the medical treatment can help to predict the trend of the body health and help the user to carry out rehabilitation treatment.
In the human physiological parameter detection and monitoring system provided by this embodiment, because the characteristics of uniqueness, universality, durability and the like of the electrocardio signal can be accurately reflected, the identity can be identified by extracting the intrinsic characteristics of the electrocardio signal, such as waveform interval, amplitude and the like.
In a specific embodiment, each user needs to be registered, and the template human physiological parameters and the personal information of each user are input, so that a doctor or the user can judge the physical condition of the user through the continuous change of the human physiological parameters of the user to perform reasonable rehabilitation.
Further, the data processing and transmission module comprises a processing module, an identification module and a template library; when the users register, the data acquisition module is used for inputting the human physiological parameters of each user, the processing module is used for processing the human physiological parameter data input by each user, a human physiological parameter template of each user is established, the human physiological parameter template of each user is stored in the template library, and when all the users are subjected to human physiological parameter detection and monitoring, all the human physiological parameter data acquired at the same time are identified and judged with the human physiological parameter templates in the template library through the identification module, so that identity matching of all the acquired human physiological parameter data is realized.
Further, denoising the acquired ECG signal, and preprocessing the denoised ECG signal to obtain a processed QRS wave, wherein the preprocessing comprises R peak detection and waveform segmentation; and further extracting and fusing time domain and frequency domain features of the preprocessed electrocardiosignals, and completing the electrocardio identity recognition through feature matching.
During feature extraction, the QRS waves are respectively extracted to obtain the features of a time domain and a frequency domain, the QRS waves are subjected to autocorrelation change in the time domain, and time domain feature parameters are obtained through Discrete Cosine Transform (DCT); performing wavelet transformation on the QRS wave in a frequency domain, and obtaining frequency domain characteristic parameters through discrete cosine transformation; the two characteristic parameters are fused into a group of characteristic vectors, the fused characteristic vectors are used as the characteristics of the electrocardiosignals to be stored in a database, and then the electrocardio identity identification can be completed through a nearest neighbor classifier.
The QRS wave energy in the electrocardiosignals is mainly concentrated at about 5HZ-30HZ bandwidth, so that the filter can retain necessary information for identity identification while filtering noise such as baseline drift, high-frequency noise and the like.
More specifically, because the electrocardiosignal has periodicity, each period comprises a P wave, a QRS wave, a T wave and other coincident waves, and the energy in the electrocardio waveform is mainly concentrated in the QRS wave, wherein the amplitude of the R wave is most obvious, so that the R wave in the electrocardiosignal can be detected first and then the QRS wave can be detected.
Furthermore, after the cardiac electrical signal is subjected to the operations of difference and low-pass filtering, two thresholds are determined to define a time period, so that the starting position of a constant window is located in the time period, so as to find the maximum value corresponding to the window in the original signal, namely the R point.
Further, the QRS wave is detected by the following method:
(1) carrying out difference operation on the preprocessed ECG signal x to obtain a signal y1，y1[n]＝x[n]-x[n-4]；
(2) Will signal y1Transmitted to a low-pass filter to output a signal y2，
(3) At y2Is determined to be a threshold value nthi+And nthf+To define the starting position of the time window, nthi+And nthf+The conditions are satisfied: y is2[n]＞Th,Th＝0.6max(y2[n])；
(4) Setting a window W with the duration of 160ms, the starting point is set at the signal y2Middle threshold nthf+Corresponds to y within the duration corresponding to the window W2The maximum value found by the part of the adaptive search which is less than zero is the R point.
Furthermore, the electrocardiosignals extracted from the individuals are subjected to autocorrelation, discrete cosine transform and wavelet transform and then discrete cosine transform to obtain fusion features as features of the classifier, the feature vector of each electrocardiosignal of the individual is a 1 x N-dimensional vector, classification and identification of the electrocardiosignals can be realized through a K-nearest neighbor algorithm, the optimal K is 1, and the measurement function is as follows:
In the human physiological parameter detecting and monitoring system provided by the embodiment, the monitoring center module includes a database for storing human physiological change conditions corresponding to each human physiological parameter;
and the analysis module is used for analyzing the processed human physiological parameter data according to the data in the database, grading the human physiological parameter data which is beyond or below a normal range if the data is abnormal, converting the data and historical data into a time-physiological parameter line graph, and adding grade degree early warning, such as yellow at a low level, orange at a middle level and red at a high level, into the time-physiological parameter line graph.
The prediction module is used for generating a human body physiological trend report for the user according to the time-physiological parameter line graph;
the output module is used for sending the acquired human physiological parameter data, the time-physiological parameter line graph and the human physiological trend report to the terminal and the user side;
and the alarm module is used for sending an alarm signal to the terminal when the human body physiological parameter data of the user is abnormal.
Further, after the human physiological parameter data of all users are processed and identity matched through the data processing and transmission module, the analysis module analyzes the human physiological parameter data of each user according to data in a database, if the human physiological parameter data of the users are abnormal, the analysis module grades the human physiological parameter data which are beyond or below a normal range, converts the data and historical data into a time-physiological parameter line graph, adds grade degree early warning in the time-physiological parameter line graph, and then the prediction module can generate a human physiological trend report for the users according to the time-physiological parameter line graph; and the alarm signal, the human physiological parameter data, the time-physiological parameter line graph and the human physiological trend are reported to the terminal through the alarm module and the output module, so that the human physiological parameters of each user can be monitored in real time, and the user is helped to carry out rehabilitation treatment.
Compared with the prior art, the human body physiological parameter detection and monitoring system provided by the invention has the beneficial effects that:
the invention provides a human body physiological parameter detection and monitoring system which is used for acquiring and inputting human body physiological parameters of a user in real time through a data acquisition module; the data processing and transmitting module is used for processing the acquired and recorded human physiological parameters, matching the identity information of the human physiological parameters and transmitting the processed human physiological parameter data in real time; the monitoring center module is used for receiving the processed human physiological parameter data in real time, analyzing the human physiological parameters of the user and monitoring; the data of the physiological parameters of the user can be displayed in real time, a doctor or the user can judge the physical condition of the user through observation of the data of the physiological parameters of the human body, when the acquired physiological parameters of the human body are abnormal, the monitoring center module can generate an automatic alarm signal, and meanwhile, the acquired physiological parameters of the human body can be sent to a remote monitoring center or a server, so that the medical treatment can help the user to predict the trend of the physical health and carry out rehabilitation treatment.
Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that various changes, modifications and substitutions can be made without departing from the spirit and scope of the invention as defined by the appended claims. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A human physiological parameter detection and monitoring system is characterized in that: the system comprises:
the data acquisition module is used for acquiring and inputting human physiological parameters of a user in real time;
the data processing and transmitting module is used for processing the acquired and recorded human physiological parameters, matching the identity information of the human physiological parameters and transmitting the processed human physiological parameter data in real time;
and the monitoring center module is used for receiving the processed human physiological parameter data in real time, analyzing the human physiological parameters of the user and monitoring.
2. The human physiological parameter detection and monitoring system of claim 1, wherein: the data acquisition module acquires human physiological parameters including a body temperature value, an ECG signal and a pulse signal for a user through a sensor.
3. The human physiological parameter detection and monitoring system of claim 2, wherein: the data acquisition module includes:
the ZigBee module is used for finishing data centralized processing, information receiving and transmitting control, node communication, routing protocol and power consumption management of the whole node;
the sensor module is used for detecting and collecting human physiological parameters;
and the power supply module is used for providing energy for each module.
4. The human physiological parameter detection and monitoring system of claim 3, wherein: the data processing and transmitting module performs identity matching on the human physiological parameter data by extracting the characteristics of the electrocardiosignals.
5. The human physiological parameter detection and monitoring system of claim 4, wherein: the data processing and transmitting module comprises a processing module, an identification module and a template library; when the users register, after the human physiological parameter data input by each user are processed by the processing module, a human physiological parameter template of each user is established, the human physiological parameter template of each user is stored in the template library, and when human physiological parameters of all users are detected and monitored, the human physiological parameter data acquired at the same time and the human physiological parameter templates in the template library are identified and judged by the identification module, so that identity matching of all the acquired human physiological parameter data is realized.
6. The human physiological parameter detection and monitoring system of claim 5, wherein: denoising the acquired ECG signal, and preprocessing the denoised ECG signal to obtain a processed QRS wave, wherein the preprocessing comprises R peak detection and waveform segmentation; and further extracting and fusing time domain and frequency domain features of the preprocessed electrocardiosignals, and completing the electrocardio identity recognition through feature matching.
7. The human physiological parameter detection and monitoring system of claim 6, wherein: the QRS wave is detected by the following method:
carrying out difference operation on the preprocessed ECG signal x to obtain a signal y1，y1[n]＝x[n]-x[n-4]；
Will signal y1Transmitted to a low-pass filter to output a signal y2，
At y2Is determined to be a threshold value nthi+And nthf+To define the starting position of the time window, nthi+And nthf+The conditions are satisfied: y is2[n]＞Th,Th＝0.6max(y2[n])；
Setting a window W with the duration of 160ms, the starting point is set at the signal y2Middle threshold nthf+Corresponds to y within the duration corresponding to the window W2The maximum value found by the part of the adaptive search which is less than zero is the R point.
8. The human physiological parameter detection and monitoring system of claim 7, wherein: extracting electrocardiosignals from individuals, performing autocorrelation, discrete cosine transform and wavelet transform and discrete cosine transform to obtain fusion features as features of a classifier, wherein a feature vector obtained by extracting the features of the electrocardiosignals of each individual is a 1 x N-dimensional vector, and performing classification and identification on the electrocardiosignals through a K-nearest neighbor algorithm, wherein a measurement function is as follows:
wherein X is a sample in the electrocardiosignal characteristic vector registration set, and Y is the characteristic vector of the electrocardiosignal of the person to be identified.
9. The human physiological parameter detection and monitoring system of claim 8, wherein: when the identity recognition is carried out, the Euclidean distance between the input electrocardiosignal characteristic vector and the electrocardiosignal characteristic vector in the template library is calculated, and the distance between the input electrocardiosignal characteristic vector and the electrocardiosignal characteristic vector in the template library is the closest when the distance between the input electrocardiosignal characteristic vector and the electrocardiosignal characteristic vector in the template library is smaller.
10. The human physiological parameter detection and monitoring system of claim 9, wherein: the monitoring center module comprises a database for storing human body physiological change conditions corresponding to various human body physiological parameters;
and the analysis module is used for analyzing the processed human physiological parameter data according to the data in the database, grading the human physiological parameter data which is beyond or below a normal range if the data is abnormal, converting the data and the historical data into a time-physiological parameter line graph, and adding a grade degree early warning in the time-physiological parameter line graph.
The prediction module is used for generating a human body physiological trend report for the user according to the time-physiological parameter line graph;
the output module is used for sending the acquired human physiological parameter data, the time-physiological parameter line graph and the human physiological trend report to the terminal and the user side;
and the alarm module is used for sending an alarm signal to the terminal when the human body physiological parameter data of the user is abnormal.
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