CN111627550B - Health condition online monitoring system and monitoring method - Google Patents
Health condition online monitoring system and monitoring method Download PDFInfo
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
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- G—PHYSICS
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- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
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Abstract
The invention discloses a health condition on-line monitoring system and a health condition on-line monitoring method, which enable wearable terminal equipment to capture physical information of pulse of a monitored object; the terminal equipment converts the physical information into an electric signal, and the electric signal is amplified and/or filtered to form a clear pulse fluctuation signal; the pulse wave signal can be divided into a pulse section (T2) and a slow section (T1); the data of the flat segment and/or the data of the beating segment are transmitted to an external device. Wearable terminal equipment is through catching human pulse piezoelectricity signal to with pulse piezoelectricity signal conversion to the signal of telecommunication that can transmit. The refueling terminal equipment has the advantages of long endurance, small pressure of data transmission, high learning speed and low false alarm rate.
Description
Technical Field
The invention belongs to the field of medical health monitoring, and particularly relates to an online health condition monitoring system and a monitoring method.
Background
Schools, adult care institutions, and disciplinary institutions that operate a large number of population managers encounter great difficulty in observing the health and physical characteristics of individuals under their supervision. Disease and injury are persistent threats to their general health and safety when a group of individuals spend a significant amount of time approaching. Early detection of disease or injury in the initial stages can be difficult, especially for children and the elderly who are unable to recognize their own symptoms.
Prior art, such as publication No. CN104334075B, discloses a system, method and server for monitoring the health and safety of individuals in a crowd and sending an alarm notification when an abnormality is detected, comprising: the biometric data obtained from the individual is compared to a biometric model generated for the individual by computer learning methods. The biometric data may be collected by a wireless biometric sensor device that transmits the biometric data to a receiver device that relays the biometric data to a server. The biometric model may be maintained in a server and include: a nominal biometric parameter and a threshold biometric parameter for each individual based on biometric sensor data collected or analyzed over a period of time. The server may issue an alarm when the biometric data of the individual exceeds a threshold in the biometric model. The alert sent may depend on the nature of the anomaly, user settings, and past notification experience. The alarm may be escalated when there is no reply within a specified duration.
Disclosure of Invention
The invention aims to provide an online health condition monitoring method with long endurance, low pressure of transmitted data, high learning speed and low false alarm rate for terminal equipment.
The technical scheme adopted by the invention for realizing the purpose is as follows:
a health condition on-line monitoring method enables wearable terminal equipment to capture physical information of pulse of a monitored object; the terminal equipment converts the physical information into an electric signal, and the electric signal is amplified and/or filtered to form a clear pulse fluctuation signal; the pulse wave signal can be divided into a pulse section (T2) and a slow section (T1); the data of the flat segment and/or the data of the beating segment are transmitted to an external device. Wearable terminal equipment is through catching human pulse piezoelectricity signal to with pulse piezoelectricity signal conversion to the signal of telecommunication that can transmit. After amplification and filtering, the piezoelectric signal is used as a set of the whole period T, and due to the huge monitoring base number, under the condition that the pulsation section and the gentle section are not separated, the data volume is too large, cloud resources are wasted, and meanwhile, the learning of the pulse characteristics by a machine is not facilitated. After segmentation, invalid learning of background noise is reduced in the clustering learning process, and the efficiency of the cloud server can be improved. And the pulse fluctuation signals are divided and distributed in the terminal equipment, so that the load can be further dispersed, the energy consumption of wireless transmission is further reduced, and the battery endurance capacity during terminal monitoring is improved.
In order to further optimize the technical scheme, the technical measures adopted further comprise:
taking the highest value A of the pulse wave signalmaxTaking s more than 0.5AmaxObtaining an average value Aa; traverse the pulse fluctuation signal AnA isn+1Is greater than a threshold value AVAs the start of the pulse signal, An+1Is less than a threshold value AVThe start end and the end are made to be a pulse section (T2), and the adjacent pulse periods are made to be a gentle section (T1); a. theVIs 0.33 | Aa | to 0.26 | Aa | in a single unit. The pulse fluctuation signals are segmented and classified through a simple algorithm, and on the basis, unnecessary T1 segment transmission in the transmission process is reduced, and the power consumption of the terminal is greatly reduced. And after the screened signal pulse section (T2) is acquired by the cloud, the pulse section (T2) of each bound user is repeatedly learned through the cloud, and the newly uploaded pulse section of the user can be identified. A in the above rangeVSimple segmentation is carried out, the efficiency is high, and the algorithm is simple. Even if segmentation errors occur, the method has no influence on cloud learning recursion in the later period.
The external device binds and/or distinguishes the authorized user of the terminal device by learning and/or recognizing data of the beat segments (T2). When a user wears the terminal equipment newly, the terminal equipment needs to be kept connected with the cloud end, and after the cloud end learning is completed, the only binding relation between the terminal equipment and the user is established. Furthermore, after the new beat segment (T2) data arrives at the cloud, the cloud can identify whether it is the pulse of the bound user.
If the user is bound and the monitoring value (T) of T is abnormal, entering an alarm monitoring process and/or prompting manual intervention; if the user is not bound and the monitored value (T) is not life-threatening, only recording. The problem of cloud online system false alarm caused when the user artificially gives other people to play the terminal of trying is reduced, and monitoring resource consumption is reduced. In safety considerations, if the monitored value (T) reflects a life risk of the wearer, for example the monitored value indicates cardiac arrest; even if the user is not bound, the user still can be monitored normally by the terminal equipment, and the person is informed to cure the user.
The external device obtains the information of the pulse section (T2) through a quantizer to obtain the quantized amplitude
(ii) a Will be provided with
Using distribution functions
Modulation, where A is the value of the signal potential,
is the differential of the value of the signal potential. And through the modulation processing of the quantization amplitude, data preparation can be further prepared for the GMM model learning clustering.
The external device carries out recognition processing on the information of the modulated pulse section (T2) by adopting a Gaussian Mixture Model (GMM) and utilizes the maximum likelihood criterion to recognize; the similarity measure of the maximum likelihood criterion adopts the following algorithm:
The invention also provides a health condition online monitoring system for realizing the method, which comprises a cloud server and wearable terminal equipment capable of exchanging data with the cloud server, wherein the wearable terminal equipment comprises,
a sensor assembly for capturing physical information of a pulse of a monitored subject and outputting as a pulse wave signal;
the pre-amplification circuit is used for amplifying the electric signal of the physical information to the working condition of the filter circuit;
a filter circuit for filtering the received signal and a control circuit for controlling the filter circuit,
the secondary amplifying circuit is used for amplifying the signal processed by the filter circuit to the working condition of the trap circuit;
the trap circuit is used for eliminating power frequency interference;
the digital-to-analog conversion circuit, the singlechip and the communication module;
the singlechip is stored with a program for realizing the method of claim 1; the single-chip processor can divide the pulse wave signal into a pulse section (T2) and a slow section (T1).
The sensor assembly contains a piezoelectric sensor, a distance sensor and a temperature sensor. The distance sensor is used for judging whether the wearing state is achieved or not after combination. Different from the prior art such as a sports bracelet, the technology has the function of health monitoring and alarming, so when the heart rate signal cannot be monitored, whether the terminal is taken down or not needs to be determined in an auxiliary mode according to the temperature and distance signals. Otherwise, the false alarm is frequently sent, which is not favorable for the user experience and the coping pressure of the server and the working personnel.
The invention also discloses a storage medium which stores a program capable of realizing the health condition on-line monitoring method.
The wearable terminal equipment captures the physical information of the pulse of the monitored object; the terminal equipment converts the physical information into an electric signal, and the electric signal is amplified and/or filtered to form a clear pulse fluctuation signal; the pulse wave signal can be divided into a pulse section (T2) and a slow section (T1); the data of the flat segment and/or the data of the beating segment are transmitted to an external device. Therefore, the following beneficial effects are achieved: wearable terminal equipment is through catching human pulse piezoelectricity signal to with pulse piezoelectricity signal conversion to the signal of telecommunication that can transmit. After amplification and filtering, the piezoelectric signal is used as a set of the whole period T, and due to the huge monitoring base number, under the condition that the pulsation section and the gentle section are not separated, the data volume is too large, cloud resources are wasted, and meanwhile, the learning of the pulse characteristics by a machine is not facilitated. After segmentation, invalid learning of background noise is reduced in the clustering learning process, and the efficiency of the cloud server can be improved. And the pulse fluctuation signals are divided and distributed in the terminal equipment, so that the load can be further dispersed, the energy consumption of wireless transmission is further reduced, and the battery endurance capacity during terminal monitoring is improved. Therefore, the invention provides the health condition on-line monitoring system and the health condition on-line monitoring method which have the advantages of long endurance of the terminal equipment, small pressure of transmitted data, high learning speed and low false alarm rate.
Drawings
FIG. 1 is a schematic diagram of a terminal circuit module connection of a monitoring system according to the present invention;
FIG. 2 is a schematic diagram of signal filtering and segmentation according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating comparative recognition rates according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a conventional preamplifier circuit;
FIG. 5 is a diagram of a conventional filter circuit;
FIG. 6 is a schematic diagram of a two-stage amplifying circuit used in the embodiment of the present invention;
FIG. 7 is a schematic interface display diagram of a system according to an embodiment of the present invention.
Reference numerals are used.
Detailed Description
The technical solution of the present invention is further described in detail below with reference to the following detailed description and the accompanying drawings:
example 1:
a health condition on-line monitoring method enables wearable terminal equipment to capture physical information of pulse of a monitored object; the terminal equipment converts the physical information into an electric signal, and the electric signal is amplified and/or filtered to form a clear pulse fluctuation signal; the pulse wave signal can be divided into a pulse section (T2) and a slow section (T1); the data of the flat segment and/or the data of the beating segment are transmitted to an external device. Wearable terminal equipment is through catching human pulse piezoelectricity signal to with pulse piezoelectricity signal conversion to the signal of telecommunication that can transmit. After amplification and filtering, the piezoelectric signal is used as a set of the whole period T, and due to the huge monitoring base number, under the condition that the pulsation section and the gentle section are not separated, the data volume is too large, cloud resources are wasted, and meanwhile, the learning of the pulse characteristics by a machine is not facilitated. After segmentation, invalid learning of background noise is reduced in the clustering learning process, and the efficiency of the cloud server can be improved. And the pulse fluctuation signals are divided and distributed in the terminal equipment, so that the load can be further dispersed, the energy consumption of wireless transmission is further reduced, and the battery endurance capacity during terminal monitoring is improved.
In order to further optimize the technical scheme, the technical measures adopted further comprise:
taking the highest value A of the pulse wave signalmaxTaking s more than 0.5AmaxObtaining an average value Aa; traverse the pulse fluctuation signal AnA isn+1Is greater than a threshold value AVAs the start of the pulse signal, An+1Is less than a threshold value AVThe start end and the end are made to be a pulse section (T2), and the adjacent pulse periods are made to be a gentle section (T1); a. theVFrom 0.33 | Aa | to 0.26 | Aa | in the formula. The pulse fluctuation signals are segmented and classified through a simple algorithm, and on the basis, unnecessary T1 segment transmission in the transmission process is reduced, and the power consumption of the terminal is greatly reduced. And after the screened signal pulse section (T2) is acquired by the cloud, the pulse section (T2) of each bound user is repeatedly learned through the cloud, and the newly uploaded pulse section of the user can be identified. A in the above rangeVSimple segmentation is carried out, the efficiency is high, and the algorithm is simple. Even if segmentation errors occur, the method has no influence on cloud learning recursion in the later period.
The external device binds and/or distinguishes the authorized user of the terminal device by learning and/or recognizing data of the beat segments (T2). When a user wears the terminal equipment newly, the terminal equipment needs to be kept connected with the cloud end, and after the cloud end learning is completed, the only binding relation between the terminal equipment and the user is established. Furthermore, after the new beat segment (T2) data arrives at the cloud, the cloud can identify whether it is the pulse of the bound user.
If the user is bound and the monitoring value (T) of T is abnormal, entering an alarm monitoring process and/or prompting manual intervention; if the user is not bound and the monitored value (T) is not life-threatening, only recording. The problem of cloud online system false alarm caused when the user artificially gives other people to play the terminal of trying is reduced, and monitoring resource consumption is reduced. In safety considerations, if the monitored value (T) reflects a life risk of the wearer, for example the monitored value indicates cardiac arrest; even if the user is not bound, the user still can be monitored normally by the terminal equipment, and the person is informed to cure the user.
The external device obtains the information of the pulse section (T2) through a quantizer to obtain the quantized amplitude
(ii) a Will be provided with
Using distribution functions
Modulation, where A is the value of the signal potential,
is the differential of the value of the signal potential. And through the modulation processing of the quantization amplitude, data preparation can be further prepared for the GMM model learning clustering.
The external device carries out recognition processing on the information of the modulated pulse section (T2) by adopting a Gaussian Mixture Model (GMM) and utilizes the maximum likelihood criterion to recognize; the similarity measure of the maximum likelihood criterion adopts the following algorithm:
The embodiment also provides an online health condition monitoring system for implementing the method, which comprises a cloud server and wearable terminal equipment capable of exchanging data with the cloud server, wherein the wearable terminal equipment comprises,
a sensor assembly for capturing physical information of a pulse of a monitored subject and outputting as a pulse wave signal;
the pre-amplification circuit is used for amplifying the electric signal of the physical information to the working condition of the filter circuit;
a filter circuit for filtering the received signal and a control circuit for controlling the filter circuit,
the secondary amplifying circuit is used for amplifying the signal processed by the filter circuit to the working condition of the trap circuit;
the trap circuit is used for eliminating power frequency interference;
the digital-to-analog conversion circuit, the singlechip and the communication module;
the singlechip is stored with a program for realizing the method of claim 1; the single-chip processor can divide the pulse wave signal into a pulse section (T2) and a slow section (T1).
The sensor assembly contains a piezoelectric sensor, a distance sensor and a temperature sensor. The distance sensor is used for judging whether the wearing state is achieved or not after combination. Different from the prior art such as a sports bracelet, the technology has the function of health monitoring and alarming, so when the heart rate signal cannot be monitored, whether the terminal is taken down or not needs to be determined in an auxiliary mode according to the temperature and distance signals. Otherwise, the false alarm is frequently sent, which is not favorable for the user experience and the coping pressure of the server and the working personnel.
The embodiment also discloses a storage medium, which stores a program capable of realizing the health condition online monitoring method.
Example 2:
the conduction of pulse wave is embodied by heart sound signals, and after the steps of amplification, filtering, digital-to-analog conversion and the like, the noise caused by the body and the environment is filtered, and the specific identification can be carried out by utilizing a modern identification mode to be used as the identity identification of a user.
The wearable terminal equipment comprises the following circuit modules: the device comprises a sensor component (a piezoelectric sensor), a pre-amplification circuit, a filter circuit, a secondary amplification circuit, a trap circuit, a digital-to-analog conversion circuit, a single chip microcomputer and a Bluetooth module.
The piezoelectric sensor can acquire a human pulse signal and can also be a light-sensitive sensor. Is a prior art sensor. The pre-amplification circuit is used as a low-frequency amplifier for stably amplifying the signal obtained by the piezoelectric sensor, and preferably, the AD620 is used as an amplifier to be assisted with the existing peripheral circuit design. There are conventional amplification baseline drift suppression circuits in the figures. The purpose of the two-stage amplifying circuit is to amplify the filtered signal by about 100 to 1000 times so as to enter the working range of the digital-to-analog conversion circuit. The purpose of the trap circuit is to remove 50Hz power frequency interference. By combining the circuit modules, clear pulse wave signals can be obtained. After the pulse fluctuation signals are subjected to digital-to-analog conversion and then input into the single chip microcomputer to be compressed, the pulse fluctuation signals are transmitted to the Bluetooth module as required.
The specific method of compression processing is to find the period duration T of the pulse in the pulse fluctuation signal. The maximum value A of n potentialsnThe average value Aa is obtained. A is to ben+1Is greater than a threshold value AVAs the start of the pulse signal, An+1Is less than a threshold value AVLet the pulse period T2 be between the start end and the termination end, and T1 be between the pulse periods. A. theVFrom 0.33 | Aa | to 0.26 | Aa | in the formula. The code realization of the GMM model can refer to a voiceprint recognition robustness technology and application research thereof, and the invention refers to an amplifying circuit in the text. However, in the implementation process of the model, the signal approximation degree of the recognition object of the text is low, while the signal approximation degree of the research object of the invention is high, so that the algorithm model is greatly adjusted. And the invention does not report the processing of the electric signal segmentation. By comparing the present invention with the experimental method in this article, it can be seen from the comparison in fig. 3 (the curve shown in the upper part of the table in fig. 3 is the data change trend of this example 1), that the present technical solution has the advantage over the existing algorithm in the case of a large number of samples. By derivation and calculation of new distribution functions, using AVThe limiting mode of the method reduces the calculation burden of the terminal equipment, and the comprehensive performance of the whole system is better.
The single chip microcomputer assigns T1+ T2 to T, and the T is used as a heart rate period and transmitted to the cloud through the Bluetooth or WIFI module. According to a preset sampling time period, the single chip microcomputer periodically transmits the pulse fluctuation signal of T2 to the cloud end to serve as pulse characteristic identification data information.
When the terminal device monitors that T changes, the pulse fluctuation signal of T2 is transmitted to the cloud end, and the cloud end server judges whether authentication is a terminal binding user or not according to the learned data. And if the user is bound and the monitoring value of T is abnormal, entering an alarm monitoring process and prompting the manual intervention of a nursing staff. If the user is not bound and the monitored value is not life-threatening, only the record is made. The problem that false alarm of the cloud online system is caused when the user artificially gives other people to try the terminal is solved, and monitoring resource consumption is reduced.
The whole early warning monitoring platform system comprises:
1. the early warning monitoring platform is positioned at a cloud server (cloud end);
2. wearable terminal (device is not limited, wearable device can be a watch at present, and can also be many other similar devices, such as vest, insole, etc.): and the alarm function of automatically acquiring heart rate and blood pressure uploading data (exceeding normal values) in real time (uploading time can be adjusted as required, such as uploading data once in 20 minutes or 2 minutes).
Meanwhile, the function of automatically uploading data when the old man falls down and the alarm function can be integrated, and the function is an integrated function.
And a 24-hour off-line automatic data uploading alarm function (when the old is not started for 24 hours to update data, the old can automatically alarm to prevent sudden death of the old living alone). The Bluetooth communication handshake function can be automatically carried out between the equipment (so as to realize the management record of the service duration of service personnel and users); the function of utilizing various signal sources to carry out real-time positioning to help lost people to return is achieved; the function of one-key calling is provided; the function of answering the call is provided; various prompt display functions (weather, medication, events, etc.). One-key call-out to wearing equipment function of alarm receiving operator of early warning monitoring platform, and verification of various required service contents by time-on-line user
The early warning monitoring platform realizes the management functions of dispatching orders, receiving orders and the like of the service contents for the users by the offline service provider.
While the invention has been described in connection with a preferred embodiment, it is not intended to limit the invention, and it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the invention.
Claims (5)
1. A health condition on-line monitoring method is characterized in that:
enabling the wearable terminal equipment to capture physical information of the pulse of the monitored object;
the terminal equipment converts the physical information into an electric signal, and amplifies and/or filters the electric signal into a clear pulse fluctuation signal; enabling the pulse wave signal to be divided into a pulse section T2 and a flat section T1; transmitting the data of the gentle section and/or the data of the pulse section to an external device;
taking the highest value A of the pulse wave signalmaxTaking s more than 0.5AmaxObtaining an average value Aa; traversing the pulse wave signal AnA isn+1Is greater than a threshold value AVAs the start of the pulse signal, An+1Is less than a threshold value AVThe end of the pulse signal is a pulse section T2 between the start end and the end, and the adjacent pulse periods are gentleSegment T1; a is describedVFrom 0.33 | Aa | to 0.26 | Aa | in the formula;
the external device binds and/or distinguishes the authorized user of the terminal device by learning and/or recognizing the data of the beat segment T2;
the wearable terminal equipment comprises a single chip microcomputer, the single chip microcomputer assigns T1+ T2 to T, the T is used as a heart rate period, and the heart rate period is transmitted to the cloud end through a Bluetooth or WIFI module;
according to a preset sampling time period, the single chip microcomputer periodically transmits a pulse fluctuation signal of T2 to the cloud end to serve as pulse characteristic identification data information;
when the terminal device monitors that T changes, the pulse fluctuation signal of T2 is transmitted to the cloud end, and the cloud end server judges whether authentication is a terminal binding user or not according to the learned data.
2. The on-line health condition monitoring method as claimed in claim 1, wherein: if the user is bound and the monitoring value T of the T is abnormal, entering an alarm monitoring process and/or prompting manual intervention; if the user is not bound, and the monitored value T is not life-threatening, only the record is carried out.
3. The utility model provides a health condition on-line monitoring system, includes high in the clouds server, and can with the wearing formula terminal equipment of high in the clouds server exchange data, characterized by: for carrying out the method according to any one of claims 1-2;
the wearable terminal device comprises a plurality of wearable terminal devices,
a sensor assembly for capturing physical information of a pulse of a monitored subject and outputting as a pulse wave signal;
the pre-amplifying circuit is used for amplifying the electric signal of the physical information to the working condition of the filter circuit;
a filter circuit for filtering the received signal and a control circuit for controlling the filter circuit,
the secondary amplifying circuit amplifies the signal processed by the filter circuit to the working condition of the trap circuit;
the trap circuit is used for eliminating power frequency interference;
the digital-to-analog conversion circuit, the singlechip and the communication module;
the single chip microcomputer is stored with a program for realizing the method of claim 1; the single-chip processor can divide the pulse wave signal into a pulse section T2 and a slow section T1.
4. An on-line health monitoring system as claimed in claim 3, wherein: the sensor component comprises a piezoelectric sensor, a distance sensor and a temperature sensor.
5. A storage medium, characterized by: the medium stores a program that can implement the method of any one of claims 1-2.
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