CN110827940A - Health data management method based on wearable equipment - Google Patents
Health data management method based on wearable equipment Download PDFInfo
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- CN110827940A CN110827940A CN201911060362.9A CN201911060362A CN110827940A CN 110827940 A CN110827940 A CN 110827940A CN 201911060362 A CN201911060362 A CN 201911060362A CN 110827940 A CN110827940 A CN 110827940A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- 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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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention relates to a health data management method based on wearable equipment, which comprises the steps of monitoring health data of a user through a plurality of wearable equipment, sending the health data to a cloud server for storage through a smart phone carried by the user, encrypting the health data by the smart phone in a time-sharing mode, sending a corresponding time-sharing key to the cloud server when a possible abnormal condition is found, decrypting the corresponding time-sharing data by the cloud server, and analyzing and processing the corresponding time-sharing data. The method effectively monitors and stores the health data acquired by the user through the wearable device, can timely discover and report abnormal health conditions, and ensures the privacy requirements of the user on the health data.
Description
Technical Field
The invention belongs to the field of intelligent medical treatment, and particularly relates to a health data management method based on wearable equipment.
Background
Wearable devices are new intelligent electronic devices that have been developed in recent years, and may be worn directly on the body or integrated into the clothing or accessories of a user, and typical wearable devices include smartwatches, smartbands, smartglasses, and the like. The wearable device is not only a hardware device, but also realizes powerful functions through software support, data interaction and cloud interaction.
In the prior art, a powerful function provided by a wearable device is to monitor physical health data of a user, such as blood pressure, heart rate, blood oxygen, etc., and to issue a corresponding alarm when an abnormality is found. However, wearable devices in the prior art are all independently monitored, and alarm is given out based on analysis of self-monitoring data, so that the analysis is not comprehensive enough, and false alarm is easy to occur. In addition, the health data is used as personal privacy data and is not convenient to send to the cloud.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a health data management method based on a wearable device.
The technical scheme adopted by the invention is as follows:
a health data management method based on wearable equipment comprises the following steps:
step 100: the wearable devices simultaneously monitor the human health data of the user and establish communication connection with the smart phone;
step 200: the wearable devices send the monitored health data to the smart phone through the communication connection;
step 300: the smart phone encrypts the health data in time intervals and sends the encrypted health data to a cloud server for storage, wherein symmetric encryption is used for encryption, and encryption keys used in each time interval are different;
step 400: when any wearable device finds that monitored health data are abnormal, the wearable device immediately informs the smart phone;
step 500: after receiving the abnormal notification, the smart phone sends the keys of the current time period and a plurality of time periods before and after the current time period to the cloud server to request the cloud server to perform abnormal analysis;
step 600: and after receiving the abnormal analysis request, the cloud server decrypts and analyzes corresponding health data according to the received multiple keys, and if the abnormal data is determined by analysis, the cloud server sends an analysis result to the designated equipment or personnel.
Further, in the step 300, the step of generating the key for each period includes:
step 310: the smart phone randomly generates and stores a seed key K in advance;
step 320: the smart phone numbers time periods in sequence;
step 330: when the nth time interval is finished, the smart phone generates a Key Key of the time intervalnNamely: key (R)n＝Hash(K||n||Timestamp)；
The symbol | | | represents that the binary system representations of the two variables before and after are connected, n is the number of the time interval, Timestamp is the Timestamp of the current time, and Hash is a Hash function.
Further, in step 320, the smartphone numbers the time periods according to the sequence of the time periods, where the number of the first time period is 1, the numbers of the subsequent time periods are sequentially incremented, and the number of the nth time period is n.
Further, in step 320, the smartphone numbers the time periods according to the sequence of the time periods, where the number of the first time period is m, m is a random number, the numbers of the subsequent time periods are sequentially incremented, and the number of the nth time period is m + n.
Further, in step 330, different hash functions are selected according to the requirement of the key length.
Further, the smartphone maintains a time period counter that holds the number of the current time period, and automatically increments by one at the beginning of each time period.
Further, each wearable device has a wireless communication module for establishing wireless communication with the smartphone.
Further, the wireless communication module is a bluetooth communication module.
Further, in step 600, the cloud server first decrypts the received time period data, and then decrypts the data of the subsequent time period over time.
Further, in step 600, the cloud server sends the analysis result to an assigned mobile phone number through a short message, or sends the analysis result to a device owned by a family doctor assigned by the user.
The invention has the beneficial effects that: the health data acquired by the user through the wearable device can be effectively monitored and stored, abnormal health conditions can be timely found and reported, and the privacy requirement of the user on the health data is guaranteed.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, and are not to be considered limiting of the invention, in which:
FIG. 1 is a schematic diagram of a system environment in which the method of the present invention is applicable.
Detailed Description
The present invention will now be described in detail with reference to the drawings and specific embodiments, wherein the exemplary embodiments and descriptions are provided only for the purpose of illustrating the present invention and are not to be construed as limiting the present invention.
Referring to fig. 1, a wearable device system environment to which the embodiment of the present invention is applicable is shown, in which a plurality of wearable devices, smartphones, and cloud servers are included.
Wherein each wearable device may monitor one or more items of health data of the user, such as blood pressure, heart rate, blood oxygen, and the like. According to a preferred embodiment, the wearable device 1 monitors the first health data, the wearable device 2 monitors the second health data, and the wearable device 3 monitors the third health data. Each wearable device has a wireless communication module that can establish wireless communication with the smartphone and transmit monitored health data. The wireless communication module may be, for example, a bluetooth communication module.
The smartphone may collect health data sent by each wearable device, for example, obtain first health data, second health data, and third health data from three wearable devices, respectively. Therefore, the intelligent mobile phone can gather the health data monitored by all wearable devices, and therefore complete health monitoring data can be obtained.
Further, the smart phone can also perform corresponding processing on the obtained health data based on the method of the invention and upload the health data to the cloud server.
The cloud server is used for storing the received user health data, and can correspondingly analyze and process the health data based on the method provided by the invention.
Based on the system environment described above, the health data management method of the present invention will be described in detail below.
Step 100: a plurality of wearable devices monitor the human health data of the user simultaneously, and establish communication connection with the smart phone.
In particular, one user may wear multiple wearable devices simultaneously according to their particular needs. The existing wearable device can monitor a variety of human health data of a user, for example, blood pressure can be monitored using a smart watch, an electrocardiogram can be monitored using a wearable electrocardiograph, and the like.
The wearable device establishes a communication connection with the smartphone of the user while monitoring data, generally the connection is near field communication, typically using a bluetooth communication connection. Thus, users are generally required to carry a smartphone at the same time and do a bluetooth peer-to-peer task, for example, when first connecting. If the wearable device fails to connect to the corresponding smartphone, the wearable device may temporarily store recent data (the amount of data stored depending on its memory capacity) and periodically attempt to connect to the smartphone until the connection is successful.
Step 200: the wearable devices send the monitored health data to the smart phone through the communication connection.
Specifically, after monitoring the human health data, each wearable device sends the human health data monitored in the time to the smart phone at regular intervals. For example, every 10 seconds, the wearable device sends the smartphone with the human health data it monitored during the last 10 seconds.
Thus, corresponding to a plurality of wearable devices, the smart phone can collect a plurality of corresponding human health data, and each type of human health data collected by the smart phone is continuous human health data within a certain time under normal conditions. For example, wearable device 1 monitors blood pressure, wearable device 2 monitors heart rate, and the smartphone can acquire two continuous health data, blood pressure and heart rate.
Step 300: the smart phone encrypts the health data in time intervals and sends the encrypted health data to the cloud server for storage, wherein symmetric encryption is used for encryption, and encryption keys used in each time interval are different.
Generally, the health data belongs to private data of individuals, and users do not want to know the health data to outsiders under normal conditions, so the health data uploaded to the cloud server must be encrypted. However, in the event of a subsequent abnormality, the cloud server needs to be provided with the capability of decrypting a part of the data, and in this case, the server needs to be informed of the decrypted key. If only one key is used, the cloud server can decrypt all the health data of the user, which is contrary to the original purpose of encryption.
For the above reasons, the present invention adopts a time-division encryption method, and the length of each time interval is fixed and can be preset. For example, a time period is 1 minute, after the time period is over, the smart phone generates a key for the time period, encrypts all health data in the time period by using the key, and uploads the health data to the cloud server. Therefore, if the cloud server is required to decrypt the health data in a part of time intervals, the keys in the corresponding time intervals are only required to be sent to the cloud server. The cloud server can only decrypt the data in the corresponding time period according to the received key, but cannot decrypt all the data, so that the privacy requirement of the health data of the user is guaranteed.
However, if one key is generated every minute, the smart phone inevitably needs to store a large number of keys, and the smart phone usually has limited storage space, and storing a large number of keys brings a great burden to the smart phone, which causes a great deal of storage resource waste. Therefore, the present invention further provides a method for generating a time-share key, so that the smart phone does not need to store a large number of keys, which specifically includes:
step 310: the smart phone randomly generates and stores the seed key K in advance.
For security, the seed key K should have a sufficient length, and preferably, the seed key K has 1024 bits. The seed key is the basis for generating subsequent keys, so the smartphone should securely store the seed key.
Step 320: and the smart phone numbers time periods in sequence.
As described above, the smart phone encrypts the health data according to the time intervals and uploads the health data to the cloud server, so that the smart phone can number the time intervals according to the sequence of the time intervals. For example, the first upload data has a time slot number of 1, the subsequent time slots are sequentially incremented, and the nth time slot number is n. For increasing security, the first time interval may be numbered m, where m is a random number, and the nth time interval may be numbered m + n.
Step 330: when the nth time interval is finished, the smart phone generates a Key Key of the time intervalnNamely:
Keyn＝Hash(K||n||Timestamp)。
the symbol | | represents that binary representations of two variables before and after are connected, for example, assuming that K is 1024 bits, n is 8 bits, and timestamp is 64 bits, three numbers are connected to form a binary number with 1024+8+64 being 1096 bits.
Timestamp is a Timestamp of the current time, i.e., the end time of the nth period. The Hash is a Hash function, which can select different Hash algorithms according to the requirement of the key length. For example, if the required key length is 128 bits, then the MD5 algorithm may be used, and if the required key length is 256 bits, then the SHA-256 algorithm may be used.
Thus, through the steps 310 and 330, the smart phone can generate a key for any period of time, and encrypt the health data of the period of time using the key. The smart phone only needs to store the seed key K, the initial value m of the time period number (namely the first time period number), the initial time of the first time period and the length of the time period, and the key of any time period can be calculated, so that the storage requirement on the smart phone is reduced. In fact, the smartphone can maintain a time period counter that stores the number of the current time period, and automatically increments by one at the beginning of each time period, so that the number of the current time period can be directly obtained under most conditions without further calculation.
Step 400: when any wearable device finds that monitored health data is abnormal, the wearable device immediately informs the smart phone.
The invention requires that each wearable device has certain storage capacity and analysis capacity, can analyze the monitored health data, and can immediately inform the smart phone if the data is abnormal. However, the wearable device may only monitor one health data, the obtained data is not comprehensive, and the analysis capability is limited, so that a false alarm may occur, and a subsequent accurate and comprehensive analysis needs to be performed by the cloud server.
Step 500: after receiving the abnormal notification, the smart phone sends the keys of the current time period and a plurality of time periods before and after the current time period to the cloud server, and requests the cloud server to perform abnormal analysis.
Specifically, the smart phone may calculate the key of the current time period and a plurality of time periods before and after the current time period by using the same method as in step 310 and 330. For example, assuming that the current time interval number is n, the smart phone may calculate the keys of the first a time intervals and the second b time intervals, that is, the key sequence keyn-a，keyn-a+1，keyn-a+2，……，keyn，keyn+1，……，keyn+bA total of a + b +1 keys. And sends these keys to the cloud server. The values of a and b may be predefined in order to allow the cloud server to decrypt and analyze all health data for a continuous time。
Step 600: and after receiving the abnormal analysis request, the cloud server decrypts and analyzes corresponding health data according to the received multiple keys, and if the abnormal data is determined by analysis, the cloud server sends an analysis result to the designated equipment or personnel.
The keys received by the cloud server comprise keys of the current time period and a plurality of time periods before and after the current time period, and the cloud server can decrypt the received time period data firstly and then decrypt the data of the subsequent time period along with time. The time period data is analyzed based on specific conditions, the analysis can be carried out immediately, or the analysis can be carried out after all the data are decrypted.
Because the data obtained by the cloud server decryption include all the monitored health data, and the computing capability and the analysis capability of the cloud server are strong, all the health data can be analyzed according to the preset rule, and a relatively reliable analysis result is obtained.
Once the analysis result confirms that the abnormal health condition occurs, the cloud server may send the analysis result to a designated device or person, for example, send a short message to a designated mobile phone number, or send the analysis result to a family doctor designated by the user.
Through the steps of the method, the health data acquired by the user through the wearable device are effectively monitored and stored, abnormal health conditions can be found and reported in time, and the privacy requirement of the user on the health data is ensured.
The above description is only a preferred embodiment of the present invention, and all equivalent changes or modifications of the structure, characteristics and principles described in the present invention are included in the scope of the present invention.
Claims (10)
1. A health data management method based on wearable equipment is characterized by comprising the following steps:
step 100: the wearable devices simultaneously monitor the human health data of the user and establish communication connection with the smart phone;
step 200: the wearable devices send the monitored health data to the smart phone through the communication connection;
step 300: the smart phone encrypts the health data in time intervals and sends the encrypted health data to a cloud server for storage, wherein symmetric encryption is used for encryption, and encryption keys used in each time interval are different;
step 400: when any wearable device finds that monitored health data are abnormal, the wearable device immediately informs the smart phone;
step 500: after receiving the abnormal notification, the smart phone sends the keys of the current time period and a plurality of time periods before and after the current time period to the cloud server to request the cloud server to perform abnormal analysis;
step 600: and after receiving the abnormal analysis request, the cloud server decrypts and analyzes corresponding health data according to the received multiple keys, and if the abnormal data is determined by analysis, the cloud server sends an analysis result to the designated equipment or personnel.
2. The method of claim 1, wherein the step 300 of generating a key for each time interval comprises:
step 310: the smart phone randomly generates and stores a seed key K in advance;
step 320: the smart phone numbers time periods in sequence;
step 330: when the nth time interval is finished, the smart phone generates a Key Key of the time intervalnNamely: key (R)n＝Hash(K||n||Timestamp)；
The symbol | | | represents that the binary system representations of the two variables before and after are connected, n is the number of the time interval, Timestamp is the Timestamp of the current time, and Hash is a Hash function.
3. The method according to claim 2, wherein in step 320, the smartphone numbers the time periods according to the sequence of the time periods, the first time period number is 1, the subsequent time periods number sequentially increases, and the nth time period number is n.
4. The method according to claim 2, wherein in step 320, the smartphone numbers the time periods according to the sequence of the time periods, the first time period number is m, m is a random number, the subsequent time periods number increases in sequence, and the nth time period number is m + n.
5. The method according to any of claims 2-4, wherein in step 330, different hash functions are selected according to the requirement of key length.
6. The method of any of claims 2-5, wherein the smartphone maintains a time period counter that holds the current time period number, automatically incremented by one at the beginning of each time period.
7. The method of any of claims 1-6, wherein each wearable device has a wireless communication module for establishing wireless communication with a smartphone.
8. The method of claim 7, wherein the wireless communication module is a bluetooth communication module.
9. The method according to claim 1, wherein in step 600, the cloud server first decrypts the received time period data, and then decrypts the data of the subsequent time period with time.
10. The method according to claim 1, wherein in step 600, the cloud server sends the analysis result to a designated mobile phone number through a short message, or sends the analysis result to a device owned by a family doctor designated by the user.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117240870A (en) * | 2023-11-01 | 2023-12-15 | 广东壹健康健康产业集团股份有限公司 | Wearable device data synchronization method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102546655A (en) * | 2012-02-07 | 2012-07-04 | 中山爱科数字科技股份有限公司 | Secure transmission method for health information |
| CN105581786A (en) * | 2014-10-24 | 2016-05-18 | 无锡蓝阳谐波科技有限公司 | Health monitoring system |
| CN105812126A (en) * | 2016-05-19 | 2016-07-27 | 齐鲁工业大学 | Lightweight back-up and efficient restoration method of health block chain data encryption keys |
| CN107307855A (en) * | 2017-08-02 | 2017-11-03 | 沈阳东康智能科技有限公司 | Vehicular human health monitoring system and method based on wearable device |
| CN109938711A (en) * | 2019-04-23 | 2019-06-28 | 深圳傲智天下信息科技有限公司 | Health monitor method, system and computer readable storage medium |
-
2019
- 2019-11-01 CN CN201911060362.9A patent/CN110827940B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102546655A (en) * | 2012-02-07 | 2012-07-04 | 中山爱科数字科技股份有限公司 | Secure transmission method for health information |
| CN105581786A (en) * | 2014-10-24 | 2016-05-18 | 无锡蓝阳谐波科技有限公司 | Health monitoring system |
| CN105812126A (en) * | 2016-05-19 | 2016-07-27 | 齐鲁工业大学 | Lightweight back-up and efficient restoration method of health block chain data encryption keys |
| CN107307855A (en) * | 2017-08-02 | 2017-11-03 | 沈阳东康智能科技有限公司 | Vehicular human health monitoring system and method based on wearable device |
| CN109938711A (en) * | 2019-04-23 | 2019-06-28 | 深圳傲智天下信息科技有限公司 | Health monitor method, system and computer readable storage medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117240870A (en) * | 2023-11-01 | 2023-12-15 | 广东壹健康健康产业集团股份有限公司 | Wearable device data synchronization method |
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