JP7438068B2 - Dehydration state management system and dehydration state management method - Google Patents

Description

Application of Article 30, Paragraph 2 of the Patent Act Presented at the Bio4Apps 2019 International Conference held from December 18th to 20th, 2019

The present invention relates to a dehydration state management system and a dehydration state management method for managing the dehydration state of a person to be managed.

In recent years, with global warming, the number of patients suffering from heat stroke in the summer tends to increase. In particular, construction site workers are likely to sweat a lot and become dehydrated because they work outdoors in hot environments.

Therefore, as disclosed in Patent Document 1, the WBGT (Wet bulb globe temperature) value, which is an index for managing the risk of heat stroke, is measured at the work place, and based on the measurement, the on-site The health of workers is managed by notifying them of the risk of heat stroke on their mobile devices.

Further, Patent Document 2 discloses a method for individually evaluating heatstroke risk by measuring biological indicators such as blood hemoglobin concentration, cardiac output, and core body temperature. On the other hand, as disclosed in Patent Documents 3 and 4, a liquid flow rate such as blood flow rate can be measured by emitting a laser beam to a measurement target site and receiving the scattered light. Measuring devices are known.

JP2020-79732A JP2020-65641A International Publication No. 2017/208645 International Publication No. 2015/199159

However, biological indicators such as blood pressure and heart rate are not suitable for detecting the initial state of dehydration, and other indicators are required to detect dehydration in the initial state. On the other hand, it is known that dehydration can be prevented by water supply.

Therefore, the present invention provides a dehydration state management system and a dehydration state management method that can accurately estimate the dehydration state of a person to be managed and perform quantitative health management, taking into account the amount of water supplied. It is an object.

In order to achieve the above object, the dehydration state management system of the present invention is a dehydration state management system that manages the dehydration state of a person to be managed, and includes a blood flow measuring device that measures the blood flow rate of the person to be managed; A water supply device having a storage unit that stores blood flow data measured by the blood flow measurement device in association with an identifier of the person to be managed, and a communication function that is associated with the identifier that can measure the amount of water supplied by the person to be managed. an environmental state acquisition unit that obtains the environmental state of the place where the person to be managed stays; a communication terminal carried by the person to be managed; The present invention is characterized by comprising an estimation processing unit that estimates the dehydration state of the person to be managed and controls notification to the communication terminal based on the estimation result of the dehydration state.

Here, it is preferable that the blood flow measuring device be attached to the body of the person to be managed. Further, the notification to the communication terminal is configured to be performed when it is determined that water supply by the water supply device is necessary based on the estimation result of the dehydration state, and to be continued until water supply by the water supply device is performed. be able to.

Further, the invention of a dehydration state management method is a dehydration state management method for managing the dehydration state of a person to be managed, the method comprising: associating blood flow data obtained by measuring the blood flow rate of the person to be managed with an identifier of the person to be managed; a step of storing the environmental condition of the place where the person to be managed stays; and a step of detecting that the person to be managed has supplied water with a water supply device having a communication function associated with the identifier. , a step of estimating the dehydration state of the person to be managed from the blood flow data, the amount of water supplied by the water supply device, and the environmental condition; The method is characterized by comprising a step of notifying the user.

The dehydration state management system and the dehydration state management method of the present invention configured as described above store the blood flow data measured from the person to be managed, and also communicate the amount of water supplied by the water supply device carried by the person to be managed. It is structured so that it can be understood by function.

Then, the dehydration state of the person to be managed is estimated from the blood flow data, water supply amount, and the environmental condition of the place where the person to be managed is staying, and a notification is sent to the communication terminal carried by the person to be managed based on the estimation result. be exposed.

Therefore, the state of dehydration can be accurately estimated after taking into consideration the amount of water consumed by the person to be managed. Furthermore, the health of the person to be managed can be managed based on the quantitatively estimated dehydration state such as the dehydration rate. In particular, by using blood flow data, it is now possible to detect even mild dehydration symptoms, and from the perspective of preventing the onset of symptoms, it is possible to understand the possibility of dehydration even when the symptoms are mild, and to notify the user to drink water. You will be able to take measures such as:

FIG. 1 is a block diagram illustrating the configuration of a dehydration state management system according to the present embodiment. FIG. 1 is an explanatory diagram conceptually showing a dehydration state management system according to the present embodiment. It is a flowchart explaining the flow of the measurement process of the water supply amount by a water supply apparatus. It is a flowchart explaining the flow of processing for constructing an estimator. FIG. 3 is an explanatory diagram of a method of noise removal using measured blood flow data. It is a flowchart explaining the process flow of the dehydration state management method of this embodiment.

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram for explaining the configuration of a dehydration state management system 1 according to the present embodiment. Further, FIG. 2 is an explanatory diagram conceptually showing the dehydration state management system 1.

For example, as shown in FIG. 2, the dehydration state management system 1 of the present embodiment is managed by a construction manager, a site supervisor, etc. located at an office P2, etc., with workers working at a construction site P1 as management targets H1. This is a system for monitoring and managing the dehydration state of subject H1.

As shown in FIG. 1, the dehydration state management system 1 of this embodiment includes a measurement unit 2 that measures blood flow, etc., a storage unit 3 that stores measured blood flow data, etc., and a management subject H1. Mainly by a water supply device 4 that can measure the amount of water supplied, an environmental state acquisition section 5 that acquires the environmental state of the place where the person to be managed H1 stays, and an estimation processing section 6 that estimates the dehydration state of the person to be managed H1. configured.

On the other hand, as a specific device for realizing the dehydration state management system 1 of the present embodiment described above, as shown in FIG. A cloud server CL for storing measured blood flow data, etc., a water bottle BT with a communication function that can measure the amount of water supplied, a smartphone SM serving as a communication terminal carried by the person to be managed H1, and management used by the administrator H2. Examples include personal terminal MP.

Hereinafter, details of each configuration of the dehydration state management system 1 of this embodiment will be sequentially explained. First, as shown in FIG. 1, the measurement unit 2 includes a blood flow sensor 21 serving as a blood flow measurement device, a temperature sensor 22 that measures the temperature of a measurement target site for measuring blood flow, and a blood flow sensor 21 and a management unit. It includes a pressure sensor 23 that measures the contact pressure with the measurement target site of the subject H1.

As shown in FIG. 2, the measurement unit 2 can be incorporated into a wearable terminal WT that can be attached to the body of the managed person H1, such as the wrist. In this case, the blood flow rate of the person to be managed H1 can be measured at regular time intervals or at arbitrary timing.

On the other hand, the measuring unit 2 can also be a stationary measuring instrument installed in the office P2 or the like. In this case, the person to be managed H1 can measure blood flow and the like before heading to the construction site P1 at the start of work or after a break.

The blood flow sensor 21 is a measuring device for measuring the blood flow of the human body serving as the managed person H1. A stationary measuring device measures, for example, the blood flow rate at a person's fingertips. The blood flow sensor 21 emits light from a light source to the measurement target site, receives the light scattered by the measurement target site, and measures the flow rate of blood flowing into the measurement target site based on information on the amount of received light.

As the light source of the blood flow sensor 21, for example, a vertical cavity surface emitting laser (VCSEL) can be used. Emitted light is emitted from the light emitting section toward the measurement target site by driving the laser drive circuit. The wavelength of the emitted light can be set to, for example, a wavelength of near-infrared light of 850 nm to 1300 nm.

The emitted light is reflected or scattered (hereinafter also simply referred to as "scattering") by the measurement target site to become scattered light. That is, the emitted light propagates in a substantially hemispherical shape while being repeatedly scattered by blood cells and tissues within the capillaries within the measurement target site within the living tissue of the person to be managed H1. Then, the emitted light is scattered by the measurement target site, and the scattered light is received by a light receiving element formed by a photodiode for blood flow measurement, and the scattered light is photoelectrically converted to generate a photodetection signal.

Here, the contact pressure between the blood flow sensor 21 and the measurement target site is measured by the pressure sensor 23. Then, from the detection information of the light receiving element, the blood flow rate of the measurement target site is calculated using Doppler shift. For example, a configuration may be adopted in which blood flow measurement is started when a contact pressure equal to or higher than a predetermined pressure (for example, 80 mmHg) is measured.

For example, in scattered light scattered by blood cells moving in a capillary at a measurement target site, a frequency shift occurs due to the Doppler effect that is proportional to the moving speed of the blood cells. The frequency difference (shift) between the scattered light from stationary tissues and the scattered light from moving blood cells is distributed in a band from about several hundred Hz to several tens of kHz.

Therefore, in the power spectrum of the beat signal caused by the interference of the scattered lights of both, the frequency shifted due to the Doppler effect corresponds to the velocity of the blood cells, and the power corresponds to the amount of blood cells. Since the blood flow is the sum of the products of the velocity of each blood cell and the number of blood cells, the blood flow can be calculated by multiplying the power spectrum of the beat signal by the frequency and integrating the result.

For example, frequency analysis (for example, FFT (Fast Fourier Transform) calculation) of the interference component of scattered light is performed on the detection information from the light receiving element. By deriving a spectral sequence of the beat signal through this frequency analysis, and multiplying and integrating each spectral sequence by a corresponding frequency, it is possible to derive the blood flow rate of the measurement target site. Further, the value of the blood flow rate derived in this way can also be corrected based on the temperature near the measurement target site measured by the temperature sensor 22.

When the measurement unit 2 starts measurement, a unique ID (identifier) serving as an identifier for the managed person H1 is acquired by inputting a barcode or QR code (registered trademark) through an input interface, or by key input.

The unique ID of the person to be managed H1 is registered in the dehydration state management system 1 in advance before measurement by the measurement unit 2. Further, a unique ID (identifier) serving as an identifier is attached to the water supply device 4, and the unique ID of the water supply device 4 is associated with the unique ID of the managed person H1 who carries it.

The blood flow data measured by the measurement unit 2 is transmitted to the cloud server CL serving as a storage unit in a state where it is associated (linked) with the unique ID of the person to be managed H1. When the measurement unit 2 is, for example, a wristband type wearable terminal WT, data can be transmitted to the cloud server CL using an application and a communication function installed in the wearable terminal body. In addition, an application that controls the wearable terminal WT is installed on a communication terminal such as a smartphone SM, a laptop computer, or a tablet terminal carried by the managed person H1, and data is sent from the smartphone SM etc. to the cloud server CL. You can also do that.

The water supply device 4 includes a container such as a bottle containing water, a detection unit 41 attached to the container, and a transmission processing unit 42 for transmitting data regarding the measured amount of water supply to the cloud server CL. There is.

For example, the water bottle BT shown in FIG. 2 includes a container portion and a detection section 41. For example, the detection unit 41 includes an acceleration sensor and a pressure sensor, and detects the number of events in which water is supplied by the water bottle BT from changes in the tilt of the water bottle BT and the weight of the water bottle BT. For example, a smart bottle described in Japanese Patent Publication No. 2020-515822 can be used as a water bottle BT.

This water bottle BT has a communication function. For example, short-range wireless communications such as Wi-Fi, Bluetooth (registered trademark), and ZigBee (registered trademark) can be used. For example, when the function of the transmission processing unit 42 is executed by the smartphone SM carried by the managed person H1, communication between the water bottle BT and the smartphone SM may be performed by short-range wireless communication.

On the other hand, when the transmission processing unit 42 is provided in the water bottle BT, the configuration is such that it can communicate with the cloud server CL using Wi-Fi, a carrier line, a 920MHz radio wave, or the like. Communication with the cloud server CL may be configured to go through an access point AP such as a wireless router installed at the construction site P1.

The flow of the process for measuring the amount of water supplied by the water supply device 4 will be described below with reference to the flowchart shown in FIG.
The water bottle BT carried by the person to be managed H1 is monitored for acceleration data detected by the detection unit 41 (step S1). That is, when the person to be managed H1 tilts the water bottle BT to drink water, an acceleration equal to or higher than the threshold value is detected (step S2).

In this way, the water supply event is detected by the detection unit 41, and the number of detections is incremented and held as the water supply counter number (step S3). Then, when the transmission interval time is reached in step S4, the unique ID and water supply counter number of the water bottle BT are transmitted to the smartphone SM in which the transmission processing unit 42 is installed via the wireless communication function of the water bottle BT (step S5 ).

In step S6, a callback indicating completion of reception is sent to the water bottle BT from the smartphone SM which has received the unique ID and water supply counter number of the water bottle BT, and the water supply counter of the detection unit 41 of the water bottle BT is reset to "0" (step S7).

The transmission processing unit 42 provided in the smartphone SM adds a time stamp to the unique ID and water counter number information received from the water bottle BT, and transmits the data to the cloud server CL at set time intervals.

As described above, the blood flow data and the data regarding the water supply amount are stored in the cloud server CL in a state where they are associated with the unique ID of the person to be managed H1. These stored data are used in the estimation processing section 6. The estimation processing unit 6 can be executed in the cloud server CL or a management server connected thereto, or can be executed by an application installed in the administrator terminal MP operated by the administrator H2.

The environmental state acquisition unit 5 acquires the environmental state of the construction site P1 where the managed person H1 stays. For example, an environmental measuring device capable of measuring a WBGT (Wet bulb globe temperature) value can be installed as the environmental state acquisition unit 5 at the construction site P1.

An environmental measuring device capable of measuring a WBGT value (heat index) is equipped with a sensor that measures temperature, relative humidity, and black bulb temperature. The process of determining the dry bulb temperature and wet bulb temperature from the temperature and relative humidity may be performed by the environmental state acquisition section 5 or the estimation processing section 6.

Furthermore, the environmental state acquisition unit 5 may be configured to obtain the environmental state of the construction site P1 from an external server such as that of the Ministry of the Environment, which is connected to the dehydration state management system 1 via a network such as the Internet. Furthermore, the external environment such as sunshine hours can also be acquired as an environmental state.

The estimation processing unit 6 estimates the dehydration state of the person to be managed H1 from the blood flow data, the water supply amount measured by the water supply device 4, and the environmental state acquired by the environmental state acquisition unit 5. Furthermore, based on the estimation result of the dehydration state, notifications to the smartphone SM, which is a communication terminal carried by the managed person H1, are controlled.

Specifically, the estimation processing section 6 includes a data aggregation section 61 that takes in various data necessary for estimating the dehydration state, a preprocessing section 62 that performs preprocessing on the acquired data as necessary, and a dehydration state. It mainly includes a state estimation section 63 and a notification control section 64 for notifying warnings and the like.

The data aggregation unit 61 unifies the measurement data regarding the managed person H1 by associating the unique ID of the managed person H1 measured by the measurement unit 2 with the unique ID of the water supply device 4.

In detail, the data aggregation unit 61 detects, for each managed person H1, measurement values such as blood flow rate, temperature, and pressure by each sensor of the measurement unit 2, and water supply information obtained by the water supply device 4 acquired at an arbitrary interval. Obtain the number of times and build a database. The constructed database can also be stored in the storage unit 3 until estimation is performed.

Furthermore, the data aggregation unit 61 acquires, via the environmental status acquisition unit 5, information regarding the environmental status such as the temperature, humidity, and WBGT value of the construction site P1 where the person to be managed H1 is working. Information regarding this environmental state is also unified by being linked to the unique ID of the managed person H1.

From the database constructed by the data aggregation unit 61 in this way, the dehydration rate, which is the body water content index of the person to be managed H1, is estimated. In estimating the dehydration rate, the preprocessing section 62 preprocesses input data.

The preprocessing unit 62 processes data determined to be abnormal values from the data acquired by the measurement unit 2 using a predetermined method to construct learning data for machine learning. For example, the preprocessing unit 62 generates preprocessed data by removing noise from the captured blood flow data.

At the start and end of blood flow measurement, noise is generated due to contact between the human body contact site and the sensor. Since this noise affects the estimation of the dehydration rate, the noise is removed using a binarization method using an index calculated from the measured data or flag processing using another sensor.

In filtering using the binarization method, for example, as shown in Figure 5, a moving average (moving average data) of an arbitrary interval is calculated for raw blood flow data, and areas that stand out as high values are estimated to be noise and removed. It's a method.

Flag processing using other sensors means, for example, that only the measured value of blood flow data is used when the contact pressure calculated from the detection information of the pressure sensor 23 exceeds a threshold and is detected for an arbitrary time. It's a method.

Further, noise in measurement of blood flow data can also be removed by signal processing using an unsupervised classification method such as Mahalanobis distance or abnormal value detection using a singular spectrum transformation method.

Then, if the total data length becomes less than 10 seconds or the continuous data becomes less than 5 seconds due to noise removal, the preprocessing unit 62 also performs a process of excluding the data from the measurement data.

Using the data collected in this way, an estimation model used to estimate the dehydration rate is constructed by machine learning. The estimation unit 63 constructs an estimation model and estimates the dehydration rate using the constructed estimation model. Once the estimation model is constructed, it may be updated at any timing as needed.

For example, construction of a data set when relearning a dehydration rate estimation model can be performed according to the process flow shown in the flowchart of FIG. 4.
First, in step S11, the unique ID of the managed person H1 is read.

In step S12, it is checked whether the dataset is already being constructed at this point, and if it is, the process moves to step S131, where the dataset being constructed is called up and copied.

On the other hand, when constructing a new data set, a new data set is created and duplicated in step S132. Then, information regarding the amount of water supply linked to the unique ID (water supply measuring device ID) of the water supply device 4 carried by the person to be managed H1 is imported into the data set copied in steps S131 and S132 (step S14). . Up to this point, the data aggregation unit 61 performs the processing.

Then, preprocessing of the captured data is performed by the preprocessing unit 62 (step S15). Next, it is determined whether to construct an estimation model for each unique ID of the managed person H1 or to integrate the entire model (step S16).

When building an estimation model by integrating all managed persons H1 managed by the administrator H2, all data are integrated in step S171. On the other hand, when constructing an estimation model for each managed person H1, a data set is constructed for each unique ID of the managed person H1. In this case, the health condition of each managed person H1, such as chronic disease, can be taken into account.

Relearning by the estimation unit 63 is performed when the accuracy of the dehydration rate estimation result obtained by estimation is determined to be low, and the estimation unit 63 performs relearning of the estimation model using the data set obtained after the introduction of the current estimation model. Executed to make corrections.

In relearning, the contribution rate of the parameters used in machine learning is reevaluated, and if a change is found from the default contribution rate, the contribution rate of each parameter is replaced with the corrected one. Ensemble learning using random forest, for example, can be used for learning and relearning by machine learning.

Ensemble learning is a method for building a classifier that performs highly accurate classification by integrating the classification results of multiple weak classifiers. Bagging, boosting, random forest, etc. are known as ensemble learning.

In random forest, multiple training datasets are created from a given dataset by sampling using the bootstrap method, and multiple weak classifiers, which are decision trees, are constructed from these multiple training datasets. Then, the final classification result is obtained by a majority vote of the results of the plurality of decision trees.

Specifically, a dehydration rate estimation model using ensemble learning is constructed as follows.
First, from the constructed dataset, 60% of the dataset size is extracted using the bootstrap method to create a total of 100 samples (teacher dataset).

Furthermore, when creating a regression tree (decision tree) from each sample by machine learning, the number N of features to be used is determined by the following formula and randomly selected from all the features.
N=log ₂ P+1
Here, P indicates the total number of features included in the sample. Furthermore, when performing machine learning, there is no limit to the depth of the regression tree.

The estimation unit 63 outputs the average value of the values estimated by each regression tree, which is the result of machine learning and relearning, as the calculation result of the dehydration rate estimation model. For example, the dehydration rate is calculated by correcting the value estimated from the blood flow data using the water supply amount and the WBGT value.

The dehydration rate is estimated based on blood flow data, but can be corrected based on the water supply amount and environmental conditions as described above. In addition to the WBGT value, the environmental conditions used for correction include sunshine hours and the like. Furthermore, if the dehydration rate at the end of the previous day's workday is compared with the dehydration rate at the start of the workday, and if the numerical values are not recoverable, the estimated dehydration rate can be corrected based on that.

The estimated value of the dehydration rate estimated by the estimation unit 63 is sent to the notification control unit 64. The notification control unit 64 controls the content to be displayed on the smartphone SM carried by the person to be managed H1 and the administrator terminal MP operated by the administrator H2, based on the estimated value of the dehydration rate obtained from the estimation unit 63.

For example, as shown in FIG. 2, the estimated result of the dehydration rate calculated by the estimation unit 63 is displayed on the smartphone SM or the administrator terminal MP, which serves as the output unit 7 for displaying notifications sent from the notification control unit 64. , are displayed as graphs, numerical values, etc. on screens SM1 and MP1.

In addition, since the risk rank of heat stroke changes depending on the magnitude of the dehydration rate value, a fixed phrase arbitrarily set according to the risk rank is displayed on the screen SM1 and MP1. You can also.

How the notification control unit 64 performs the notification can be set arbitrarily. For example, it is possible to arbitrarily set how the dehydration rate is divided into risk ranks, when to give water supply instructions, whether to use a warning sound, etc.

The notification control unit 64 may notify the managed person H1 by a notification method such as vibrating the wearable terminal WT worn by the managed person H1. Further, notifications to the smartphone SM carried by the person to be managed H1 can be sent by e-mail, push notification, etc. at arbitrary intervals.

At the manager terminal MP, all data related to the dehydration rate of the person to be managed H1 can be monitored at once. In addition to the notification automatically sent to the managed person H1 by the notification control unit 64, the administrator terminal MP sends an alert to encourage drinking water and breaks to any managed person H1. It can also be sent to H1 smartphone SM.

The smartphone SM or wearable terminal WT of the managed person H1 that has received the automatic notification from the notification control unit 64 or the notification from the administrator terminal MP continues to emit at least one vibration or buzzer sound until an improvement in the dehydration rate is confirmed. is issued as an alert.

Then, if the dehydration rate estimated by the measurement by the measurement unit 2 of the wearable terminal WT falls below the threshold, or if a measurement result indicating that water has been supplied by the water supply device 4 is received, the alert is automatically canceled. It is also possible to do this.

Next, the process flow of the dehydration state management method of this embodiment will be explained with reference to FIG.
First, in step S21, the measurement unit 2 is used to measure the blood flow rate of the person to be managed H1. If the measuring unit 2 is a stationary measuring instrument placed in an office P2 or the like, the person to be managed H1 may place his or her finger on the stationary measuring instrument for a certain period of time or more before heading to the construction site P1. Measure blood flow, temperature, and contact pressure. On the other hand, when the measurement unit 2 is incorporated in the wearable terminal WT, the blood flow rate, etc. of the person to be managed H1 is measured at an arbitrary set time interval (for example, once every 30 minutes).

At the construction site P1 where the person to be managed H1 works, environmental conditions such as the WBGT value are measured (step S22). The environmental status can be acquired by installing an environmental measuring device with a communication function at the construction site P1 and taking actual measurements, or it can be acquired from an external server such as the Ministry of the Environment based on the address of the construction site P1. can.

When the monitoring of the managed person H1 starts, the environmental condition of the construction site P1 and the dehydration status of all the managed persons H1 are displayed in graphs and numerical values on the screen MP1 of the administrator terminal MP in the office P2. be done. Further, a record of whether or not water has been supplied by the water bottle BT carried by the person to be managed H1 can also be displayed on the screen MP1 of the manager terminal MP.

The water supply amount in step S23 can be confirmed by acquiring the number of times (the number of water supply counters) that a water supply event has been performed by the water bottle BT as described above. In short, if the average water supply amount per water supply event is set, the water supply amount can be calculated from the number of water supply counters. Further, if the water bottle BT has a configuration in which a change in weight can be detected using a pressure sensor or the like, the amount of water supplied can be directly measured.

From the acquired information, the current state of dehydration of the person to be managed H1 can be estimated (step S24). In short, the estimation unit 63 of the estimation processing unit 6 calculates the dehydration rate of the person to be managed H1 using the acquired blood flow data, water supply amount, and environmental state information.

The dehydration rate estimated by the estimation unit 63 can be displayed as is on the screen MP1 of the manager terminal MP or the screen SM1 of the smartphone SM. On the other hand, if the notification control unit 64 determines that the risk of heat stroke is increasing based on the estimated dehydration rate, an alert notification is sent to the smartphone SM or wearable terminal WT (steps S25, S26). . The alert is also notified to the administrator terminal MP.

The managed person H1 who has received the alert promptly takes measures such as drinking water from the water supply device 4 or taking a break to cool down in order to prevent the occurrence of heat stroke. As a result, if the blood flow improves and recovery from the dehydration state is recognized, the person to be managed H1 returns to work and the dehydration state is monitored again.

Next, the operation of the dehydration state management system 1 and the dehydration state management method of this embodiment will be explained.
The dehydration state management system 1 and the dehydration state management method of the present embodiment configured as described above store the blood flow data measured from the person to be managed H1, and the water supply device carried by the person to be managed H1. The system is configured such that the amount of water supplied according to No. 4 can be grasped through the communication function.

Then, the dehydration state of the person to be managed H1 is estimated from the blood flow data, the water supply amount, and the information on the environmental condition of the construction site P1 where the person to be managed H1 is staying, and based on the estimation result, the person to be managed H1 carries. A notification is sent to the smartphone SM, wearable terminal WT, etc.

Therefore, the state of dehydration can be accurately estimated by taking into account the amount of water ingested by the person to be managed H1. Furthermore, the health of the person to be managed H1 can be managed based on the quantitatively estimated dehydration state such as the dehydration rate.

In particular, by using blood flow data, it is now possible to detect even mild dehydration symptoms, and from the perspective of preventing the onset of symptoms, it is possible to understand the possibility of heat stroke even when the symptoms are mild, and to notify the user to drink water. You will be able to take preventive measures such as:

In addition, by configuring an alert to be sent to the smartphone SM or wearable terminal WT carried by the person to be managed H1 until water is supplied by the water supply device 4, the person to be managed H1 can interrupt work and supply water. It is easier to carry out, and can be more effective in preventing heatstroke.

Although the embodiments of the present invention have been described above in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and design changes that do not depart from the gist of the present invention may be made. Included in invention.

For example, in the embodiment described above, the measurement unit 2 that measures the blood flow in the fingertips and wrist has been described, but the measurement unit 2 is not limited to this, and may also be used as the measurement unit 2 that measures the blood flow in the earlobe or neck. good. Furthermore, the wearable terminal WT may be configured to only receive alerts.

1: Dehydration state management system 21: Blood flow sensor (blood flow measuring device)
3: Storage unit 4: Water supply device 41: Detection unit 42: Transmission processing unit (communication function)
5: Environmental state acquisition unit 6: Estimation processing unit 63: Estimation unit 64: Notification control unit 7: Output unit (communication terminal)
H1: Person to be managed P1: Construction site (place to stay)
SM: Smartphone (communication terminal)
WT: Wearable terminal (blood flow measurement device)
CL: Cloud server (storage unit)

Claims (3)

A dehydration state management system for managing the dehydration state of a person to be managed,
a blood flow measuring device that measures the blood flow of the person to be managed;
a storage unit that stores blood flow data measured by the blood flow measurement device in association with an identifier of the managed person;
a water supply device having a communication function associated with the identifier capable of measuring the amount of water supplied by the person to be managed;
an environmental status acquisition unit that acquires the environmental status of a place where the managed person stays;
a communication terminal carried by the managed person;
an estimation processing unit that estimates a dehydration state of the person to be managed from the blood flow data, the amount of water supplied by the water supply device, and the environmental state, and controls notification to the communication terminal based on the estimation result of the dehydration state; Equipped with
The blood flow measurement device is in a form that is worn in contact with the body of the person to be managed, and the estimation processing unit removes noise caused by contact between the human body contact site and the sensor from the blood flow data. Generate preprocessed data by excluding data with a total data length of less than 10 seconds or continuous data of 5 seconds or less from the processed data, and use the preprocessed data as the blood flow data to determine the dehydration of the person to be managed. A dehydration state management system characterized by estimating the state . The notification to the communication terminal is performed when it is determined that water supply by the water supply device is necessary based on the estimation result of the dehydration state, and is continued until water supply by the water supply device is performed. The dehydration state management system according to claim 1. A dehydration state management method for managing the dehydration state of a person to be managed, the method comprising:
storing blood flow data obtained by measuring the blood flow of the person to be managed in association with an identifier of the person to be managed;
acquiring the environmental status of the place where the managed person stays;
detecting that the managed person has supplied water using a water supply device having a communication function associated with the identifier;
estimating the dehydration state of the person to be managed from the blood flow data, the amount of water supplied by the water supply device, and the environmental condition;
a step of notifying a communication terminal carried by the person to be managed based on the estimation result of the dehydration state,
The blood flow data is measured by contacting the body of the person to be managed, and when estimating the dehydration state of the person to be managed, the blood flow data is used to estimate the relationship between the human body contact site and the sensor. Generate preprocessed data by excluding data with a total data length of less than 10 seconds or continuous data of 5 seconds or less from data from which noise caused by contact has been removed, and use the preprocessed data to calculate the blood flow rate. A dehydration state management method characterized by performing estimation as data .