JP3886997B2 - Action status provision system - Google Patents

Description

  The present invention relates to a behavior status providing system using an exercise status transmission terminal, and more particularly to a system that provides behavior status data from an exercise status transmission terminal in an optimal manner to a monitoring center.

  In recent years, with the development of the Internet, various medical services are provided.

For example, a system in which the center grasps the position by interlocking a mobile phone and GPS, or a temperature sensor and a pulse sensor are periodically transmitted to the center in conjunction with the mobile phone, and the center is based on these information There is also a system to grasp the current health situation.

  As such a mobile phone, a “mobile phone with motion sensor” described in Japanese Patent Application Laid-Open No. 2002-272413 has been reported.

  The human situation is not just about temperature and number of nights. Exercising, sleeping, resting, exercising.

  This kind of human movement is acquired on the mobile terminal side, processed into predetermined data and displayed so that the user's situation can be understood on the mobile side, and the situation is also acquired at the center and provided to various monitoring centers. It is desirable to do.

In the present invention, a server of various centers and a user terminal device are connected to a health management data server via a communication network, and the health management data server collects and analyzes behavior status data from the user terminal device. It is an action situation provision system which transmits a result to the server of the various centers, and a user terminal device.
The user terminal device
It consists of a mobile phone and an exercise status transmission terminal worn on the arm,
The exercise status transmission terminal is
Equipped with acceleration sensor, angular velocity sensor,
The exercise status transmission terminal is
Means for sampling the data of these sensors, and determining the type of motion of the sampling data from the periodicity, size, direction, and frequency of the sampling data;
Exercise status data including the acquisition time of the sampling data, the type of exercise, the identification code of the user having the user terminal device, and the sampling data are collected at a preset time and the health management is performed by the mobile phone. Means for sending to the data server;
Is provided.
The health management data server
First storage means for storing the exercise status data from the user terminal device;
A second storage means for storing a behavior state form in a plurality of rectangular lattice areas in which a vertical axis indicates a percentage, a horizontal axis indicates a time axis for one day, and the time axis is divided in units of predetermined minutes;
Is provided.
Means for receiving and storing in the first storage means exercise status data transmitted from the exercise status transmission terminal via the mobile phone;
Data extraction means for separating and extracting the sampling data in predetermined minutes from the exercise status data stored in the first storage means;
Means for extracting an exercise type of each sampling data in the extracted sampling data for the predetermined unit;
Means for determining how long the sampling data corresponding to the extracted exercise type is; and
Means for determining the time ratio of the determined length of the sampling data corresponding to the extracted exercise type with respect to the percentage of the rectangular lattice region;
Means for defining the length ratio of the sampling data corresponding to the extracted exercise type in the second storage unit together with the exercise type of the data to obtain the user's exercise status graph information;
Means for transmitting the exercise status graph information stored in the second storage means to a server of the various centers;
The main point is that
In addition, a medical center server and a user terminal device are connected to the health management data server via a communication network, and the health management data server collects and analyzes behavior status data from the user terminal device, and the analysis result is It is an action situation provision system which transmits to the server of the various centers, and a user terminal device.
The user terminal device
It consists of a mobile phone and an exercise status transmission terminal worn on the arm,
The exercise status transmission terminal is
Equipped with acceleration sensor, angular velocity sensor,
The exercise status transmission terminal is
Means for sampling the data of these sensors, and determining the type of motion of the sampling data from the periodicity, size, direction, and frequency of the sampling data;
Exercise status data including the acquisition time of the sampling data, the type of exercise, the identification code of the user having the user terminal device, and the sampling data are collected at a preset time and the health management is performed by the mobile phone. Means for sending to the data server;
Is provided.
The health management data server
First storage means for storing the exercise status data from the user terminal device;
A second storage means in which action status forms are stored in a plurality of rectangular lattice areas in which a vertical axis indicates a percentage, a horizontal axis indicates a time axis for one day, and the time axis is divided in units of 15 minutes;
Third storage means for storing the user identification code, doctor code, diagnosis result information, and the address of the mobile phone in association with each other;
With
Means for receiving and storing in the first storage means exercise status data transmitted from the exercise status transmission terminal via the mobile phone;
Data extraction means for separating and extracting sampling data for 15 minutes from the accumulated exercise status data;
Action type determining means for extracting the exercise type of each sampling data in the extracted sampling data for 15 minutes;
Means for determining how long the sampling data corresponding to the extracted exercise type is; and
Means for determining the time ratio of the determined length of the sampling data corresponding to the extracted exercise type with respect to the percentage of the rectangular lattice region;
Means for defining the length ratio of the sampling data corresponding to the extracted exercise type together with the exercise type of the data to obtain the user's exercise status graph information;
When the doctor code, the user code, and the diagnosis result information are transmitted from the medical center server, the number of times of diagnosis is counted, and the count result, the doctor code, the diagnosis date, and the time together with the identification code of the user are counted. Means for storing in a third storage means;
Means for periodically collecting the number of diagnoses of diagnostic result information having the same doctor code, and sending the total number of diagnoses as the number of medical points together with the doctor code to the medical center server;
Means for converting the number of medical points into a monetary amount and transmitting the address to the mobile phone address of the user identification code;
Is provided.
The medical center server is
With display,
Receiving the user's exercise status graph information from the health management server and displaying it on the display unit;
Means for transmitting diagnostic result information on the input exercise status graph information of the user to the health management data server;
Means for receiving the number of medical points from the health management data server;
The main point is that

  As described above, according to the present invention, since the center side can grasp what line the user is currently doing in minute increments, the appropriate action information suitable for the user can be obtained. Can be sent to a mobile terminal.

  In addition, since a large number of terminal devices and servers of various monitoring centers are connected via a network, and exchanges with the terminal devices are collectively managed in the monitoring center, it is possible to determine whether the coping method is appropriate at a later date.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

(First embodiment)
FIG. 1 is a schematic configuration diagram of an action situation providing system using the exercise situation transmission terminal according to the first embodiment. The system according to the present embodiment includes a terminal device 13 including an exercise status transmission terminal 1 and a mobile phone 2 with a wireless adapter 3, which will be described later, a health management data server 5, a care center 6 (server), and a medical center 7 ( A server) and a bidirectional TV 8 (which may be a TV using a cable television network) are connected through a mobile phone network 15, the Internet 17, and a CATV network 16.

  Then, the health management data server 5 accumulates behavior status data Ai periodically transmitted from the terminal device 13 and compares it with past accumulated data Bi, similar behavior status data Ci (age, district, behavior type), and the like. Thus, the nursing center 6 or the medical center 7 is provided with exercise status data in a predetermined display format that allows the current status to be grasped at a glance.

  In addition, the health management data server 5 is connected to the CATV network 16 and transmits the determination result from the care center 6 or the medical center 7, attention information, and the like to the TV 8 that is a terminal device. An interface 9 for controlling bidirectional communication is connected to the TV 8. Further, the TV is controlled based on an instruction from the controller 10, and data is transmitted to the health management data server 5.

  Further, as shown in FIG. 1, the exercise status transmission terminal 1 has a shape similar to a wristwatch, and is attached to the wrist with an arm-wrapped band. Also, the exercise status transmission terminal 1 transmits the action identification information (acceleration, angular velocity, frequency analysis result data, exercise determination result, number of steps, energy consumption, etc.) and the number of steps, stride, pulse stay, heart rate, etc. by short-range wireless transmission. The data is periodically transmitted to the mobile phone 2 by the method. These pieces of information are collectively referred to as action situation data Ai (with an identification code). This regular time differs for each exercise status transmission terminal 1. For example, if A's exercise status transmission terminal 1 transmits at 10:10, B becomes 10:12.

  The mobile phone 2 transmits the exercise status information described above using the URL code of the health management data server 5.

  The health management data server 5 accumulates the behavior status data Ai, and determines the current status by comparing it with data for health judgment such as past accumulated data Bi and similar behavior status data Ci.

  For example, it is possible to determine the user of the district from the identification code of the exercise status information, compare it with the exercise status data of each user in the corresponding district, and display the comparison result in a predetermined form. The situation is judged by comparing with the user. The health management data server 5 has a web function.

  As shown in FIG. 1, the health management data server 5 includes at least a data extraction unit 25, an action type extraction unit 26, an action type ratio calculation unit 27, and an action pattern graphing unit 28. .

  The data extraction unit 25 separates and extracts, for example, 15 minutes of data each time the received behavior status data Ai is stored in the database.

  The behavior type determination unit 26 extracts the type of the behavior status data ai (15 minutes) extracted by the data extraction unit 25 and informs the behavior pattern graphing unit 28 and the behavior type ratio calculation unit 27.

  The behavior type ratio calculation unit 27 calculates the ratio of the type of the behavior status data ai with 15 minutes as 100%, and sends the calculation result to the behavior pattern graphing unit 28.

  The behavior pattern graphing unit 28 includes a memory in which the vertical axis is percentage and the horizontal axis is time (24 hours), and the ratio of the type of the behavior status data ai is displayed by color corresponding to the time axis and the percentage axis. .

  Next, the exercise status transmission terminal 1 will be described.

  The exercise status transmission terminal 1 according to the present embodiment has a shape similar to a wristwatch, and is worn on the wrist by an arm-wrapping band. In addition, at least a motion sensor and its operation circuit are built in. The motion sensor measures the acceleration and angular velocity in at least one direction relative to the inherent direction of the motion measuring device. The direction of the acceleration Gx to be measured is a direction corresponding to the vertical direction of the body (that is, the vertical direction, which is defined as the X axis) when the wearer stands and naturally lowers the arm toward the body. The direction of the measured angular velocity ωz corresponds to the natural rotation direction of the wrist around the left and right axis (Z axis) of the body when the arm is shaken in parallel with the side of the body. The output of the measured acceleration Gx and angular velocity ωz is variously processed and used for motion identification and energy consumption calculation. The final information may be immediately observed by the wrist device with the user, before the calculation or Data on the way may be wirelessly transferred to a fixed computer (or, for example, data for one day is collected and transferred by wire), and final information may be visualized and recorded by calculation on the fixed device side. .

  The main feature of the present invention is not the configuration or function sharing of the body side device or the external device, but an algorithm for obtaining necessary information from the acceleration Gx and the angular velocity ωz. The outline will be described below, and further detailed description will be given with reference to a flowchart showing the operation of the present embodiment.

  For the acceleration Gx and the angular velocity ωz, data obtained by sampling measured values at 10 to 100 Hz (for example, 20 or 50 Hz) is used. Further, as a quantity indicating the magnitude of the acceleration Gx or the angular velocity ωz, a sum of a predetermined number of absolute values or sum of squares of the sampled data is used.

(1) Identification of body action: If a certain degree of periodicity is found in the sampling data of acceleration Gx and angular velocity ωz, it is determined to be walking or running, and if no periodicity is recognized, it is determined to be other movement. Furthermore, walking and running can be distinguished by a remarkable difference in acceleration Gx. These actions are further divided into several levels depending on the amount of acceleration Gx or angular velocity ωz. In the case of walking or running, the number of steps can be counted from the periodicity of the data.

(2) Energy consumption in a short time: Based on a wide range of conventional research, the energy consumption per unit weight (kg) is shown as a “behavior-specific coefficient” for each type of behavior on the basis of men aged 20 to 29 years. It is given as 6A [Table 1]. (According to the Sports Science Committee of the Japan Physical Education Association.) Further, correction factors for subjects (users) of different ages and genders are given as shown in FIG. 6A [Table 1]. (According to the 4th revision “Japanese nutritional requirements”.) As a result, energy consumption (including basal metabolism) can be calculated if the type of action being performed is determined.

(3) Energy consumption for a long time: The energy consumption for a short time that changes with time may be integrated. Alternatively, the energy consumption is calculated by operating the motion sensor intermittently rather than constantly, and calculating the type and intensity of the action identified from the data during operation, for example, during an intermittent operation interval of several minutes to several tens of minutes. May be integrated.

  FIG. 2 is a flowchart of the measurement operation of an example of the embodiment of the motion measuring apparatus of the present invention, and FIGS. 3A and 3B show the operation of the flowchart of the part for performing energy calculation. In FIG. 2, in step S1, data such as stride, transmission time (hours, minutes, usage period) are input in advance according to the user's age, sex, weight, and purpose.

  When the power is turned on in step S2, the motion sensor and the measurement circuit start operating, and in step S3, a large number of Gx and ωz are measured at a predetermined timing. Next, in step S4, ωz is sampled at 20 Hz, for example, and a frequency analysis (by short time DFT) is performed to examine whether there is a frequency of 4 Hz or less every 0.1 Hz. This data is updated every 2 seconds. The frequency of walking is about 0.5 to 1.8 Hz. In step S5, the ratio between the average value a and the peak value b of the Gx data during the period is calculated.

  In step S6, periodicity is determined. When periodicity is not recognized or when b / a <7, it is assumed that there is no periodicity and the process moves to the branch A point in FIG. When the periodicity is clear and b / a ≧ 7, it is identified in step S7 that walking or running is being performed, and in step S8, twice the peak frequency of ωz × 2 seconds is counted as the number of steps in 2 seconds. (Note that the value of b / a = 7 used for the determination boundary is experimentally conveyed, and in this case, the value determined to be almost optimal in this case using the sum of absolute values for the data. In step S9, the number of steps is displayed (although it is delayed by 2 seconds) (for example, a maximum of 2 hours), and the change (for example, every 15 minutes or the number of steps accumulated every day) is stored and saved for several days. (Data may be transferred to an external computer.) Then, the process proceeds to the start point B of the energy calculation flow for running and walking.

  In FIG. 3A, in step S11, it is determined that the action is other than walking or running. In step S12, for example, the sum of squares (or the sum of absolute values) of data for 2 seconds sampled at 20 Hz of Gx is used. Classify non-periodic behaviors with mathematical formulas and determine behavior coefficients as shown. That is, if Gx <2, desk work (sitting), if 2 <Gx <6, light work (housework in the standing position), light exercise (sports) if 6 <Gx <16, intense exercise (sports) if 16 <Gx I reckon. A predetermined behavior coefficient is applied to each classified motion. The numerical values representing the magnitudes of Gx and ωz used here are the output voltage values of the measurement circuit used in this embodiment, and are the accelerations, angular velocities, or their absolute values (or the sum of squares). It should be noted that although there is a proportional relationship, it is not a value with those dynamic units.

  Next, in step S13, energy consumption is calculated by the equation (1).

Energy consumption [kcal] = coefficient by action [kcal / kg / min] × weight [kg] × time [minute] × correction coefficient In step S14, the energy consumption value is displayed and stored, and if necessary, data is stored in an external computer. This may be performed by wireless transfer (may be pre-calculation data).

For example, it may be appropriate to display the energy consumption value every 15 minutes or every day. When the data processing is completed, the process returns to the point C in step S4 in FIG. 2 from the end point C, and the next motion analysis is performed.

  In the case of running / walking, the classification is further performed in step S15 from the point B, and the behavior coefficient is determined respectively. That is, using the sum of squares of Gx and ωz (or the sum of absolute values), if Gx <8 and ωz <2.8, walk 1 and 2 if 8 <ωz <5, 5 <ωz <7.2. If so, walk 3; if 7.2 <ωz, then walk 1 if 4.8 <Gx <16, and travel 2 if Gx <16. In step 16, the energy consumption is calculated by the above-described equation using the behavior coefficient. The flow from the point D is sent to step S14 in FIG. 3A to display and hold data.

  Hereinafter, an example of a specific form of the embodiment of the motion measuring device of the present invention will be introduced with reference to FIGS. 4A, 4B and 5. FIG. 4A and 4B show an example of a motion measuring device, FIG. 4A is a partial plan view, and FIG. 4B is a cross-sectional view taken along line BB. The motion measuring device 30 has a substantially wristwatch shape, and can be worn on the wrist with a wrist-wrapping band 36. The motion sensor 31, the display device 32, the communication circuit module 33 with the external device, the battery 34 serving as a power source, and the operation switch 35 are shown as the main components. The motion measuring device 30 does not burden the user. It must be thin and small.

  The display device 32 is arranged in the widest representation corresponding to the display surface of the wristwatch when the visibility is emphasized. The motion sensor 31 is also arranged on the same plane and thus parallel to the display device 32. Since a thin display device 32 such as a liquid crystal display panel can be used, the motion sensor 31 must also be housed in a sufficiently thin package.

  The reason why the thin motion sensor 31 is arranged in parallel with the display device 32 is as follows. As described above, the optimal motion detection direction is linear motion in the vertical direction of the body with respect to acceleration, that is, the X direction shown in FIG. 4A, and rotation within a plane that includes both the vertical direction and longitudinal direction of the rotational angular velocity. (Ωz direction in the figure), that is, a rotational motion around the horizontal rotation axis (parallel to the Z axis in the drawing) that faces the left-right direction of the body. Suppose that the motion measuring device 30 is worn like a wristwatch so that the display surface is on the back side or the palm side of the wrist (this is the most natural and desirable), and when the upper body is upright and the elbow is naturally bent and stretched, its rotation Since the surface is parallel to the display surface of the motion measuring device 30, that is, the display device 32, if there is a thin angular velocity sensor having a rotation detection surface parallel to the widest surface, the motion sensor 31 including this is included in the display device. 32 is preferably arranged in parallel.

  FIG. 5 is a plan view showing the internal structure of an example of the motion sensor in the embodiment of the present invention. The structure of the motion sensor satisfies all the requirements regarding the shape, arrangement, and detection direction as described above. Reference numeral 40 denotes a thin box-shaped airtight (preferably vacuum) container from which a lid (a ceiling portion of the container) is removed to show the internal structure. Reference numeral 41 denotes a number of hermetic end pins penetrating the bottom of the container. Each pin is connected to each of the electrode film groups on the motion sensor vibrating body 50 by, for example, a wire bonding technique, but the electrode films and bonding wires are not shown. The motion sensor vibrating body 50 is formed from a single flat plate of piezoelectric material, and the acceleration sensor unit and the angular velocity sensor unit are integrated. The motion sensor vibrating body 50 is supported by fixing a fixed portion A52 (shaded portion) on the back surface of the total base 51 and a back surface of a small area fixing portion B64 (shaded portion) on a base (not shown) on the container 40 side. Has been.

  The angular velocity sensor portion is a so-called tripod warm-shaped portion, and is composed of an L-shaped outer leg A53, an outer leg B55, a middle leg C54, and a sound base 56 and a fulcrum 57, respectively. The outer leg A53 and the outer leg B55 are cantilevered like the normal bipedal sound, and are excited in the angular velocity measuring circuit so as to vibrate symmetrically with respect to the symmetry axis (not shown). The oscillation circuit) is excited with a constant amplitude. The middle leg C54 is not excited, but has a surface electrode (not shown) for detecting the deflection thereof. 58A, 58B, and 58C shown with hatching different from the fixed portion are each an additional mass, and consist of a thick metal plating layer applied to the tip of the leg in order to lower the natural frequency and equalize each other (middle leg C54). May be different from the natural frequency of both outer legs as appropriate).

  When the motion sensor 50 is rotated at an angular velocity ωz around the rotation direction parallel to the Z axis perpendicular to the paper surface, the Coriolis force proportional to the angular velocity acts on the outer vibrating legs. The direction is the longitudinal direction of the leg, and if a force toward the leg tip acts on the outer leg A53 at a certain moment, a force toward the base of the leg acts on the outer leg B55. The direction of the force changes sinusoidally in synchronism with the vibration of the leg and reverses periodically. The two forces are both parallel to each other and the eccentric direction of the additional mass is opposite to the axis of the outer leg, so that a couple is formed, the tuning fork base 56 is shaken, and a slight rotation around the fulcrum 57 Causes vibration.

The middle leg C54 vibrates with an amplitude proportional to the Coriolis force by sensing the vibration of the tuning fork base 56 caused by the moment due to the Coriolis force. The vibration voltage extracted by the detection electrode provided on the middle leg C54 is the angular velocity detection signal.

  The acceleration sensor portion of the motion sensor 50 is composed of a pair of parallel vibrating bars A and B and an additional mass. Bar A61, bar B62, which is a spring part, load mass 60 (consisting of a mass of a part of a large area material plate and a mass of a thick plating material applied to the surface), two support springs 63 (load mass 60 And a fixing portion B64 (a portion for supporting and fixing the load mass 60 so that the load mass 60 is not greatly displaced particularly in the X direction). The rods A61 and B62, which are fixed at both ends, are excited by an oscillation circuit (for example, included in the angular velocity measurement circuit 14 in FIG. 1) in an oscillating state symmetric with respect to the symmetry axis of the motion sensor 50.

  The oscillation frequency is usually constant, but when the acceleration Gx in the X direction shown in the figure acts on the load mass 60, the load mass 60 compresses or pulls the rod A61 and the rod B62 in the longitudinal direction with a force proportional to the magnitude. Thus, the oscillation frequency increases and decreases depending on the direction and magnitude of the force. Therefore, by comparing a separately provided reference frequency with the oscillation frequency and knowing the direction and amount of change in the oscillation frequency, the acceleration in the X-axis direction can be obtained. There is a possibility that the oscillation frequency of the outer legs A53 and B55, which are vibration bodies for the angular velocity sensor, can be used instead without providing a reference frequency source. The greatest advantage of this motion sensor is that it is thin and can be arranged parallel to the largest surface (display surface) of the wristwatch-type device to detect important Gx and ωz.

  Hereinafter, the validity and practicality of the concept of the present invention will be verified with reference to FIGS. 7 to 14 showing experimental results using the algorithm of the present invention.

  FIG. 7 is a graph showing the relationship between the sum of the absolute values of Gx and ωz of the motion of the subject P determined to be periodic, and FIG. 8 is the graph of Gx and the motion of the motion determined to be non-periodic performed by the same subject. It is a graph showing the relation of the sum of absolute values of ωz. From this, it can be said that the intensity of running and strong exercise can be classified by Gx, and the intensity of walking and other exercises can be classified by ωz.

  FIG. 9 is a graph showing the relationship between the walking and running speeds and the sum of the absolute values of ωz for five subjects P, Q, R, S, and T. It can be seen that the walking intensity is well proportional to ωz, and the walking speed (intensity) can be estimated by ωz. On the other hand, it is difficult to estimate the running speed at ωz. The reason seems to be to bend the elbow when driving.

  FIG. 10 is a graph showing the relationship between the walking and running speeds of the same subject and the sum of the absolute values of Gx. It can be seen that the traveling speed can be estimated by Gx.

  FIG. 11 is a graph showing the distribution of the sum of the absolute values of Gx and ωz when the subject P walks and runs at a speed almost specified. The data of the same speed is well organized, and it is shown that driving can be sufficiently classified by the size of Gx and walking can be sufficiently classified by the level of Gx and the size of ωz.

  FIG. 12 is a graph of similar data collected for the subject R. In this case, ωz is set to be small, and the walking speed is not successfully separated. When the behavior of the subject R was observed, it was found that there was a heel that turned the palm forward during walking, the orientation of the sensor of the wrist device was changed, and the correct ωz was not measured. This measure can be corrected by, for example, mounting the motion measuring device with a slight shift around the wrist. There are other methods, which will be described later. On the other hand, there is no problem in classification of traveling speed by Gx.

  FIG. 13 is a graph showing the result of identifying the exercise of the subject P for one day every 15 minutes. According to the present invention, it becomes possible to analyze the behavior of the user, and the usefulness is high.

  FIG. 14 is a graph showing fluctuations in energy consumption every 15 minutes for the subject P over one day. This also shows that the present invention is useful for grasping the energy consumption pattern of the user or the total energy consumption.

  FIG. 15 is a graph showing the change in the number of steps of the subject P over one day every 15 minutes. This figure also knows the user's behavior pattern, and can be used as a material for diagnosis and life improvement together with other graphs and data.

  It goes without saying that the embodiment of the present invention is not limited to what has been described above. For example, the direction of detection of acceleration and angular velocity is one axis (one direction) in the above-described embodiment, and this is a configuration in which the motion measuring device can be realized at the lowest cost. An ω sensor may be incorporated. In this case, there is an advantage that information for analyzing the motion increases. In addition, the absolute maximum and minimum values of acceleration and angular velocity can be calculated regardless of the orientation and direction of the measuring apparatus. Even if the direction to be detected by the user's heel deviates on the device as in the subject R in FIG. 11, for example, the maximum value from the angular velocity component in two directions (in the case of a wrist device, this occurs due to the rotation of the arm along the body side). Calculated).

  In addition, the motion sensor unit of the motion measurement device is attached to other than the wrist (upper arm, chest, waist, legs, etc.), and the measured values obtained from these are used alone or in association with the measured values at the wrist to achieve more advanced motion. Analysis can also be aimed at. For example, by attaching an angular velocity sensor to the leg, it may be easy to analyze the motion of the bicycle.

  In addition to the configuration in which the device to be worn on the arm has all the functions, the portion to be worn on the arm is limited to the sensor-related functions as much as possible to reduce the size and weight of the device and reduce the addition of the device. There may be a configuration in which the apparatus is divided into a device with a belt or the like, a mobile phone (having a necessary function), and the like, and the analysis result is displayed on the device or the data is transferred to the host computer. In this way, a certain degree of consideration for pacemaker users is possible.

  In addition to the above-described calculation function, a special case detection function can be provided to contribute to the safety of the user. For example, if acceleration or angular velocity is rarely detected for a predetermined time or if it operates at a loose frequency that is not normally considered, the user may have fainted, and if the user falls, the motion sensor may be temporarily abnormal ( For example, a shocking waveform). In addition, when the user requests emergency help, a signal may be sent by striking or shaking the device. In that case, it is desirable that the motion detection device transmits an emergency signal by sound generation or wirelessly. For sound generation, use the speaker attached to the device.For wireless communication, send a radio wave directly to the external device or send a rescue signal via a wireless device such as a mobile phone you have. It is possible to send. When the apparatus detects an abnormal value of acceleration or angular velocity, the rescue signal generation function is interrupted to the normal processing route as shown in FIGS.

(Description of operation)
Next, the operation of the system will be described below with reference to the sequence diagram of FIG. In the present embodiment, it is assumed that the user is exercising using the terminal device described above.

  Then, it is assumed that the regular transmission time has come (d1). When the regular transmission time is reached, the exercise status transmission terminal 1 transmits the URL code of the health management data server 5 and logs in to the site (d2).

  Next, the behavior status data Ai is transmitted to the health management data server 5, and the meal data of the day input by the user using the mobile phone 2 is transmitted (d3, d4).

The health management data server 5 receives the behavior status data Ai and the meal data, and stores them in a file (d5).

  The care center 6 accesses the health management data server 5 and requests various desired data (d6).

  The health management data server 5 decodes the request command (for example, totaling by exercise pattern, action pattern, number of steps for one day, number of steps for one month, etc.). In addition, each time the received behavior status data Ai is stored in the database, the data extraction unit 25 separates, for example, 15 minutes of data, and the behavior type determination unit 26 indicates the behavior indicated by the behavior status data ai (15 minutes). Is extracted as a type. Then, the behavior type ratio calculation unit 27 calculates the ratio of the behavior state data ai as a percentage, and sends the result to the behavior pattern graphing unit 28.

  The behavior pattern graphing unit 28 includes a memory in which the vertical axis is percentage and the horizontal axis is time (24 hours), and the ratio of the type of the behavior status data ai is displayed by color corresponding to the time axis and the percentage axis. .

  For example, as shown in FIG. 18, the behavior status data ai corresponding to the user name is read, and the status of the behavior type is displayed as a bar graph in a coordinate system in which percentage is assigned to the vertical axis and time is assigned to the horizontal axis.

  Further, in the case of requesting a behavior pattern for one month, as shown in FIG. 17, the past accumulated data of the user name is assigned, and these are separated into a predetermined period, and the behavior during that time is displayed by color in a pie chart.

  In addition, when requesting the number of steps for one month, the number of steps is assigned to the vertical axis and the date is assigned to the horizontal axis, as shown in FIG. In the coordinate system, the number of steps for each day is displayed as a bar graph.

  Furthermore, as shown in FIG. 20, when the number of steps is a day, the number of steps for each time is displayed as a bar graph in a coordinate system in which the number of steps is assigned to the vertical axis and the time is assigned to the horizontal axis.

When a daily action pattern is requested, as shown in FIG. 21A, a ratio according to the action type is displayed in a bar graph in a coordinate system composed of a time axis and a percentage axis. For example, red is displayed for intense sports, vermilion for light sports, amber for fast walking, and light blue for slow walking. Further, (b) of FIG. 21B shows details of the bar graph, and intense sports, light sports, standing work, etc. are shown on the upper side.

  Further, when the calorie consumption is requested, only the calorie value is extracted from the behavior situation data, and this is displayed on the coordinate system composed of the calorie axis and the date axis (see FIG. 22).

  Further, the screen is formed by comparing the target value and the personal situation in a graph, or by combining a bar graph and a pie graph.

  Such data is transmitted to the care center (d7). Therefore, in the care center, it is possible to grasp what action is being performed at a glance from the state of the graph displayed on the screen (FIGS. 17 to 22). Based on the grasped result, the person in charge of the care center operates the server terminal to send appropriate advice (person in charge code, date, partner user code, etc.) to the health management data server 5 (d8). ).

  The health management database server 5 stores and manages the advice and transmits (mails) it to the mobile phone 2 (d11). In this embodiment, since it is connected to the CATV network, the health management data server can transmit information such as advice and attention received to the user's TV (d12).

  Since the medical center is also connected to the Internet, the various screens described above are transmitted to the medical center at the request from the medical center (server), and the medical center provides appropriate advice to the health management database server 5. Is transmitted to the mobile phone 2 or the TV via (d10, d13, d14, d15, d16, d17).

  Note that (1) an i-mode specification mobile phone and (2) PHS may be used instead of the mobile phone 2 provided in the system of the first embodiment.

(1) In the system according to the first embodiment, the terminal device 13 is composed of the exercise status transmission terminal 1 and the mobile phone 2 with the wireless adapter 3, but the mobile phone 2 is one of character information services. It may be a mobile phone equipped with a mode specification.

  The i-mode is a character information service using a cellular phone. The cellular phone network 15 provides a provider function, can access i-mode dedicated sites and sites on the Internet, and also provides an Internet mail function.

  In this case, action status data Ai is transmitted from the exercise status transmission terminal 1 to the i-mode specification mobile phone with the wireless adapter 3, and further transmitted from the i-mode specification mobile phone to the health management data server 5. The health management data server 5 may receive the action status data Ai from the mobile phone 2 when the mobile phone 2 logs in to the web site specified by the URL code.

(2) In the system of the first embodiment, the terminal device 13 is composed of the exercise status transmission terminal 1 and the mobile phone 2 with the wireless adapter 3, but instead of the mobile phone 2, PHS (Personal Handy-phone System).

  The PHS is a simple mobile phone system based on a digital cordless telephone. The mobile phone has a radio frequency of 800 MHz, whereas the PHS uses a radio frequency of 1.9 GHz. Since the service area of one base station is smaller than that of a mobile phone because it uses weak radio waves, it is not suitable for making calls while moving at high speed. On the other hand, PHS has a feature that enables stable data transmission at a speed of about 30 kbps.

 In this case, the behavior status data Ai is transmitted from the exercise status transmission terminal 1 to the PHS with the wireless adapter 3 and further transmitted from the PHS to the health management data server 5.

  The health management data server 5 only has to receive the behavior status data Ai from the PHS when there is a login from the PHS to the web site specified by the URL code.

(Second Embodiment)
FIG. 23 is a schematic configuration diagram of an action situation providing system using the exercise situation transmission terminal according to the second embodiment. Hereinafter, the components described in the first embodiment among the configurations shown in the second embodiment are denoted by the same reference numerals, and the description thereof is omitted.

  The system according to the present embodiment includes an exercise status transmission terminal 80, a communication adapter 81, a personal computer 83, a health management data server 5, a care center 6 (server), a medical center 7 (server), and the Internet, which will be described later. 17 (ADSL), a system connected by the CATV network 16, and the health management data server 5 stores the action status data Ai transmitted from the personal computer 83 when the exercise status transmission terminal 80 is attached to the communication adapter 81. The exercise center data of a predetermined display format that can grasp the current situation at a glance by comparing with the past accumulated data Bi, similar action situation data Ci (age, district, action type), etc. Provide to the server of the center 7.

  The exercise status transmission terminal 80 stores action identification information (acceleration, angular velocity, frequency analysis result data, exercise determination result, number of steps, energy consumption, etc.) and number of steps, stride, pulse, heart rate, etc., and a communication adapter 81. Action status data Ai transmitted from the personal computer 83 when it is attached to the health management data server 5 is stored. Since the exercise status transmission terminal 80 is provided with the same movement sensor and display device as the exercise status transmission terminal 1, description thereof will be omitted.

  When the exercise status transmission terminal 80 is attached, the communication adapter 81 rectifies and smoothes the commercial power supply AC100V and charges a battery provided inside the exercise status transmission terminal 80. Further, a communication cable is connected to the communication adapter 81, and the behavior status data Ai transmitted from the exercise status transmission terminal 80 connected to the COM port or USB port provided in the personal computer 83 is transmitted to the user terminal 83. Send to.

  The personal computer 83 is provided with a COM port and a USB port together with a CPU, ROM, RAM, hard disk HD storing an OS software and browser software, an ADSL modem, a monitor and the like for performing calculation and control. After receiving the behavior status data Ai from the exercise status transmission terminal 80 attached to the adapter 81 and temporarily storing it in the hard disk HD, the behavior status data Ai is transmitted to the health management data server 5 via the Internet 17 using an ADSL modem. Send.

  Next, with reference to FIG. 24, a method for charging the exercise status transmission terminal 80 using the communication adapter 81 will be described.

  First, the AC cable 85 provided in the exercise status transmission terminal 80 is plugged into the outlet of the commercial power supply AC100V. Next, the buckle of the belt 84 provided in the exercise status transmission terminal 80 is removed. Next, the slider 86 provided on the communication adapter 81 is pulled rightward on the paper surface, the exercise status transmission terminal 80 is attached to the communication adapter 81, and the slider 86 pulled rightward is returned. As a result, the communication adapter 81 and the contact point provided in the exercise status transmission terminal 80 are connected to each other, and the indicator provided in the exercise status transmission terminal 80 is lit to notify that charging has started.

(Description of operation)
Next, the operation of the system will be described below with reference to the sequence diagram shown in FIG. 25, the front screen shown in FIG. 26, and the flowchart shown in FIG. In the present embodiment, after the user exercises using the exercise status transmission terminal 80 described above, for example, at the end of the day, the exercise status transmission terminal 80 is removed from the arm and mounted on the communication adapter 81. (D21).

  At this time, it is assumed that the communication cable connected to the communication adapter 81 is connected to a COM port or a USB port provided in the personal computer 83.

  Further, in the personal computer 83, application software and browser software for performing the transfer processing of the behavior status data Ai are activated, and the display screen shown in FIG. 26 is displayed on the monitor. As a result, the personal computer 83 is in a standby state in which a user operation can be accepted.

  Here, in step S51, when the user clicks the “data read” button provided on the display screen using the mouse 89 (d22), the data request signal is transmitted from the personal computer 83 via the communication cable 87. It is transmitted to the transmission terminal 80 (d23).

  The exercise status transmission terminal 80 that has received the data request signal from the personal computer 83 sends the action status data Ai including the exerciser data, exercise identification information, the number of steps, calories, and the pulse to the personal computer 83 according to the received data request signal. Transmit (d24).

  Next, the personal computer 83 that has received the behavior status data Ai from the exercise status transmission terminal 80 temporarily stores the received behavior status data Ai in a hard disk (not shown) provided therein. That is, in FIG. 27, in step S53, the received action status data Ai is stored in a hard disk (not shown). Further, in step S55, the calorie consumption is calculated from the received behavior status data Ai and stored in a hard disk (not shown). As the behavior status data Ai, personal user information, step count data, and exercise pattern data are collected by the exercise status transmission terminal 80.

  Next, when the user clicks the “data transfer” button provided on the display screen using the mouse 89 in step S57, in step S59, the action status data Ai and the calorie consumption are compressed to generate a compressed file. . Next, in step S61, the personal computer 83 creates the URL code of the health management data server 5 as the transmission destination and transmits it to log in to the site (d2). The URL code corresponds to a dedicated folder for each user.

  Next, in step S63, the personal computer 83 reads a compressed file from a hard disk (not shown) provided therein, transmits it to the health management data server 5 using an ADSL modem, and the user uses the personal computer 83. The inputted meal data for today is transmitted (d3, d4).

  The health management data server 5 receives the compressed files from the personal computer 83, and stores them as a set in a folder for each user provided on a hard disk (not shown) (d5).

  The care center 6 accesses the health management data server 5 (person-in-charge code, request type code, period, area name, etc.) and requests various desired data (d6).

  The health management data server 5 decodes a request command (for example, totaling by exercise pattern, action pattern, number of steps for one day, number of steps for one month, etc.). Further, each time the received behavior status data Ai is stored in the database, the data extraction unit 25 separates, for example, 15 minutes of data, and the behavior type determination unit 26 indicates the behavior indicated by the behavior status data Ai (15 minutes). Is extracted as a type. Then, the behavior type ratio calculation unit 27 calculates the ratio of the behavior status data Ai as a percentage, and sends the result to the behavior pattern graphing unit 28.

  The behavior pattern graphing unit 28 includes a memory in which the vertical axis is percentage and the horizontal axis is time (24 hours), and the ratio of the type of the behavior status data Ai is displayed by color corresponding to the time axis and the percentage axis. .

  For example, as shown in FIG. 18, the behavior status data Ai corresponding to the user name is read, and the status of the behavior type is displayed as a bar graph in a coordinate system in which percentage is assigned to the vertical axis and time is assigned to the horizontal axis.

  In the case of an action pattern request for one month, as shown in FIG. 17, the past accumulated data of the user name is assigned, and these are separated into a predetermined period, and the action in the meantime is displayed by color in a pie chart.

  In addition, when requesting the number of steps for one month, the number of steps is assigned to the vertical axis and the date is assigned to the horizontal axis, as shown in FIG. In the coordinate system, the number of steps for each day is displayed as a bar graph.

  Furthermore, as shown in FIG. 20, when the number of steps is a day, the number of steps for each time is displayed as a bar graph in a coordinate system in which the number of steps is assigned to the vertical axis and the time is assigned to the horizontal axis.

  When a daily exercise pattern is requested, as shown in FIG. 21A, a ratio is displayed as a bar graph in accordance with the action type in a coordinate system composed of a time axis and a percentage axis. For example, red is displayed for intense sports, vermilion for light sports, amber for fast walking, and light blue for slow walking. FIG. 21B shows the details of the bar graph, and the upper side shows intense sports, light sports, standing work, and the like.

  Further, when the calorie consumption is requested, only the calorie value is extracted from the behavior situation data, and this is displayed on the coordinate system composed of the calorie axis and the date axis (see FIG. 22).

  Further, the screen is formed by comparing the target value and the personal situation in a graph, or by combining a bar graph and a pie graph.

  Such data is transmitted to the care center (D7). Accordingly, since the care center can grasp at a glance what action is being taken from the state of the screen, appropriate advice is transmitted to the personal computer 83 via the health management data server 5 (d8, d8a). In addition, since the health management data server 5 is connected to the CATV network in the present embodiment, it is possible to transmit information such as advice and attention to the user TV 8 (d8b). Further, since the health management data server 5 is also connected to the medical center via the Internet, the various screens described above can be displayed on the medical center upon request (doctor code, area name, period, data type code) from the medical center server. The medical center transmits appropriate advice to the user through the health management data server 5 to the personal computer 83 or the TV 8 (d10, d11, d12, d13, d12a, d13a). At this time, every time advice (diagnosis result) is transmitted to the user, the health management data server 5 counts the number of transmissions, and transmits medical points to the medical center according to the number of counts (d14).

  In other words, the Health Care Center counts the results advised by the doctor as medical practice.

(Third embodiment)
Similarly to the second embodiment, the third embodiment can be applied to the behavior situation providing system shown in FIG. 23, and in particular, the processing in the personal computer 83 executed based on the behavior situation data Ai. About. With reference to the flowcharts shown in FIGS. 28, 29A, and 29B, an action situation providing system according to the third embodiment will be described. The flowcharts shown in FIGS. 28, 29A, and B are stored on a hard disk (not shown) provided in the personal computer 83 as a program of application software.

  In the personal computer 83, application software for displaying the behavior status data Ai received from the exercise status transmission terminal 80 is activated, and the display screen shown in FIG. 26 is displayed on the monitor to accept the user's operation. It is assumed that it is in a possible standby state. In addition, it is assumed that action status data Ai received from the exercise status transmission terminal 80 is stored in a hard disk (not shown) provided in the personal computer 83. As the behavior status data Ai, personal user information, step count data, and exercise pattern data are collected by the exercise status transmission terminal 80.

  First, in step S100, the time interval set in the “time interval” area provided on the display screen is read to calculate the number of graph display data. That is, when the time interval of the graph display has been set to 3 minutes, for example, the number of data is 480 time intervals of 3 minutes for 24 hours per day.

  Next, in step S105, it is determined whether or not the “all patterns” button is selected for the “legend” area provided on the display screen. If the “all patterns” button is selected, the process proceeds to step S110. On the other hand, if the desired “pattern” button is selected, the process proceeds to step S200.

(Selection of desired pattern)
If the desired “pattern” button is selected, in step S200, the time interval related to the graph set in the “time interval” area provided on the display screen is read and set to 15 minutes. Advances to step S205, and if it is set to 3 minutes, advances to step S220.

  First, when the time interval regarding the graph is set to 15 minutes, in step S205, the total value Ki of the count values of each exercise pattern for 15 minutes is calculated.

  Next, in step S210, the total value S of the count values of all exercise patterns for 15 minutes is calculated.

  Next, in step S215, the ratio Pi of the motion pattern is calculated.

Pi = (Ki / S) * 100 (2)
On the other hand, when the time interval regarding the graph is set to 3 minutes, in step S220, the ratio Pi of the corresponding motion pattern is calculated. The ratio Pi of the corresponding exercise pattern is obtained by the above-described equation (1) based on the total value Ki of the count values of each exercise pattern for 3 minutes and the total value S of the count values of all exercise patterns for 3 minutes. And

  Next, in step S225, the data is stored in the array.

  Next, in step S230, rectangles are drawn in the order of “legend”, and a graph is displayed on the display screen. That is, the X axis is the time, and the Y axis is the total value Spi of the motion pattern ratio Pi so far, and the total value Spi of the ratio Pi including the displayed motion pattern.

  When the processing loop relating to all movement patterns is completed, the process proceeds to step S235, and the vertical / horizontal scale and the scale line are drawn. As a result, a daily exercise pattern as shown in FIG. 26 is displayed on the display screen.

(Select all patterns)
If the “all patterns” button is selected, it is determined in step S110 whether or not the processing loop relating to all motion patterns has been completed. That is, as shown in FIG. 26, the exercise pattern of the “legend” area includes intense sports, light sports, daily movement, slight movement, walk, normal walk, far walk, rapid walk, weak jogging, strong jogging, etc. Different processing numbers (# 1 to # 10) are assigned in order, and when the processing of steps S115 to S145 described later with respect to the processing number (# 1) is completed, the same applies to the next processing number (# 2). Processing is performed, and when the processing up to the processing number (# 10) is completed, the process branches to step S250, and when the processing up to the processing number (# 10) is not completed, the processing branches to step S115.

  Next, in step S115, the time interval related to the graph set in the “time interval” area provided on the display screen is read, and if it is set to 15 minutes, the process proceeds to step S120 and is set to 3 minutes. If yes, the process proceeds to step S135.

  First, when the time interval regarding the graph is set to 15 minutes, in step S120, the total value Ki of the count values of each exercise pattern for 15 minutes is calculated.

  Next, in step S125, the total value S of the count values of all exercise patterns for 15 minutes is calculated.

  Next, in step S130, the ratio Pi of the motion pattern is calculated.

Pi = (Ki / S) * 100 (3)
On the other hand, if the time interval for the graph is set to 3 minutes, in step S135, the ratio Pi of the corresponding motion pattern is calculated. The ratio Pi of the corresponding exercise pattern is obtained by the above-described equation (1) based on the total value Ki of the count values of each exercise pattern for 3 minutes and the total value S of the count values of all exercise patterns for 3 minutes. And

  Next, in step S140, the data is stored in the array. That is, a value (Spi + Pi) obtained by adding the total value Spi of the motion pattern ratio Pi and the ratio Pi of the corresponding motion pattern so far is stored in the array.

  Next, in step S145, the total value Spi of the movement pattern ratios Pi thus far is set as an array value.

  Next, the process returns to step S110, and if the processing loop related to all motion patterns is completed, the process proceeds to step S250.

  In step S250, it is determined whether or not the processing loop for all motion patterns has been completed. If the processing loop relating to all the motion patterns is not completed and the processing is continued, the process proceeds to step S255. On the other hand, when the processing loop regarding all the motion patterns is completed, the process proceeds to step S260.

  First, in step S255, rectangles are drawn in the order of “legend”, and a graph is displayed on the display screen. That is, the X axis is the time, and the Y axis is the total value Spi of the motion pattern ratio Pi so far, and the total value Spi of the ratio Pi including the displayed motion pattern.

  When the processing loop for all motion patterns is completed, the process proceeds to step S260, and the vertical / horizontal scales and scale lines are drawn. As a result, a daily exercise pattern as shown in FIG. 26 is displayed on the display screen.

  Here, the advice to the user in the medical center 7 of Embodiment 3 is demonstrated. In general, even if a doctor advises health-related information by fax, email, etc., it does not lead to medical practice.

  Therefore, when the health management data server 5 receives the advice information (user code, advice information, doctor code) from the medical center server as shown in FIG. 30, it stores it in the diagnostic file. The advice information described above is, for example, a diagnosis result or a caution determined by the doctor with reference to the graphs of FIGS. 17 to 23 and FIG. 26, and is transmitted by mail.

  Then, the address information is saved, and the user code and the doctor code are associated with the file number and saved (Fa).

  Next, the health management server 5 sends the user name, advice information, doctor name, doctor name, doctor's phone number, etc. as a set (Fa) to the user's terminal (personal computer or mobile phone).

  At this time, the counter processing 100 counts the number of transmissions, reads the number of the insurance policy stored in advance corresponding to the user code, and reads the user code, advice date, count value (diagnosis) The number of times is saved (Fa).

  Next, the conversion processing 101 searches the data Fc stored regularly (for example, every month), and for a predetermined period having the same doctor code (in August, from July 20 to August 20). The total number of diagnoses of the data Fc is calculated, and the total value is converted into the number of medical points, which is notified to the doctor and converted into a monetary amount to the user, and is withdrawn from the bank account to the medical center.

  Therefore, a medical point is a result advised by a doctor based on the graph transmitted from the terminal 1.

It is a schematic block diagram of the action condition provision system in 1st Embodiment. It is a principal part of the flowchart explaining operation | movement of the exercise condition transmission terminal in 1st Embodiment. FIG. 3A shows a main part (part 1), and FIG. 3B shows a main part (part 2), which are main parts of a flowchart for explaining the operation of the exercise status transmission terminal in the first embodiment. An example of the body measuring apparatus in 1st Embodiment is shown, FIG. 4A is a fragmentary top view, FIG. 4B is the AA sectional drawing. It is a top view which shows the internal structure of the motion sensor in 1st Embodiment. FIG. 6A shows behavioral coefficients, and FIG. 6B shows correction coefficients based on age and sex. It is a graph showing the relationship between Gx and ωz of the periodic movement of the subject P. It is a graph showing the relationship between Gx and ωz of the non-periodic behavior of the subject P. It is a graph showing the relationship between walking and running and ωz. It is a graph showing the relationship between walking and running and Gx. It is a graph showing the relationship between Gx and ωz of walking and running of the subject P. It is a graph showing the relationship between Gx and ωz of walking and running of the subject R. It is a graph which shows the result of having identified exercise of subject P every 15 minutes. It is a graph which shows the fluctuation | variation of the energy consumption of the test subject P for every 15 minutes. It is a graph which shows the fluctuation | variation of the step count for every 15 minutes of the test subject P. It is a sequence diagram explaining operation | movement of the system of 1st Embodiment. It is explanatory drawing explaining the processing screen by the side of the server of 1st Embodiment. It is explanatory drawing explaining the processing screen by the side of the server of 1st Embodiment. It is explanatory drawing explaining the processing screen by the side of the server of 1st Embodiment. It is explanatory drawing explaining the processing screen by the side of the server of 1st Embodiment. It is explanatory drawing explaining the server side processing screen of 1st Embodiment, FIG. 21A is a processing screen which shows the exercise | movement pattern for 1 day, FIG. 21B shows the detail of the bar graph which comprises the exercise | movement pattern. It is explanatory drawing. It is explanatory drawing explaining the processing screen by the side of the server of 1st Embodiment. It is a schematic block diagram of the action condition provision system in 2nd Embodiment. It is a figure which shows a mode that it is going to mount | wear with the exercise condition transmission terminal 80 on the communication adapter 81. FIG. It is a sequence diagram explaining operation | movement of the system of 2nd Embodiment. It is explanatory drawing explaining the processing screen of the personal computer of 2nd Embodiment. It is a principal part of the flowchart explaining operation | movement of the personal computer in 2nd Embodiment. It is a principal part (the 1) of the flowchart explaining the operation | movement of the personal computer in 3rd Embodiment. FIG. 29A shows a main part (part 2), and FIG. 29B shows a main part (part 3) (b), which are main parts of a flowchart for explaining the operation of the personal computer in the third embodiment. It is explanatory drawing explaining counting the frequency | count of diagnosis of advice information, and charging.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Exercise condition transmission terminal 3 Wireless adapter 2 Mobile phone 5 Health management data server 6 Care center 15 Data extraction part 16 Action type extraction part 17 Action type ratio calculation part 18 Action pattern graphing part

Claims (6)

Servers of various centers and user terminal devices are connected to the health management data server via a communication network, and behavior status data from the user terminal devices are collected and analyzed by the health management data server. It is an action status providing system that transmits to a center server and a user terminal device,
  The user terminal device
  It consists of a mobile phone and an exercise status transmission terminal worn on the arm,
  The exercise status transmission terminal is
Equipped with acceleration sensor, angular velocity sensor,
  The exercise status transmission terminal is
Means for sampling the data of these sensors, and determining the type of motion of the sampling data from the periodicity, size, direction, and frequency of the sampling data;
Exercise status data including the acquisition time of the sampling data, the type of exercise, the identification code of the user having the user terminal device, and the sampling data are collected at a preset time and the health management is performed by the mobile phone. Means for sending to the data server;
With
  The health management data server
First storage means for storing the exercise status data from the user terminal device;
  A second storage means for storing a behavior state form in a plurality of rectangular lattice areas in which a vertical axis indicates a percentage, a horizontal axis indicates a time axis for a day, and the time axis is divided in units of predetermined minutes;
  With
Means for receiving and storing in the first storage means exercise status data transmitted from the exercise status transmission terminal via the mobile phone;
  Data extraction means for separating and extracting the sampling data in predetermined minutes from the exercise status data stored in the first storage means;
  Means for extracting an exercise type of each sampling data in the extracted sampling data for the predetermined unit;
  Means for determining how long the sampling data corresponding to the extracted exercise type is; and
Means for determining the time ratio of the determined length of the sampling data corresponding to the extracted exercise type with respect to the percentage of the rectangular lattice region;
Means for defining the length ratio of the sampling data corresponding to the extracted exercise type in the second storage unit together with the exercise type of the data to obtain the user's exercise status graph information;
  Means for transmitting the exercise status graph information stored in the second storage means to a server of the various centers;
A behavior situation providing system characterized by comprising: 2. The behavior situation providing system according to claim 1, wherein the predetermined unit is a unit of 15 minutes . The servers of the various centers are medical center servers,
The health management data server
  A third storage means for storing the user identification code, the user insurance card number and the address of the mobile phone in association with each other, and storing the diagnosis result information;
With
  The health management data server
  When the doctor code, the user identification code, and the diagnosis result information are transmitted from the medical center server, the number of diagnoses is counted, and the count result, the doctor code, the diagnosis date, and the time are identified. Means for storing in the third storage means together with a code;
  Means for periodically collecting the number of diagnoses of diagnostic result information having the same doctor code, and sending the total number of diagnoses as the number of medical points together with the doctor code to the medical center server;
Means for converting the number of medical points into a monetary amount and transmitting the address to the mobile phone address of the user identification code;
With
The medical center server is
  With a display,
  Means for receiving exercise status graph information of the user from the health management data server and displaying the information on the display unit;
Means for transmitting diagnostic result information for the input exercise status graph information of the user to the health management data server together with the identification code and doctor code of the user;
The behavior status providing system according to claim 1, wherein: In place of the mobile phone of the user terminal, a cable TV or a personal computer is provided,
The health management data server is means for transmitting the diagnosis result information to the cable TV or transmitting it to the personal computer.
The behavior status providing system according to claim 1, 2, or 3 . A health center server and a user terminal device are connected to a health management data server via a communication network, and the health management data server collects and analyzes behavior status data from the user terminal device, and the analysis results are analyzed for the various types of analysis results. It is an action status providing system that transmits to a center server and a user terminal device,
  The user terminal device
  It consists of a mobile phone and an exercise status transmission terminal worn on the arm,
  The exercise status transmission terminal is
Equipped with acceleration sensor, angular velocity sensor,
  The exercise status transmission terminal is
Means for sampling the data of these sensors, and determining the type of motion of the sampling data from the periodicity, size, direction, and frequency of the sampling data;
Exercise status data including the acquisition time of the sampling data, the type of exercise, the identification code of the user having the user terminal device, and the sampling data are collected at a preset time and the health management is performed by the mobile phone. Means for sending to the data server;
With
  The health management data server
First storage means for storing the exercise status data from the user terminal device;
  A second storage means in which action status forms are stored in a plurality of rectangular lattice areas in which a vertical axis indicates a percentage, a horizontal axis indicates a time axis for one day, and the time axis is divided in units of 15 minutes;
  Third storage means for storing the user identification code, doctor code, diagnosis result information, and the address of the mobile phone in association with each other;
With
Means for receiving and storing in the first storage means exercise status data transmitted from the exercise status transmission terminal via the mobile phone;
  Data extraction means for separating and extracting sampling data for 15 minutes from the accumulated exercise status data;
  Action type determining means for extracting the exercise type of each sampling data in the extracted sampling data for 15 minutes;
  Means for determining how long the sampling data corresponding to the extracted exercise type is; and
Means for determining a time ratio of the determined length of sampling data corresponding to the extracted exercise type with respect to the percentage of the rectangular lattice region;
Means for defining the ratio of the length of the sampling data corresponding to the extracted exercise type together with the exercise type of the data to obtain exercise status graph information of the user;
  When the doctor code, the user code, and the diagnosis result information are transmitted from the medical center server, the number of times of diagnosis is counted, and the count result, the doctor code, the diagnosis date, the time, and the identification code of the user are counted. Means for storing in a third storage means;
  Means for periodically collecting the number of diagnoses of diagnosis result information having the same doctor code, and sending the total number of diagnoses as a medical point number together with the doctor code to the medical center server;
Means for converting the number of medical points into a monetary amount and transmitting the address to the mobile phone address of the user identification code;
With
The medical center server is
  With display,
  Receiving the user's exercise status graph information from the health management server and displaying it on the display unit;
Means for transmitting diagnostic result information on the input exercise status graph information of the user to the health management data server;
Means for receiving the number of medical points from the health management data server;
A behavior situation providing system characterized by comprising: In place of the mobile phone of the user terminal, a cable TV or a personal computer is provided,
The health management server transmits the diagnosis result information to the cable TV or transmits to the personal computer
5. The behavior status providing system according to claim 4, further comprising:

Images