JP2015228911A - Device for measuring human activity amount, method for measuring human activity amount, and program for measuring human activity amount - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a device and the like for measuring human activity amount, the device calculating an intensity of human physical activity and the like by using a Doppler sensor.SOLUTION: The device for measuring human activity amount includes: a transmitter; a receiver; and a processor for obtaining frequency information and amplitude information of input signals obtained by receiving by the receiver reflection waves related to transmission waves sent from the transmitter, and on the basis of information associating the obtained frequency information and amplitude information with intensity of physical activity corresponding to the frequency information and amplitude information, for calculating the intensity of physical activity of the person who has reflected the transmission waves.

Description

  The present disclosure relates to a human activity amount measuring apparatus and the like.

  A Doppler-type sensor unit that transmits a transmission signal to the detection area and receives a reflected wave from the detection target person, correlates the output of the sensor unit with the displacement of the detection target person, Human body abnormality detectors that determine normal or abnormal states are known (see, for example, Patent Document 1). The displacement of the person to be detected is a displacement accompanying the breath of the person to be detected.

JP 2002-159453 A

  Patent Document 1 only discloses that a displacement of a detection target accompanying breathing is measured using a frequency value from the Doppler sensor or the like (detection interval that is a period of a pulse signal). The point of calculating the exercise intensity of a person by using is not disclosed.

  Therefore, the disclosed technique aims to provide a human activity amount measuring device and the like that calculate a person's exercise intensity using a Doppler sensor.

According to one aspect of the present disclosure, a transmitter;
A receiver,
The frequency information and amplitude information of the received signal obtained by receiving the reflected wave related to the transmission wave transmitted from the transmitter by the receiver is acquired, and the acquired frequency information, amplitude information, frequency information and amplitude information are acquired. And a processing device that calculates the exercise intensity of the person reflecting the transmitted wave based on information relating to the exercise intensity corresponding to the human activity amount measuring apparatus.

  According to the technology of the present disclosure, it is possible to obtain a human activity amount measuring device that calculates a human exercise intensity and the like using a Doppler sensor.

The figure which shows schematically the structure of the human activity amount measuring apparatus 1 by one Example. The figure which shows an example of the hardware constitutions of the processing apparatus. The circuit block diagram of the Doppler sensor 20 by an example. The figure which shows an example of the waveform of the output signal of the Doppler sensor. 5 is a flowchart showing an example of processing executed by the processing apparatus 100. Explanatory drawing of the amplitude variation | change_quantity of the output signal of the Doppler sensor 20. FIG. Explanatory drawing of the wavelength calculation process at the time of extension. The figure which shows the correlation with the wavelength at the time of extension, and exercise intensity. 7 is a flowchart showing another example of processing executed by the processing apparatus 100. The figure which shows the example of application of the human activity amount measuring apparatus 1. FIG. The figure which shows the other application example of the human activity amount measuring apparatus.

  Hereinafter, embodiments will be described in detail with reference to the accompanying drawings.

  FIG. 1 is a diagram schematically showing a configuration of a human activity measuring device 1 according to an embodiment.

  The human activity measuring device 1 includes a Doppler sensor 20 and a processing device 100.

  The Doppler sensor 20 is provided in the living space of the detection target person (for example, the room of the detection target person). The person to be detected is arbitrary, but may be, for example, an elderly person living alone. The Doppler sensor 20 is typically fixed. A plurality of Doppler sensors 20 may be provided in the living space of the person to be detected. Hereinafter, for convenience of explanation, one Doppler sensor 20 will be described unless otherwise specified.

  The Doppler sensor 20 includes a transmitter 220 and a receiver 240. The transmitter 220 and the receiver 240 may be formed separately, or may be formed integrally as a transceiver. The transmitter 220 transmits a transmission wave having a predetermined frequency into the living space of the person to be detected. The receiver 240 receives a reflected wave from a reflector (for example, a detection target person) in the living space of the detection target person. Signal processing in the Doppler sensor 20 will be described later.

  The processing device 100 performs various processes based on the output signal obtained from the Doppler sensor 20. Note that the functions of the processing apparatus 100 may be realized by one or more arbitrary numbers of processing apparatuses. Further, part or all of the functions of the processing apparatus 100 may be realized by a processing apparatus (for example, refer to the MCU 24 in FIG. 3) that can be incorporated in the Doppler sensor 20. Conversely, some or all of the functions realized by the processing device in the Doppler sensor 20 may be realized by the processing device 100.

  FIG. 2 is a diagram illustrating an example of a hardware configuration of the processing apparatus 100.

  In the example illustrated in FIG. 2, the processing device 100 includes a control unit 101, a main storage unit 102, an auxiliary storage unit 103, a drive device 104, a network I / F unit 106, and an input unit 107.

  The control unit 101 is an arithmetic device that executes a program stored in the main storage unit 102 or the auxiliary storage unit 103, receives data from the input unit 107 or the storage device, calculates, processes, and outputs the data to the storage device or the like. To do.

  The main storage unit 102 is a ROM (Read Only Memory), a RAM (Random Access Memory), or the like. The main storage unit 102 is a storage device that stores or temporarily stores programs and data such as OS (Operating System) and application software which are basic software executed by the control unit 101.

  The auxiliary storage unit 103 is an HDD (Hard Disk Drive) or the like, and is a storage device that stores data related to application software or the like.

  The drive device 104 reads the program from the recording medium 105, for example, a flexible disk, and installs it in the storage device.

  The recording medium 105 stores a predetermined program. The program stored in the recording medium 105 is installed in the processing device 100 via the drive device 104. The installed predetermined program can be executed by the processing apparatus 100.

  The network I / F unit 106 is an interface between the processing apparatus 100 and a peripheral device having a communication function connected via a network constructed by a data transmission path such as a wired and / or wireless line.

  The input unit 107 includes a keyboard having cursor keys, numeric input, various function keys, and the like, a mouse, a slice pad, and the like.

  In the example shown in FIG. 2, various processes described below can be realized by causing the processing apparatus 100 to execute a program. It is also possible to record the program on the recording medium 105 and cause the processing apparatus 100 to read the recording medium 105 on which the program is recorded, thereby realizing various processes described below. Note that various types of recording media can be used as the recording medium 105. For example, the recording medium 105 is a recording medium that records information optically, electrically, or magnetically, such as a CD (Compact Disc) -ROM, a flexible disk, a magneto-optical disk, or the like, or a ROM, a flash memory, or the like. It may be a semiconductor memory or the like for electrically recording. Note that the recording medium 105 does not include a carrier wave.

  FIG. 3 is an explanatory diagram of signal processing in the Doppler sensor 20, and schematically shows a circuit block diagram of the Doppler sensor 20 according to an example. FIG. 3 schematically shows the detection target person S and various waveforms.

  The Doppler sensor 20 includes an OSC (oscillator) 22, an antenna 23, an MCU (Micro Control Unit) 24, a detection circuit 26, a battery 28, and an OP (Operational) amplifier 30.

  In the example illustrated in FIG. 3, the OSC 22 generates a local signal under the control of the MCU 24. The local signal is demultiplexed by the antenna 23 and the detection circuit 26. A radio wave transmitted from the antenna 23 is generated based on a local signal and transmitted as a transmission wave in the living space of the detection subject S. The frequency of the transmission wave is arbitrary. The transmission wave may be a radio wave (microwave) of 2 GHz to 4 GHz, for example. The radio wave (reflected wave) reflected by the person to be detected S is received by the antenna 23 and mixed with a local signal to generate a beat signal. The beat signal is input to the detection circuit 26, and the Doppler frequency and the like are detected by the detection circuit 26. The beat signal is amplified by the OP amplifier 30 and output to the processing apparatus 100. The OSC 22, the detection circuit 26, etc. operate based on the power from the battery 28. In the example shown in FIG. 3, the transmitter 220 is formed by the OSC 22 and the antenna 23 and the receiver 240 is formed by the OSC 22 and the antenna 23 and the like. The antenna 23 may be provided separately for each of the transmitter 220 and the receiver 240.

  FIG. 4 shows an example of a waveform of an output signal output from the Doppler sensor 20 to the processing device 100.

  As described above, the output signal corresponds to the received signal (the beat signal in the example of FIG. 3) related to the reflected wave received by the Doppler sensor 20. For example, the beat signal can be expressed by the following equation.

ここで、ｃは光速、ｆ_ｄはドップラ周波数、ｆ_０は送信波の周波数とし、ｖは検知対象者Ｓの速度、Ｒはドップラセンサ２０から検知対象者Ｓまでの距離である。Ａは、振幅であり、反射強度に応じて変動する。

Here, c is the speed of light, f _d is the Doppler frequency, f ₀ is the frequency of the transmission wave, v is the speed of the detection target person S, and R is the distance from the Doppler sensor 20 to the detection target person S. A is an amplitude and varies according to the reflection intensity.

The value of the amplitude A of the output signal represents the reflection intensity, and generally increases as the reflection area increases. Therefore, the amplitude value of the output signal increases as the region where the detection target person S moves increases. For example, the amplitude value of the output signal is larger when the detection target person S is moving the entire body than when the detection target person S is moving only the hand. The frequency (Doppler frequency) of the output signal represents the speed of the detection target person S, and increases as the speed of the detection target person S increases. The Doppler frequency f _d can be expressed by f _d = 2vf ₀ / (c−v).

  Thus, the size and speed of the moving part of the detection subject S appear in each of the amplitude value and the frequency of the output signal of the Doppler sensor 20. The size and speed of the moving part of the detection target person S can be related to the amount of exercise, and can represent the exercise intensity as described later.

  FIG. 5 is a flowchart illustrating an example of processing executed by the processing device 100. The process illustrated in FIG. 5 may be repeatedly executed at predetermined intervals.

  In step S500, processing device 100 acquires an output signal of Doppler sensor 20 over a period ΔT corresponding to a predetermined cycle.

  In step S <b> 502, the processing device 100 calculates the amplitude change amount of the output signal of the Doppler sensor 20. The amplitude change amount is calculated as an absolute value. The amplitude change amount may be calculated after pre-processing the output signal of the Doppler sensor 20 by a low-pass filter, A / D (Analog-to-Digital) conversion, or the like. In FIG. 6, the horizontal axis represents time, and the vertical axis represents the amplitude of the output signal of the Doppler sensor 20. In FIG. 6, for convenience, the output signal of the Doppler sensor 20 is represented by a voltage value [V]. As shown in FIG. 6, the amplitude change amount from a certain time point t = N + 2 to the next time point t = N + 1 is | (α + 1) − (α + 2) |. Similarly, the amount of amplitude change from time t = N + 1 to the next time t = N is | (α) − (α + 1) |. Note that the intervals between the time points N + 2, N + 1, and N are arbitrary, but are set to values that are significantly smaller than ¼ of the period that the output signal can take. This is because the sum of the amplitude change amounts accurately represents the extension wavelength (described later) of the output signal as will be described later. For example, the interval between each time point N + 2, N + 1, N is set to a value equal to or less than 1/5 of ¼ of the period that the output signal can take.

  In step S504, the processing apparatus 100 calculates the length of the waveform of the output signal (hereinafter also referred to as “extension wavelength”) based on the amplitude change amount calculated in step S502. The wavelength at extension corresponds to the length when the waveform of the output signal is straightened. The processing apparatus 100 calculates the extension wavelength in the period ΔT. The period ΔT is preferably set to a value that is significantly larger than a possible period of the output signal. This is because the difference in frequency is remarkably reflected in the extended wavelength. For example, the period ΔT is set to a length that is at least five times the period that the output signal can take. The processing apparatus 100 calculates the extension wavelength by summing up each amplitude change amount calculated over the immediately preceding period ΔT with the current time as a reference. That is, the extension wavelength corresponds to the integrated value of the amplitude change amount over the period ΔT. For example, in the example illustrated in FIG. 6, | (α + 1) − (α + 2) | + | (α) − (α + 1) | +. In the case where the amplitude of the output signal is represented by a voltage value as shown in FIG. 6, the unit of the extension wavelength is “voltage / time” such as V / min.

  FIG. 7 is an explanatory diagram of the wavelength calculation process during extension, where (A) shows the original waveform of the output signal, (B) shows the differential waveform, and (C) shows the differential waveform for a predetermined time (this example). Shows the total value in 1 second). The differential waveform represents an amplitude change amount for each predetermined minute time, and in this example, represents a differential waveform calculated at a sampling period of 1 kHz. Therefore, in this example, the amplitude change amount represents the amplitude change amount every 1/1000 second. The process of calculating the differential waveform from the original waveform corresponds to the process of step S502. When the period ΔT is 1 second, the difference waveforms are summed every second (in this example, the amplitude variation is summed every 1000). In this way, the extension wavelength in the period ΔT is calculated.

  In step S506, the processing apparatus 100 calculates exercise intensity based on the extension wavelength calculated in step S504. The exercise intensity is an index value representing the amount of activity of a person and is known as a MET value (Mets value). METs is an abbreviation of “Metabolic equivalents”, and the Mets value indicates how many times the metabolism (calorie consumption) is in a resting state when performing activity / exercise. That is, the Met's value is expressed as a relative value when each physical activity is performed with the reference value “1” when resting. What physical activity results in what mets value is expressed in the mets table (published by the National Institute of Health and Nutrition).

  Here, the extension wavelength corresponds to the length when the waveform of the output signal in the period ΔT is straightened as described above. The wavelength at the time of extension becomes longer as the amplitude of the output signal is larger, and becomes longer as the frequency of the output signal is higher. That is, the extension wavelength becomes longer as the region where the detection target person moves increases, and becomes longer as the detection target person moves faster. It can be seen that the size and speed of the moving part of the detection target person are related to the momentum related to the movement of the detection target person as described above, and therefore the extension wavelength is a parameter related to the momentum. Actually, the inventors of the present application have confirmed that there is a strong correlation between the extension wavelength and the exercise intensity, for example, as shown in FIG. In FIG. 8, the extension wavelength and exercise intensity are plotted for six types of physical activities, “sitting position”, “sleep”, “dishwashing”, “cleaning”, “walking”, and “stretching”. The extension wavelength is calculated by setting the period ΔT to 1 minute. “Sleep” corresponds to a resting state, and the exercise intensity is the reference value “1”. As shown in FIG. 8, the wavelength and movement at the time of extension are increased as the physical activity is larger and the movement speed is faster in the order of “sitting position”, “dishwashing”, “cleaning”, “stretching”, and “walking”. It can be seen that the strength has increased. In the “sitting position”, since the heart rate and the respiratory rate are about 5 to 10% higher than the resting state (because the number of times of movement increases), the wave number increases and the wavelength during extension increases. The extension wavelength and the exercise intensity can be related by a certain relational expression F. As shown in FIG. 8, the relational expression F can be derived in advance by curve fitting (curve fitting) using a plurality of actual data. The relational expression F may be stored in a storage device (for example, the auxiliary storage unit 103) in the processing device 100. In this case, the processing apparatus 100 can obtain the exercise intensity by substituting the extension wavelength calculated in step S504 into the relational expression F.

  The relational expression F may be derived assuming an average user. However, the relational expression F may be derived for each sex, weight, and height. This is because the correlation between the extension wavelength and the exercise intensity changes depending on the sex, weight, and height. In this case, the processing apparatus 100 calculates the exercise intensity using the relational expression F corresponding to the detection target person. For this purpose, detection target person information indicating the age, height, weight, etc. of the detection target person may be input to the human activity amount measuring apparatus 1 at the time of initial setting or the like. Similarly, the relationship between the extension wavelength and exercise intensity can be influenced by other parameters (environmental temperature, mental tension) and the like. Accordingly, the relational expression F may be derived for each such parameter. Alternatively, the relational expression F may be derived for each detection target person based on the actual measurement data of the detection target person.

  In step S506, an example of obtaining the exercise intensity using the relational expression F that associates the extension wavelength and the exercise intensity is shown. However, a database that associates the extension wavelength and the exercise intensity, or the frequency and amplitude You may make it obtain | require exercise intensity with reference to the database which linked | related exercise intensity.

In step S508, the processing device 100 calculates the heart rate of the detection target person based on the exercise intensity calculated in step S504. The heart rate and the exercise intensity are represented by the following relational expression, for example.
Exercise intensity = (heart rate-resting heart rate) ÷ (maximum heart rate-resting heart rate) x 10 formulas (1)
Here, predetermined values can be used for the resting heart rate and the maximum heart rate. Alternatively, the resting heart rate and the maximum heart rate may be set for each person to be detected. For example, (220—age of the person to be detected) may be used as the maximum heart rate. Alternatively, the measurement target person's measured data may be used as the resting heart rate and the maximum heart rate.

  In step S510, processing device 100 outputs the heart rate calculated in step S508. The output destination of the heart rate is arbitrary, and may be output to, for example, a monitor (not shown) that monitors the person to be detected. The heart rate may be output as a direct numerical value, or may be output after being converted into indirect information. In addition to or instead of the real-time output of the heart rate, the processing device 100 may output a warning when the heart rate calculated in step S508 is outside the predetermined normal range.

  According to the process shown in FIG. 5, the heart rate of the detection target person can be calculated from the output signal of the Doppler sensor 20 via the exercise intensity of the detection target person.

  By the way, the Doppler sensor 20 can also detect a minute displacement of the detection subject's body related to the heart rate and respiration rate of the detection subject. That is, a minute displacement of the body appears as a change in the frequency of the output signal (change in the Doppler frequency) and can be detected. However, such detection is actually possible only when the person to be detected is in a resting state. This is because when the detection target person moves, the reflected wave due to the movement becomes dominant.

  On the other hand, according to the process shown in FIG. 5, the exercise intensity of the detection subject is calculated from the output signal of the Doppler sensor 20, and the heart rate of the detection subject is calculated based on the calculated exercise intensity. Thereby, even when the detection target person is moving, the heart rate of the detection target person can be accurately calculated.

  In the process shown in FIG. 5, the processing apparatus 100 may execute the process of step S502 in real time on the output signal of the Doppler sensor 20 input in real time. In this case, in step S504, the processing apparatus 100 may calculate the extension wavelength in the period ΔT at the time when the amplitude change amount for the period ΔT is calculated for each period ΔT. Alternatively, in step S504, the processing apparatus 100 may calculate the extension wavelength using each amplitude change amount for the most recent period ΔT at every predetermined time shorter than the period ΔT. In this case, the predetermined time may be the same as the calculation cycle of the amplitude change amount, or may be longer than the calculation cycle of the amplitude change amount.

  In the process shown in FIG. 5, the heart rate is calculated from the exercise intensity, but the process in step S508 may be omitted as shown in FIG. That is, the calculation of the heart rate may be omitted. Such a configuration is suitable for controlling home appliances using the calculated exercise intensity (see, for example, FIG. 10). According to the process shown in FIG. 9, the exercise intensity of the person to be detected can be calculated from the output signal of the Doppler sensor 20.

  In the process shown in FIG. 9, in step S510, the processing apparatus 100 outputs the exercise intensity calculated in step S506. The output destination of the exercise intensity is arbitrary, and may be output to, for example, a monitor (not shown) that monitors the person to be detected. The exercise intensity may be output as a direct numerical value, or may be converted into indirect information and output. In addition to or instead of the real-time output of the exercise intensity, the processing apparatus 100 may output a warning when the exercise intensity calculated in step S506 is less than a predetermined value (for example, less than 1).

  In addition, even if it is the same physical activity, exercise intensity can become a different value if the load is different. For example, even if the physical activity is “walking”, the exercise intensity differs depending on whether the person has a heavy object or a light object. In this regard, in the examples shown in FIGS. 5 and 9, the exercise intensity is calculated without considering such a load or assuming a light load state. 5 and 9, the Doppler sensor 20 alone can calculate the exercise intensity (and heart rate) of the person to be detected, but information on other sensors (for example, an image sensor, etc.) The exercise intensity may be calculated in combination. For example, the load of the person to be detected (for example, a state of having a heavy object) may be detected by another sensor, and the exercise intensity may be corrected.

  FIG. 10 is a diagram illustrating an application example of the human activity measuring device 1. Here, as an example, the processing apparatus 100 calculates only exercise intensity and does not calculate the heart rate (see FIG. 9). However, the processing apparatus 100 is also configured to calculate the heart rate (see FIG. 5).

  In the example illustrated in FIG. 10, the function of the processing device 100 is realized by the processing device in the cloud 400. Specifically, an output signal (sensor data) from the Doppler sensor 20 is supplied to the cloud 400 via the gateway 302. In this case, the Doppler sensor 20 may be provided in the air conditioner 300. The cloud 400 includes a home appliance control application 402, an activity state determination application 404, an API (Application Programming Interface) 406, an exercise intensity analysis engine 408, a raw data database 410, and an analysis data database 412.

  The exercise intensity analysis engine 408 uses the sensor data acquired via the gateway 302 to calculate the exercise intensity of the detection target person S according to the process shown in FIG. The sensor data acquired via the gateway 302 is stored in the raw data database 410. The exercise intensity analysis engine 408 stores the calculated exercise intensity in the analysis data database 412 and supplies it to the activity state determination application 404 via the API 406. The activity state determination application 404 determines the activity state of the detection target person S based on the exercise intensity. The activity state of the person S to be detected may correspond to various activity states described in the Mets table (issued by the National Institute of Health and Nutrition). The activity state of the detection target person S may be, for example, “sitting position”, “sleep”, “dishwashing”, “cleaning”, “walking”, “stretching”, and the like. The activity state determination application 404 supplies the determination result of the activity state of the detection target person S to the home appliance control application 402. The home appliance control application 402 generates a control signal for the air conditioner 300 according to the activity state of the detection target person S, and transmits the control signal to the air conditioner 300 via the gateway 302. The control items of the air conditioner 300 are arbitrary, and may include, for example, the type of operation such as dry, heating, and cooling, temperature, air volume, and direction of the wind direction. The home appliance control application 402 is typically an air conditioner in which the temperature in the living space of the detection target person S decreases as the exercise intensity of the detection target person S increases (an aspect that takes away the heat generated by the detection target person S). The apparatus 300 is controlled. On the contrary, when the exercise intensity of the person S to be detected is low (for example, in a resting state), the home appliance control application 502 may cause the air conditioner 300 to perform a weak operation or stop. Note that the home appliance control application 402 may determine the control mode of the air conditioner 300 in consideration of other parameters such as the temperature of the living space of the detection target person S and the set temperature.

  In the example shown in FIG. 10, the activity state determination application 404 is used, but the activity state determination application 404 may be omitted. In this case, the home appliance control application 402 may control the air conditioner 300 according to the exercise intensity of the detection target person S.

  In the example shown in FIG. 10, the function of the processing device 100 is realized by the processing device in the cloud 400, but a part of the function of the processing device 100 is built in the air conditioner 300 and / or the gateway 302. May be realized by a processing device.

  FIG. 11 is a diagram illustrating another application example of the human activity amount measuring apparatus 1. Here, as an example, the processing apparatus 100 calculates only exercise intensity and does not calculate the heart rate (see FIG. 9). However, the processing apparatus 100 is also configured to calculate the heart rate (see FIG. 5).

  In the example illustrated in FIG. 11, the function of the processing device 100 is realized by the processing device in the mobile terminal 500. Specifically, an output signal (sensor data) from the Doppler sensor 20 is supplied to the portable terminal 500. The portable terminal 500 may be any information terminal such as a smartphone or a tablet terminal. The mobile terminal 500 includes a home appliance control application 502, an activity state determination application 504, an exercise intensity analysis engine 508, a raw data database 510, and an analysis data database 512.

  The exercise intensity analysis engine 508 uses the sensor data received from the Doppler sensor 20 to calculate the exercise intensity of the person S to be detected according to the process shown in FIG. The received sensor data is stored in the raw data database 510. The exercise intensity analysis engine 508 stores the calculated exercise intensity in the analysis data database 512 and supplies it to the activity state determination application 504. The activity state determination application 504 determines the activity state of the detection target person S based on the exercise intensity. The activity state determination application 504 supplies the determination result of the activity state of the detection target person S to the home appliance control application 502. The home appliance control application 502 generates a control signal for the air conditioner 300 according to the activity state of the detection target person S and transmits the control signal to the air conditioner 300. The home appliance control application 502 typically controls the air conditioner 300 in such a manner that the temperature in the living space of the detection target person S decreases as the exercise intensity of the detection target person S increases. On the contrary, when the exercise intensity of the person S to be detected is low (for example, in a resting state), the home appliance control application 502 may cause the air conditioner 300 to perform a weak operation or stop. Similarly, the home appliance control application 502 may determine the control mode of the air conditioner 300 in consideration of other parameters such as the temperature of the living space of the detection target person S and the set temperature.

  In the example shown in FIG. 11, the activity state determination application 504 is used, but the activity state determination application 504 may be omitted. In this case, the home appliance control application 502 may control the air conditioner 300 according to the exercise intensity of the detection target person S.

  In the example illustrated in FIG. 11, the function of the processing device 100 is realized by the processing device in the portable terminal 500, but a part of the function of the processing device 100 is performed by the processing device that can be incorporated in the air conditioner 300. It may be realized.

  In the example illustrated in FIGS. 10 and 11, an air conditioner 300 is assumed as an example of the home appliance. However, home appliances are various in addition to the air conditioner 300, and may include a fan, floor heating, a kotatsu, a lighting fixture, and the like. Moreover, the number of household appliances to be controlled is not necessarily one, and may be plural. Moreover, the control aspect of the household appliance according to the exercise | movement intensity | strength of the detection subject person S may be determined according to the kind of household appliance. For example, when the home appliance is a lighting fixture, the home appliance control applications 402 and 502 may turn on the lighting fixture or increase the illuminance when the exercise intensity of the detection target person S is high. On the other hand, when the exercise intensity of the person S to be detected is low (for example, in a resting state), the home appliance control applications 402 and 502 may turn off the luminaire or reduce the illuminance. In this case, the Doppler sensor 20 may be provided in the lighting fixture.

  In the example illustrated in FIGS. 10 and 11, the cloud 400 and the mobile terminal 500 include the home appliance control applications 402 and 502, respectively, but instead of or in addition, a monitoring application may be included. The watching application may output a warning when the exercise intensity of the detection target person S is less than a predetermined value (for example, less than 1). The warning may be output via a buzzer or the like that may be provided in the air conditioner 300, or may be output to a monitor (not shown) or a buzzer that monitors the person to be detected. Thereby, for example, even in a season where the air conditioner 300 is not used, such as spring or autumn, the watching function can be activated using the output signal from the Doppler sensor 20. In order to effectively realize the watching function, a plurality of Doppler sensors 20 are preferably provided as necessary so that the entire living space of the person to be detected can be detected.

  Although each embodiment has been described in detail above, it is not limited to a specific embodiment, and various modifications and changes can be made within the scope described in the claims. It is also possible to combine all or a plurality of the components of the above-described embodiments.

  For example, in the above-described embodiment, in order to reduce the calculation load, the extension wavelength is calculated by integrating the amount of change (absolute value) of the amplitude value in each sampling period. The hourly wavelength may be calculated. For example, the extension wavelength may be calculated by integration using the three-square theorem.

In addition, the following additional remarks are disclosed regarding the above Example.
(Appendix 1)
A transmitter,
A receiver,
The frequency information and amplitude information of the received signal obtained by receiving the reflected wave related to the transmission wave transmitted from the transmitter by the receiver is acquired, and the acquired frequency information and amplitude information, and the frequency information and amplitude information are acquired. And a processing device that calculates the exercise intensity of the person who reflected the transmitted wave based on the information relating the exercise intensity corresponding to.
(Appendix 2)
The human activity amount measuring apparatus according to claim 1, wherein the processing device calculates the exercise intensity based on a length of a waveform of the reception signal per predetermined time.
(Appendix 3)
The human activity according to claim 2, wherein the processing device calculates the exercise intensity when the length is relatively long and the exercise intensity is larger than when the length is relatively short. Quantity measuring device.
(Appendix 4)
The processing device integrates the absolute value of the change amount of the amplitude of the received signal for each first time shorter than the predetermined time for the predetermined time, and calculates the exercise intensity based on the total value of the integrated change amounts. The human activity amount measuring apparatus according to claim 2, wherein the human activity amount measuring apparatus calculates.
(Appendix 5)
The human activity amount measuring apparatus according to claim 4, wherein the processing device calculates the exercise intensity from the total value based on a relational expression between the total value and the exercise intensity.
(Appendix 6)
The human activity amount measuring device according to claim 1, wherein the processing device calculates a heart rate of the person based on the exercise intensity.
(Appendix 7)
The human activity amount according to claim 6, wherein the processing device calculates a heart rate of the person based on a relational expression of the exercise intensity, a resting heart rate, a maximum heart rate, and a heart rate. measuring device.
(Appendix 8)
The human activity measuring device according to appendix 7, wherein the processing device outputs an alarm when the calculated heart rate is outside a predetermined range.
(Appendix 9)
The human activity amount measuring device according to any one of claims 1 to 5, wherein the processing device outputs an alarm when the exercise intensity is less than a predetermined value.
(Appendix 10)
With Doppler sensor,
The human activity amount measuring device according to any one of appendices 1 to 9, wherein the Doppler sensor includes the transmitter and the transmitter.
(Appendix 11)
The said processing apparatus is a human activity amount measuring apparatus of any one of Additional remarks 1-5 which determines the control aspect of the electric equipment in the said person's living space based on the said exercise intensity.
(Appendix 12)
The human activity amount measuring apparatus according to appendix 11, wherein the processing device controls the luminaire in such a manner that the illuminance decreases when the exercise intensity is relatively low compared to when the exercise intensity is relatively high.
(Appendix 13)
The human activity amount measuring device according to appendix 11, wherein the processing device controls the air conditioner in such a manner that when the exercise intensity is relatively low, the cooling capacity is lower than when the exercise intensity is relatively high. .
(Appendix 14)
Comprising a Doppler sensor provided in the electrical device;
The human activity amount measuring device according to attachment 11, wherein the Doppler sensor includes the transmitter and the transmitter.
(Appendix 15)
The computer acquires the frequency information and amplitude information of the received signal obtained by receiving the reflected wave related to the transmission wave transmitted from the transmitter with the receiver, and the acquired frequency information, amplitude information, frequency information, and amplitude A human activity amount measuring method for calculating exercise intensity of a person reflecting the transmission wave based on information relating to exercise intensity corresponding to the information.
(Appendix 16)
Acquires frequency information and amplitude information of the received signal obtained by receiving the reflected wave related to the transmitted wave transmitted from the transmitter with the receiver, and supports the acquired frequency information, amplitude information, frequency information and amplitude information A human activity measurement program for causing a computer to execute a process of calculating exercise intensity of a person reflecting the transmitted wave based on information relating to exercise intensity to be performed.

1 human activity measuring device 20 Doppler sensor 100 processing device 220 transmitter 240 receiver

Claims (10)

A transmitter,
A receiver,
The frequency information and amplitude information of the received signal obtained by receiving the reflected wave related to the transmission wave transmitted from the transmitter by the receiver is acquired, and the acquired frequency information, amplitude information, frequency information and amplitude information are acquired. And a processing device that calculates the exercise intensity of the person reflecting the transmitted wave based on information relating to the exercise intensity corresponding to.   The human activity amount measuring apparatus according to claim 1, wherein the processing device calculates the exercise intensity based on a length of a waveform of the reception signal per predetermined time.   The human activity according to claim 2, wherein the processing device calculates the exercise intensity when the length is relatively long and the exercise intensity is larger than when the length is relatively short. Quantity measuring device.   The processing device integrates the absolute value of the change amount of the amplitude of the received signal for each first time shorter than the predetermined time for the predetermined time, and calculates the exercise intensity based on the total value of the integrated change amounts. The human activity amount measuring apparatus according to claim 2, wherein the human activity amount measuring apparatus calculates.   The human activity amount measuring apparatus according to claim 4, wherein the processing device calculates the exercise intensity from the total value based on a relational expression between the total value and the exercise intensity.   The human activity amount measuring device according to claim 1, wherein the processing device calculates a heart rate of the person based on the exercise intensity.   The human activity amount according to claim 6, wherein the processing device calculates a heart rate of the person based on a relational expression of the exercise intensity, a resting heart rate, a maximum heart rate, and a heart rate. measuring device.   The human activity amount measuring device according to any one of claims 1 to 5, wherein the processing device outputs an alarm when the exercise intensity is less than a predetermined value.   The computer acquires the frequency information and amplitude information of the received signal obtained by receiving the reflected wave related to the transmission wave transmitted from the transmitter with the receiver, and the acquired frequency information, amplitude information, frequency information, and amplitude A human activity amount measuring method for calculating exercise intensity of a person reflecting the transmission wave based on information relating to exercise intensity corresponding to the information.   Acquires frequency information and amplitude information of the received signal obtained by receiving the reflected wave related to the transmitted wave transmitted from the transmitter with the receiver, and supports the acquired frequency information, amplitude information, frequency information and amplitude information A human activity measurement program for causing a computer to execute a process of calculating exercise intensity of a person reflecting the transmitted wave based on information relating to exercise intensity to be performed.

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