Patent Publication Number: US-9901291-B2

Title: Activity meter and sleep/awake state recording system

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority from the prior Japanese Patent Application No. 2014-165262 filed in Japan on Aug. 14, 2014; the entire contents of which are incorporated herein by reference. 
     FIELD 
     An embodiment described herein relates generally to an activity meter and a sleep/awake state recording system. 
     BACKGROUND 
     There are proposals of systems configured to determine a human activity status or the like. For example, there is a system configured to attach an apparatus provided with an acceleration sensor to a target person whose activity status is determined and determine whether the target person is in a sleep state or an awake state based on an output of the acceleration sensor. 
     When a user who is a target person whose activity status is determined wears the apparatus on his/her arm, it is automatically determined whether the user is in a sleep state or an awake state from the output of the acceleration sensor. When such an activity meter of a type wearable on the user&#39;s body is attached to the body, it is possible to automatically determine whether the user is in a sleep state or an awake state. 
     However, the user may remove the activity meter from his/her body. When the user removes the activity meter from, for example, his/her arm and leaves the activity meter unattached, the activity meter is placed in an immobile or still state, resulting in a problem that the activity meter misjudges that the user is in a sleep state. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an outline view of a wristband-type activity meter  1  according to an embodiment; 
         FIG. 2  is a configuration diagram of a sleep/awake state recording system  100  made up of the wristband-type activity meter and a smartphone according to the embodiment; 
         FIG. 3  is a block diagram illustrating a configuration of the activity meter  1  of the embodiment; 
         FIG. 4  is a flowchart illustrating a flow example of a sleep/awake state determination process according to the embodiment; 
         FIG. 5  is a perspective view illustrating XYZ-axis directions when the activity meter  1  according to the embodiment is placed on a table surface  31   a  of a table  31 ; 
         FIG. 6  is a perspective view illustrating XYZ-axis directions when the activity meter  1  in the state in  FIG. 5  is turned over and placed on the table surface  31   a  of the table  31 ; 
         FIG. 7  is a graph illustrating output states of acceleration energy and Y-axis direction acceleration according to the embodiment; 
         FIG. 8  is a graph illustrating output states of acceleration energy and accelerations in three X-, Y- and Z-axis directions according to the embodiment; 
         FIG. 9  is a diagram illustrating an example of a sleep/awake estimation information table TBL stored in a RAM  23  according to the embodiment; 
         FIG. 10  is a graph of estimation results illustrating a situation in which errors are included in the estimation result according to the embodiment; and 
         FIG. 11  is a diagram for describing an estimation result correction method in the smartphone  2  according to the embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     An activity meter of an embodiment is an activity meter attachable to a target person whose activity amount is measured, including an acceleration sensor configured to detect acceleration in at least one axis direction, an acceleration energy detection section configured to detect acceleration energy based on an acceleration signal of the acceleration sensor, and a removal determining section configured to determine removal of the activity meter from the target person based on the acceleration energy detected by the acceleration energy detection section and an acceleration component in a direction of gravity in the acceleration signal of the acceleration sensor. 
     An activity meter of the embodiment is an activity meter attachable to a target person whose activity amount is measured, including an acceleration sensor configured to detect accelerations in at least three axis directions, an acceleration energy detection section configured to detect acceleration energy based on an acceleration signal of the acceleration sensor, and a removal determining section configured to determine removal (unattached state) of the activity meter from the target person based on the acceleration energy detected by the acceleration energy detection section and an acceleration component in a direction of gravity in the acceleration signal of the acceleration sensor. 
     A sleep/awake state recording system of the embodiment is a sleep/awake state recording system made up of an activity meter attachable to a target person whose activity amount is measured and a terminal communicable with the activity meter, in which the activity meter includes an acceleration sensor configured to detect acceleration in at least one axis direction, an acceleration energy detection section configured to detect acceleration energy based on an acceleration signal of the acceleration sensor, a removal determining section configured to determine removal of the activity meter from the target person based on the acceleration energy detected by the acceleration energy detection section and an acceleration component in a direction of gravity in the acceleration signal of the acceleration sensor, an awake state determining section configured to determine whether the target person is in an awake state or not based on a level of smoothness of the acceleration component in the direction of gravity in the acceleration signal of the acceleration sensor and the acceleration energy, a sleep state determining section configured to determine, except when the target person is determined to be in the awake state, that the target person is in a sleep state, a sleep/awake state storage section configured to record information on the sleep state and the awake state, and an information transmitting section configured to transmit information on the sleep state and the awake state stored in the sleep/awake state storage section, and the terminal includes a correction section configured to correct the information on the sleep state and the awake state received from the activity meter and a storage section configured to store the corrected information. 
     Hereinafter, an embodiment will be described with reference to the accompanying drawings. 
     (Configuration) 
       FIG. 1  is an outline view of a wristband-type activity meter  1  according to an embodiment.  FIG. 2  is a configuration diagram of a sleep/awake state recording system  100  made up of the wristband-type activity meter and a smartphone. 
     The activity meter  1  wearable on a target person whose activity amount is measured is a wristband-type device capable of recording an activity amount of the user who is the target person and transmitting the activity amount to a smartphone  2 . 
     The activity meter  1  is a band-shaped wristband type to be worn by being wrapped around the user&#39;s arm (shown by a dotted line) L and an elongated operation button  3  is provided in a center thereof. The operation button  3  is operated when making various settings or the like. 
     The activity meter  1  includes two extended portions  4   a  and  4   b  that extend from both sides of a central portion of a band  4  on which the operation button  3  or the like is arranged. A clasp  5  is provided at an end portion of the extended portion  4   a  and a plurality of holes  6  into which a protruding portion (not shown) of the clasp  5  is fitted are formed in the extended portion  4   b  at a predetermined interval. The user can wear the activity meter  1  on the arm L by fitting the protruding portion (not shown) formed in the clasp  5  into the hole  6  at an arbitrary position. 
     The operation button  3  is disposed in the activity meter  1  so as to come to the front side which is opposite to the back side face of the activity meter  1  in close contact with the arm L when the user wears the activity meter  1  on the arm L. 
     The sleep/awake state recording system  100  shown in  FIG. 2  is a sleep/awake state recording system using the activity meter  1 . 
     As will be described later, the activity meter  1  has a radio communication function and can transmit state information on a sleep state and an awake state which will be described later to the smartphone  2 . The user can transmit data of the state information on the sleep state and the awake state recorded in the activity meter  1  to the smartphone  2 , store the data in a memory of the smartphone  2 , and manage the data according to an application program stored in the smartphone  2  or display the data on a display section  2   a  of the smartphone  2 . 
     Note that the activity meter  1  has an acceleration sensor, generates, records or transmits activity data such as the user&#39;s activity amount and count of steps from the output of the acceleration sensor. Here, description of recording and transmission of such data is omitted and a sleep/awake state determination transmission process which is one of the functions of the activity meter  1  will be described. 
       FIG. 3  is a block diagram illustrating a configuration of the activity meter  1  of the present embodiment. 
     The activity meter  1  has a main unit  1 A including an operation button  3 , an acceleration sensor  11 , an acceleration detection section  12 , an acceleration energy detection section  13  and a control section  14 . In  FIG. 1 , as shown by a dotted line, the main unit  1 A is detachably attached to a central portion of the band  4 . 
     The activity meter  1  has an activity amount measuring function, a sleep state and awake state determining function which will be described later, a function of recording and transmitting the measured activity amount and a function of recording and transmitting state information on the determined sleep state and awake state. 
     The acceleration sensor  11  is a three-axis acceleration sensor which includes three sensors so as to be able to detect accelerations in three axis (X-axis, Y-axis and Z-axis) directions orthogonal to each other and outputs X-axis output, Y-axis output and Z-axis output as acceleration signals of the respective axes. Each output of the acceleration sensor  11  configured to detect accelerations in at least three axis directions is inputted to the acceleration detection section  12  and the control section  14 . 
     As shown in  FIG. 1 , when the activity meter  1  is worn on the user&#39;s arm L, the user can wear the activity meter  1  on the arm L so that the X-axis direction is parallel to a back of a hand H and orthogonal to an axis of the arm L, the Y-axis direction is parallel to the back of the hand H and parallel to the axis of the arm L, and the Z-axis direction is orthogonal to the back of the hand H. In  FIG. 1 , the arm L is passed through the ring-shaped band  4  of the activity meter  1  so that the arm L is oriented from the front toward the back of the sheet. 
     The acceleration detection section  12  includes a square root of sum of squares calculation section  12   a  and a high pass filter (HPF)  12   b.    
     The square root of sum of squares calculation section  12   a  is a circuit configured to generate a signal of the square root of sum of squares of each output of the acceleration sensor  11 . Here, since accelerations in a plurality of directions (here, three directions) are used, the square root of sum of squares calculation section  12   a  configured to generate a signal of the square root of sum of squares of each output is used, but a sum of squares calculation circuit configured to generate a signal of sum of squares may be used instead of the square root of sum of squares calculation section  12   a.    
     The high pass filter  12   b  is an offset canceller circuit configured to remove gravity acceleration from the output of the square root of sum of squares calculation section  12   a.    
     Note that the acceleration sensor  11  is a three-axis acceleration sensor here, but the acceleration sensor  11  may also be a 4- or more-axis acceleration sensor. 
     Thus, the acceleration detection section  12  detects acceleration from the output of the acceleration sensor  11  and outputs an acceleration signal. The acceleration signal outputted from the acceleration detection section  12  is inputted to the acceleration energy detection section  13 . 
     The acceleration energy detection section  13  includes an absolute value circuit  13   a  and a low pass filter  13   b , and detects acceleration energy based on the acceleration signal of the acceleration sensor  11 . 
     The acceleration signal inputted to the acceleration energy detection section  13  is inputted to the absolute value circuit  13   a . The absolute value circuit  13   a  calculates an absolute value of the inputted acceleration signal and outputs the absolute value to the low pass filter  13   b.    
     The low pass filter  13   b  averages the output of the absolute value circuit  13   a , detects an intensity of acceleration and outputs the intensity to the control section  14 . Thus, the acceleration energy detection section  13  constitutes an acceleration intensity detection section configured to detect an intensity of acceleration from the acceleration signal from the acceleration detection section  12 . 
     The control section  14  includes a central processing unit (hereinafter referred to as “CPU”)  21 , a ROM  22 , a RAM  23 , a clock section  24 , a radio communication section  25  and interfaces (hereinafter abbreviated as “I/F”)  26 ,  27  and  28 , which are connected to each other via a bus  29 . 
     The CPU  21  can acquire the output of the acceleration energy detection section  13  via the I/F  26 . 
     Similarly, the CPU  21  can acquire an X-axis output, Y-axis output and Z-axis output of the acceleration sensor  11  via the I/F  27 . 
     Furthermore, the CPU  21  can acquire an operating state of the operation button  3  via the I/F  28 . 
     The ROM  22  of the control section  14  stores an awake/sleep state determining processing program which will be described later. Note that the ROM  22  may also be a rewritable non-volatile memory such as a flash memory. 
     The clock section  24  is a circuit configured to generate and output time information, and the CPU  21  can acquire information on dates and times from the clock section  24 . 
     The radio communication section  25  is a circuit configured to carry out data communication with the smartphone  2  and is a circuit configured to carry out short-distance radio communication. 
     The activity meter  1  has the above-described configuration and is worn on the user&#39;s arm, and can determine whether the user is in a sleep state or an awake state, record and transmit the determination result to the smartphone  2 . 
     (Operation) 
     A sleep/awake state determination process will be described. 
       FIG. 4  is a flowchart illustrating a flow example of the sleep/awake state determination process. A sleep/awake state determination is made by the CPU  21  reading the sleep/awake state determination processing program from the ROM  22  and developing and executing the program on the RAM  23 . For example, when a sleep/awake information acquisition mode is set, the sleep/awake state determination processing program is executed. The process in  FIG. 4  is executed in a predetermined cycle, for example, in one-second cycle. 
     The CPU  21  reads the acceleration data inputted in a predetermined cycle (S 1 ). Here, respective acceleration signals in the X-, Y- and Z-axis directions of the acceleration sensor  11  are sampled at predetermined sampling timing, for example, at timing of several tens of times per second and inputted to the CPU  21  and stored in the RAM  23 . 
     The CPU  21  calculates a time average of respective accelerations in the X-, Y-, Z-axis directions (S 2 ). That is, to remove a noise component, the CPU  21  calculates an average value for a predetermined time, for example, an average value of data for several seconds for read value data of the respective acceleration signals in the X-, Y-, Z-axis directions. 
     Furthermore, the CPU  21  acquires data of acceleration energy AE from the output of acceleration energy detection section  13  (S 3 ). 
     Next, the CPU  21  determines whether the user removes the activity meter  1  form the arm or not (S 4 ). 
     The determination in S 4  is made based on whether the acceleration energy AE is equal to or less than a predetermined value TH 1  and whether an absolute value |Ya| of the Y-axis acceleration Ya which is a time average value of the acceleration signal in the Y-axis direction exceeds a predetermined value TH 2  or not. That is, it is determined whether the activity meter  1  is removed from the arm depending on whether the following expression (1) holds or not. The predetermined value TH 1  is an extremely small value and is a value at a level that it is possible to detect that the activity meter  1  is at rest. The predetermined value TH 2  is a large value among output levels of the Y-axis acceleration Ya and the largest value is a value detected when the Y-axis direction matches the direction of gravity when the activity meter  1  is at rest.
 
( AE≦TH 1) and (| Ya|&gt;TH 2)  (1)
 
     When the above expression (1) holds, it is determined that the user is awake. 
     This is because in addition to the fact that the user&#39;s activity amount is extremely small, with acceleration energy AE being equal to or less than the predetermined value TH 1 , the magnitude of acceleration in the direction of gravity, the Y-axis direction here, exceeds the predetermined value TH 2 , and it is thereby possible to estimate that the activity meter  1  is placed on, for example, a desk. 
       FIG. 5  is a perspective view illustrating the XYZ-axis directions when the activity meter  1  is placed on a table surface  31   a  of a table  31 .  FIG. 6  is a perspective view illustrating the XYZ-axis directions when the activity meter  1  in  FIG. 5  is turned over and the activity meter  1  is placed on the table surface  31   a  of the table  31 . 
     As shown in  FIG. 5  and  FIG. 6 , when placed on a flat surface such as the table surface  31   a  of the table  31 , the Y-axis direction of the band-type activity meter  1  becomes orthogonal to the table surface  31   a . For this reason, when the activity meter  1  is removed from the user&#39;s arm and left unattached on the table  31  or the like, the acceleration Ya in the Y-axis direction, that is, the direction of gravity increases. 
     Since the activity meter  1  is removed from the user&#39;s arm, the acceleration energy AE is small and the absolute value of acceleration in the direction of gravity increases. 
     Note that an example has been described in  FIG. 5  and  FIG. 6  where the Y-axis direction is orthogonal to the table surface  31   a , but without being limited to this, for example, the Z-axis direction becomes orthogonal to the table surface  31   a  when, for example, the activity meter  1  is placed such that the operation button  3  comes into contact with the table surface  31   a . In this case, the acceleration Za in the Z-axis direction increases. 
     As described above, the process in S 4  constitutes a removal determining section configured to determine removal of the activity meter  1  from the user, that is, an unattached state, based on the acceleration energy AE detected by the acceleration energy detection section  13  and an acceleration component in the direction of gravity in the acceleration signal of the acceleration sensor  11 . In the process in S 4 , when the acceleration energy AE is equal to or less than the predetermined value TH 1  and the acceleration component in the direction of gravity is equal to or greater than the predetermined value TH 2 , it is determined that the activity meter  1  is removed from the user. 
     Thus, as a result of the determination in S 4 , when it is determined that the user removes the activity meter  1  from the arm (S 4 : YES), the CPU  21  determines that the user removes the activity meter  1  from the arm and is in an awake state (S 5 ). 
     When it is determined that the user does not remove the activity meter  1  from the arm (S 4 : NO), the CPU  21  determines whether the acceleration energy AE is equal to or greater than a predetermined value TH 3  (S 6 ). 
     When the acceleration energy AE is not equal to or greater than the predetermined value TH 3  (S 6 : NO), the CPU  21  determines that the user is in a sleep state (S 7 ). That is, although the user wears the activity meter  1  on the arm, the acceleration energy AE is small, and so it is determined that the user is in a sleep state. 
     When the acceleration energy AE is equal to or greater than the predetermined value TH 3  (S 6 : YES), the CPU  21  calculates a level of smoothness of the value of the acceleration energy AE (S 8 ). 
     Here, the level of smoothness FL(i) defined in the following expression (2) is calculated. 
     
       
         
           
             
               
                 
                   
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     Here, FL(i) is the level of smoothness at a time i. 
     More specifically, FL(i) in expression (2) is the sum total of a first sum of a difference between each of m (m is an integer) portions of acceleration energy up to an mth portion before acceleration energy AE(i) at a time i and the acceleration energy AE(i) at the time i, and a second sum of a difference between each of the m (m is an integer) portions of acceleration energy up to the mth portion after the acceleration energy AE(i) at the time i. 
     Note that although the level of smoothness is calculated according to the calculation expression defined in expression (2) here, the level of smoothness may be calculated by other means such as calculating the level of smoothness from the sum of a difference between each of m (m is an integer) portions of acceleration energy up to the mth portion before acceleration energy AE(i) at the time i and the acceleration energy AE(i) at the time i. 
     After S 8 , the CPU  21  determines whether the level of smoothness is equal to or less than a predetermined value TH 4  or not (S 9 ). The fact that the level of smoothness in expression (2) is equal to or less than the predetermined value TH 4  means that the acceleration energy values are substantially constant when these values are time-sequentially arranged in a graph and that the level of smoothness of the values of the acceleration energy AE is high. Thus, the value of the predetermined value TH 4  is an extremely small value. The predetermined value TH 4  is an extremely small value and is a value at a level that the acceleration energy AE can be considered substantially invariable. 
     When the level of smoothness is equal to or less than the predetermined value TH 4  (S 9 : YES), that is, when the change in the acceleration energy value is small, the CPU  21  determines that the user is in a sleep state (S 10 ). The fact that the level of smoothness FL(i) which is the sum total of the first sum and the second sum is small in S 9  means that the acceleration energy AE is equal to or greater than the predetermined value TR 3 , but does not substantially change, that is, a constant state in which accelerations in the X-axis, Y-axis and Z-axis directions do not change, and so it is determined that the user is in a sleep state. 
     When the acceleration energy AE is large because the body motion when the user is asleep is large, the processes in S 8  and S 9  prevent the activity meter  1  from misjudging that the user is awake. 
     When the level of smoothness is not equal to or less than the predetermined value TH 4  (S 9 : NO), the CPU  21  determines that the user is in an awake state (S 11 ). That is, the fact that the level of smoothness FL(i) which is the sum total of the first sum and the second sum is not small means that the acceleration energy AE is large and changing a great deal, that is, the state is not a constant state in which accelerations in the X-axis, Y-axis and Z-axis directions are not changing, and so the user is determined to be in an awake state. 
       FIG. 7  is a graph illustrating output states of acceleration energy and Y-axis direction acceleration. In the graph in  FIG. 7 , the horizontal axis denotes a time t and indicates changes in the acceleration energy AE and the Y-axis direction acceleration Ya over time actually measured with the activity meter  1  worn on a certain examinee&#39;s arm. 
     A graph GA on the top row of  FIG. 7  is a graph of values of the acceleration energy AE and a graph GB on the bottom row of  FIG. 7  is a graph of values of the Y-axis direction acceleration Ya. 
     In  FIG. 7 , a period T 1  is a period while the examinee removes the activity meter  1  from the arm, a period T 2  is a commuting time period, a period T 3  is a period while the examinee is out, a period T 4  is a commuting time period, a period T 5  is a sleeping time period and a period T 6  is a commuting time period. During the period T 1 , the acceleration energy AE has a small value and the Y-axis direction acceleration Ya has a large value. In contrast, during the period T 5 , the acceleration energy AE has a small value, but the Y-axis direction acceleration Ya of a time average has a smaller value than that during the period T 1  and fluctuates. 
     According to the aforementioned process in S 4 , since the examinee is not in a sleep state and the activity meter  1  is removed from the arm and left unattached during the period T 1 , it is possible to determine that the user is awake. 
       FIG. 8  is a graph illustrating output states of acceleration energy and accelerations in the three X-, Y- and Z-axis directions. In the graph in  FIG. 8 , the horizontal axis denotes a time t showing changes in the acceleration energy AE and accelerations Xa, Ya and Za in the three X-, Y- and Z-axis directions over time on one day actually measured with the activity meter  1  worn on the examinee&#39;s arm. 
     A graph GA 1  on the top row in  FIG. 8  is a graph showing acceleration energy AE values, a graph GB 1  on the second row in  FIG. 8  is a graph showing X-axis direction acceleration Xa values, a graph GB 2  on the third row in  FIG. 8  is a graph showing Y-axis direction acceleration Ya values and a graph GB 3  on the bottom row in  FIG. 8  is a graph showing Z-axis direction acceleration Za values. 
     In  FIG. 8 , a period TT 1  is a time period while the examinee is asleep. 
     Since the state in which the examinee is immobile continues within the period TT 1  as shown in  FIG. 8 , there are a plurality of periods during which acceleration values in the X, Y and Z axes are constant. In the graph GB 1  in  FIG. 8 , the period CT shows a period during which acceleration values do not change and remain constant during the period TT 1 . In the graphs GB 2  and GB 3 , there are also a plurality of periods during which acceleration values are constant. Since the user remains immobile after tossing and turning in bed, the acceleration values in the X, Y and Z axes become constant before and after tossing and turning, and the graphs GB 1 , GB 2  and GB 3  during the period TT 1  show stepped waveforms as shown in  FIG. 8 . 
     Since the acceleration values do not change and are constant in the respective X-axis direction, Y-axis direction and Z-axis direction as well, the graph GA 1  during the period TT 1  becomes substantially flat. 
     When the acceleration energy AE value is equal to or greater than the predetermined value TH 3 , the aforementioned levels of smoothness in S 8  and S 9  are processes to determine whether such a graph GA 1  is flat or not. When the level of smoothness calculated in S 8  is small, that is, when the graph GA 1  is flat, the CPU  21  determines that the user is in a sleep state (S 10 ), and does not make erroneous determinations that the user is in an awake state. 
     Conversely, when the level of smoothness calculated in S 8  is not small, that is, when the graph GA 1  is not flat, the CPU  21  can determine that the user is in an awake state (S 11 ). As described above, it is determined, based on the acceleration energy AE value and the level of smoothness of the acceleration energy AE, whether the user is in a sleep state or in an awake state. 
     As described above, the processes in S 8 , S 9  and S 11  constitute an awake state determining section configured to determine whether the user is in an awake state or not based on the level of smoothness of the acceleration component in the direction of gravity and the acceleration energy AE in the acceleration signal of the acceleration sensor  11 . The level of smoothness is defined by whether the change in the acceleration energy AE value falls within a predetermined value or not. When the acceleration energy AE is equal to or greater than the predetermined value TH 3  and the change in the acceleration energy AE value is equal to or greater than a predetermined value, it is determined that the user is in an awake state (S 11 ). In  FIG. 4 , it is determined that the user is in a sleep state (S 7 , S 10 ) except when it is determined that the user is in an awake state (S 5 , S 11 ). 
     As described above, the process in  FIG. 4  is executed at a predetermined period, for example, at one-second intervals and information on the determination result is stored in the RAM  23  as an estimation result. 
       FIG. 9  is a diagram illustrating an example of a sleep/awake estimation information table TBL stored in the RAM  23 . As shown in  FIG. 9 , the sleep/awake estimation information table TBL includes data such as dates, times and estimation results. 
     When the CPU  21  determines an awake state or a sleep state through the process in  FIG. 4 , the CPU  21  additionally records the determination result together with information on the date and time of the clock section  24  in the sleep/awake estimation information table TBL of the RAM  23  as the estimation result. 
     Thus, the RAM  23  constitutes a sleep/awake state storage section configured to record information on the user&#39;s sleep state and awake state. 
     The CPU  21  transmits the information on the sleep/awake estimation information table TBL from the radio communication section  25  to the smartphone  2  at predetermined timing. The predetermined timing may be timing in a preset time period in the activity meter  1  or timing of a transmission request from the smartphone  2 . 
     Thus, the radio communication section  25  constitutes an information transmitting section configured to transmit information on a sleep state and an awake state stored in the RAM  23 . 
     The smartphone  2  may display data of the estimation result of the received sleep/awake estimation information table TBL on the display section  2   a  as is or in a table or graph or the like, but may also correct the received estimation result and display it on the display section  2   a  in a table or graph or the like. 
     For example, an application program of the smartphone  2  can show data of the estimation result of the sleep/awake estimation information table TBL in a table format or in a graph. 
     The data of the estimation result of the sleep/awake estimation information table TBL is, for example, per-second data and is generated at short time intervals. For this reason, the estimation result may contain errors. 
       FIG. 10  is a graph of the estimation result illustrating a situation in which the estimation result contains errors. 
     In a graph GR 1  in  FIG. 10 , the horizontal axis denotes a time t and shows a change in a determination result of an awake state and a sleep state transmitted from the activity meter  1  at each time. On the top row in  FIG. 10 , points (shown by rhombuses) indicating determinations as awake state are plotted, from which it is not possible to clearly distinguish between the sleep state and the awake state. 
     Thus, for example, the estimation result of the activity meter  1  may be corrected by a majority decision of adopting more numerous determination results within a predetermined time period before and after a certain time as the determination results so as to determine the sleep state and the awake state at that time. 
       FIG. 11  is a diagram for describing an estimation result correction method in the smartphone  2 . As shown in  FIG. 11 , regarding a determination result at a target time Ti to be determined, the number of estimation results determined as a sleep state is compared with the number of estimation results determined as an awake state based on determination results (shown by black circles) of a TC period before and after the time Ti, and the more numerous determination results are assumed to be the determination results at the target time Ti. 
     A graph GR 2  in  FIG. 10  is a graph of an estimation result corrected using the method in  FIG. 11 . From the graph GR 2 , it is possible to clearly distinguish between the sleep state and the awake state. 
     Furthermore, as the corrected estimation result, a start time and an end time of a sleep state, and a start time and an end time of an awake state may be displayed on the display section  2   a  of the smartphone  2  in a table format. 
     Therefore, the smartphone  2  corrects information on the sleep/awake estimation result so as to remove errors, and can thereby more accurately determine the user&#39;s awake state and sleep state and record the determination result as data. 
     As described above, according to the aforementioned embodiment, it is possible to provide an activity meter which prevents, even when the activity meter is removed from the user and left unattached, an erroneous decision that the user is in a sleep state. 
     Moreover, it is possible to provide an activity meter that prevents, even when the user moves his/her body during a sleep, a misjudgment that the user is in an awake state. 
     Note that according to the aforementioned embodiment, the process in  FIG. 4  is implemented by a software program which is executed by the CPU  21 , but the process may be implemented also by a hardware circuit. 
     While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions.