JP5958588B2 - Motion analysis device, motion analysis method - Google Patents

Description

  The present invention relates to a trajectory analysis apparatus and a trajectory analysis method for analyzing the behavior of an object.

  Conventionally, motion capture has been widely known as a method for analyzing the motion of an object or a human. However, motion capture has limited usage conditions depending on the method, such as when a dedicated studio is required or special equipment is required. In addition, it is disclosed as a tennis racket that a plurality of acceleration sensors, or acceleration sensors and gyro sensors are provided at a part of an object to be measured, and a motion analysis of the object is performed from acceleration and angular velocity data of the measurement part. (Patent Document 1).

JP 2009-125499 A

  However, in the acceleration sensor used in the above-mentioned Patent Document 1, the dynamic range that can be detected by the sensor, in other words, the maximum acceleration and the detection accuracy are in a trade-off relationship. Therefore, for example, when using an acceleration sensor with a low dynamic range, it is possible to detect a slow movement with high accuracy, but for a fast movement, the sensor characteristics become saturated and an accurate movement is captured. It becomes impossible to do.

  On the other hand, when a sensor with a high dynamic range is used, even a fast movement can be detected, but there is a problem that fine data cannot be obtained for a slow movement. Therefore, for example, in sports involving slow movement and fast movement such as tennis, even if a tennis racket having a sensor disclosed in Patent Document 1 is operated, accurate movement data over the entire movement range of the racket is obtained. It was difficult to obtain the product, and it was impossible to make appropriate improvements to the form and to determine the suitability of the equipment, which reduced the user's physical burden and technical improvement. .

  Therefore, a trajectory analysis apparatus and a trajectory analysis method that can accurately detect a minute motion to a large motion are provided.

  The present invention can be realized as the following forms or application examples so as to solve at least one of the above-described problems.

Application Example 1 A trajectory analysis apparatus according to this application example includes an attitude detection unit that includes an inertial sensor that is fixed to the object A and includes an angular velocity sensor and at least two acceleration sensors having different dynamic ranges. A data I / F unit for amplifying the detection data acquired by the unit and A / D converting; a calculation unit for processing data from the data I / F unit; and the acceleration sensor based on a calculation result from the calculation unit A sensor control unit that generates a control signal for selecting one of the acceleration sensors, and posture data is generated from output data from the inertial sensor including the acceleration sensor selected by the control data from the sensor control unit. A posture detection device including a posture data generation unit to be transmitted, and an analysis unit that analyzes the posture data from the posture detection device An analysis device comprising: a storage unit that stores the posture data and the analysis result; a notification unit that notifies the analysis result; and a communication unit between the posture detection device and the analysis device. To do.
In another aspect, the sensor control unit that selects output data from the first acceleration sensor and the second acceleration sensor having different dynamic ranges, and the analysis data using the output data selected by the sensor control unit It is characterized by generating. The sensor control unit selects the output data from the first acceleration sensor and the second acceleration sensor based on the magnitude of acceleration. A level correction unit that corrects discontinuous data at the time of switching output data of the first acceleration sensor and the second acceleration sensor into continuous data is provided. A data I / F unit that includes the first acceleration sensor and the second acceleration sensor, and that performs analog-digital conversion on output data acquired by the first acceleration sensor and the second acceleration sensor, and from the data I / F unit A calculation unit that processes the data, wherein the sensor control unit selects the output data based on a calculation result from the calculation unit. An angular velocity sensor is provided, and posture data is generated using at least two output data of the first acceleration sensor, the second acceleration sensor, and the angular velocity sensor.

  According to the application example described above, the posture data of the object is detected in the optimum measurement range range of the high and low dynamic range sensors, and is used as the trajectory analysis data, so that the posture with high accuracy from the gentle movement to the fast movement can be obtained. Data can be obtained. Therefore, this highly accurate posture data can be analyzed by the trajectory analyzer, and the measurement result can be notified to the measurer. Based on the notified result, for example, it is possible to improve the form when using sports equipment, and to determine suitability of the equipment.

  The object A is, for example, a racket such as tennis, squash or badminton, a golf club, a baseball bat, an ice hockey stick, a billiard cue, a hammer throwing hammer, a kite throwing kite, a canoe, a kayak or the like, For example, there are tools that players (humans) have in their hands. Further, examples of the object A include tools that people ride on and operate such as skiing, snowboarding, surfing board, and sled. Furthermore, humans themselves, such as skydiving and swimming, can be cited as targets.

  Application Example 2 In the application example described above, the angular velocity sensor is a triaxial angular velocity sensor, and the acceleration sensor is a triaxial acceleration sensor.

  According to the application example described above, it is possible to accurately detect the posture and trajectory of the object A, which is a complicated target.

  Application Example 3 In the application example described above, the acceleration sensor is a high dynamic range sensor having a dynamic range of + 20G to −20G and a low dynamic range sensor having a dynamic range of + 5G to −5G. Features.

  According to the application example described above, in the low dynamic range sensor, acceleration is performed in a trajectory range in which the object A is slowly moved from a stationary state and in a trajectory range in which the motion is stopped after the motion peak is stopped. It is possible to accurately detect even a slight change in. Further, the high dynamic range sensor can reliably detect the peak value of acceleration in the trajectory range in which the object A of the object is moved quickly before and after the peak of motion.

Application Example 4 A trajectory analysis method according to this application example includes an angular velocity sensor provided in an inertial sensor fixed to an object A, a low dynamic range sensor having a relatively low dynamic range of at least two acceleration sensors, and Initial motion detecting means for detecting the behavior of the object A by the sensor, and when the detection data in the initial motion detecting means exceeds the dynamic range region of the low dynamic range sensor, the relatively high dynamic of the acceleration sensor When switching to a high dynamic range sensor having a range and detecting the behavior of the object A, and the detection data in the medium motion detection means are within the dynamic range region of the low dynamic range sensor, Switch to the low dynamic range sensor Characterized in that it comprises a, and late movement detecting means for detecting the behavior of the object A.
In another aspect, a first motion detection stage by a first acceleration sensor having a relatively low dynamic range of at least two acceleration sensors, and detection of the first acceleration sensor in the first motion detection stage A motion analysis method comprising: a second motion detection step of detecting by switching to a second acceleration sensor having a relatively high dynamic range of the at least two acceleration sensors when the data exceeds a threshold value. It is characterized by. A third motion detection step of detecting by switching to the first acceleration sensor when the detection data of the second acceleration sensor in the second motion detection step falls within the dynamic range region of the first acceleration sensor; It is characterized by including.

  According to the application example described above, even in the trajectory range in which the object A is moved slowly from the stationary state, and in the trajectory range in which the motion is stopped until the motion is stopped beyond the peak of motion, even a slight change in acceleration is accurate. By switching between the low dynamic range sensor that detects the current and the high dynamic range sensor that reliably detects the peak value of acceleration in the trajectory range in which the object A of the object moves quickly before and after the peak of motion, Data enabling trajectory analysis can be acquired.

Application Example 5 In the application example described above, the detection start of the high dynamic range sensor switched to the detection final data of the low dynamic range sensor when the initial motion detection means is switched to the high dynamic range sensor. Level correction for matching the data and matching the detection final data of the switched high dynamic range sensor to the detection start data of the low dynamic range sensor when switching to the low dynamic range sensor in the medium-term motion detection means A process is provided.
In another aspect, when the first acceleration sensor is switched to the second acceleration sensor, the detection start data of the second acceleration sensor switched to the final detection data of the first acceleration sensor is matched. A one-level correction step is provided. A second level correction step of matching the detection final data of the second acceleration sensor switched to the detection start data of the first acceleration sensor when the second acceleration sensor is switched to the first acceleration sensor; It is characterized by.

  According to the application example described above, detection data that becomes discontinuous data by switching the sensor is converted into continuous data by level correction, and the trajectory analysis result can be notified as a continuous trajectory.

The block diagram which shows the basic system structure based on 1st Embodiment. The top view of the tennis racket based on 1st Embodiment. The conceptual diagram explaining the track | orbit of a tennis racket. A graph representing detection data that conceptually explains the characteristics of a low dynamic range sensor and a high dynamic sensor. Flow explanatory drawing of the orbital analysis method based on 2nd Embodiment. The graph showing the detection data which conceptually demonstrates attitude | position detection data based on 2nd Embodiment. The graph showing the detection data which conceptually demonstrates attitude | position detection data based on 2nd Embodiment. The graph showing the detection data which illustrates conceptually the attitude | position detection data based on a modification.

  Embodiments according to the present invention will be described below with reference to the drawings.

(First embodiment)
FIG. 1 is a block diagram showing the basic system configuration of the first embodiment according to the present invention. The trajectory analysis apparatus 1000 according to the present embodiment includes an attitude detection apparatus 100 fixed to an object to be measured, and an analysis apparatus 200 that receives data transmitted from the attitude detection apparatus 100 wirelessly and notifies the analysis and the result. In the present embodiment, as shown in FIG. 2, the posture detection device 100 is fixed to the end portion 300c of the grip 300a of the tennis racket 300, and the trajectory analysis of the tennis racket 300 will be described as an example.

  As is well known, the tennis racket 300 is a sport in which the player grips the grip 300 a and hits the ball with the gut surface 300 b of the tennis racket 300. At this time, the player is always required to strike back the ball accurately at the target position (in the opponent's court), and for that purpose, can the tennis racket 300 be swung while drawing a stable swing path of the tennis racket 300? Depends on. In order to perform this accurate swing, the proficiency level of the player himself, the balance of the tennis racket 300 itself, the suitability (ease of handling) of the player and the tennis racket 300, and the like are related. The objective function of the first embodiment according to the present invention is to detect and analyze the trajectory drawn by the tennis racket 300 and quantitatively evaluate these influence factors.

  The posture detection device 100 included in the trajectory analysis device 1000 is fixed to the tennis racket 300 as described above. In this embodiment, the posture detection device 100 is fixed to the end portion 300c of the grip 300a. However, the posture detection device 100 may be fixed to a position 300d that is substantially the center of the tennis racket 300, for example. However, since a slight difference in the balance of the tennis racket 300 affects the player, it is preferable to fix the posture detection device 100 to the end portion 300c of the grip 300a that has little influence on the balance as in this embodiment.

  The posture detection device 100 includes data including a posture detection unit 20 including an inertial sensor 10 that detects the posture and acceleration of the tennis racket 300, and an A / D converter that converts analog data sent from the posture detection unit 20 into digital data. An I / F 30 and a calculation unit 40 including a CPU that calculates data from the data I / F 30 are included.

  The inertial sensor 10 includes a triaxial angular velocity sensor 50 (hereinafter referred to as an angular velocity sensor 50) that detects the attitude of the tennis racket 300, and triaxial acceleration sensors 61 and 62 that detect acceleration during the swing of the tennis racket 300. . The triaxial acceleration sensors 61 and 62 have different dynamic ranges, so-called detectable acceleration areas, and the triaxial acceleration sensor 61 has a performance in the dynamic range of + 5G to −5G (G: gravitational acceleration). 62 has a dynamic range of + 20G to −20G. In the following description, in order to clarify the functions of the two three-axis acceleration sensors 61 and 62, the three-axis acceleration sensor 61 is referred to as a low dynamic range sensor 61, and the three-axis acceleration sensor 62 is referred to as a high dynamic. The range sensor 62 is referred to.

  The posture detection apparatus 100 further includes a posture data generation unit 70 that creates control data for sensor control in an analysis method described later from the calculation result obtained by the calculation unit 40, and a posture generated by the posture data generation unit 70. A low dynamic range sensor 61, a high dynamic range sensor 62, and a sensor control unit 80 that controls the angular velocity sensor 50 are provided based on the data. In addition, since transmission of data from the posture detection device 100 to the analysis device 200 is performed by wireless communication means in this embodiment, a transmission unit 90 is further provided.

  The trajectory data of the tennis racket 300 detected by the posture detection device 100 is transmitted from the transmission unit 90 to the analysis device 200. The analysis device 200 notifies the observer of the analysis result based on the transmitted data. The analysis device 200 receives the wireless data transmitted from the attitude detection device 100, and analyzes the received data. An analysis unit 220 including a CPU for performing analysis, a memory for storing analysis results, an operation unit 230 for instructing work in the analysis unit 220, and a notification unit 240 for notifying an observer of the analysis results in the analysis unit 220. It is out.

  In FIG. 3 schematically showing the trajectory of the swing of the tennis racket, the trajectory A of the tennis racket 300 is a trajectory a1 at the time of slow motion take-back, that is, the initial motion detection and until the ball is hit. It is composed of a trajectory a2 at the time of detecting an intermediate motion of a fast movement and a trajectory a3 at the time of detecting a late motion of the follow that gradually moves gradually after hitting the ball. In order to detect and analyze the trajectory A, the trajectory analysis apparatus 1000 includes a low dynamic range sensor 61 and a high dynamic range sensor 62 in the posture detection apparatus 100, and is suitable for detecting the trajectories a1 and a3 having gentle movements. Further, by measuring with the low dynamic range sensor 61 and measuring with the high dynamic range sensor 62 for detecting the trajectory a2 having a fast movement, the data of the trajectory A can be obtained with high accuracy.

  Here, an outline of the characteristics of the low dynamic range sensor 61 and the high dynamic range sensor 62 will be described. 4A and 4B are conceptual diagrams showing sensor characteristics. FIG. 4A shows, for example, the detection characteristics of the gentle movement trajectory a1 in FIG. 3, and FIG. 4B shows the detection characteristics of the fast movement trajectory a2. ing.

4A, the detection result of the low dynamic range sensor 61 having the measurable range _RL is L1, and the detection result of the high dynamic range sensor 62 having the measurable range _RH is H1. As can be seen from this figure, L1 can acquire data over the details of the detection result, and can also detect small changes in acceleration. However, in H1, even a measurement result of the same trajectory a1 cannot capture a small change in acceleration, but can only capture a trend value of the entire data, and only a low-accuracy result can be obtained. Therefore, in order to acquire data of the slowly moving trajectory a1, it is preferable to measure using the low dynamic range sensor 61.

However, when the trajectory a2 moves quickly, the detection result L2 of the low dynamic range sensor 61 becomes saturated and becomes trapezoidal when the measurable range _RL is exceeded, as shown in FIG. 4B. , L2 ′ data cannot be captured and true peak data cannot be measured. However, the detection result H2 of the high dynamic range sensor 62 can capture the peak value although it is difficult to capture the fine undulation of the data as described above. Therefore, in order to acquire the data of the trajectory a2 having a fast movement, it is preferable to measure using the high dynamic range sensor 62.

  Therefore, even if the movement speed of the measurement object changes greatly, by using an acceleration sensor with a different dynamic range according to the magnitude of the movement speed, detailed data of slow movement and peak data of fast movement can be accurately obtained. It becomes possible to capture.

(Second Embodiment)
As a second embodiment, a trajectory analysis method by the trajectory analysis apparatus 1000 of the first embodiment will be described. FIG. 5 is an explanatory diagram of a posture detection flow in the posture detection apparatus 100 in the trajectory analysis method according to the present embodiment, and FIGS. 6 and 7 are graphs schematically showing data detected by the posture detection apparatus 100.

The posture detection apparatus 100 attached to the tennis racket 300 of the first embodiment has a low dynamic range sensor 61 having a dynamic range R _L performance in the range shown in FIG. 6A and a dynamic range R _H performance. Two three-axis acceleration sensors of the high dynamic range sensor 62 are provided.

  When the trajectory analysis is started, that is, when the tennis racket 300 starts swinging by the player, when the initial motion of the trajectory a1 shown in FIG. 3 is detected, the angular velocity sensor 50 and the low dynamic range sensor 61 are first started to measure, Detection data is transmitted toward the analysis apparatus 200 (S10). In S10, as shown in FIG. 6 (a), since it is the detection data of the low dynamic range sensor 61, it is possible to acquire detection data with high accuracy, and the tennis racket 300 in the present embodiment that is the target object. Detection data D1 that substantially matches the virtual line D ′ representing the detection data of the posture detection apparatus 100 corresponding to the assumed trajectory can be acquired.

When the detection data D1 of the low dynamic range sensor 61 exceeds the dynamic range _RL, as described above, the low dynamic range sensor 61 is saturated, and accurate data acquisition becomes difficult. Therefore, a threshold value ± X is set as a threshold value in the vicinity that does not exceed the dynamic range _RL . It is determined whether the detection data D1 of the low dynamic range sensor 61 has exceeded the threshold value ± X (S20). It is determined as “No” in S20, and the detected data D1 is acceleration data by the low dynamic range sensor 61 until the tennis racket 300 is determined to be moving in the motion detection (S200) until the threshold value ± X is exceeded. Is acquired.

The movement of the racket 300 is moved quickly when the medium-term movement of the trajectory a2 shown in FIG. 3 is detected, and when the detection data D1 exceeds the threshold value ± X in S20, that is, when “Yes” is determined, the high dynamic range sensor 62 Detection of acceleration is started (S30). When measurement of the high dynamic range sensor 62 in S30 is started, measurement of acceleration by the low dynamic range sensor 61 is subsequently stopped (S40). As shown in FIG. 6B, the data of the high dynamic range sensor 62 that has started the measurement in S30 obtains detection data D2 including a detection value peak in the range of the dynamic range _RH .

  Next, level correction 1 (S50) is performed. Level correction 1 (S50) is to correct the detection data D2 of the switched high dynamic range sensor 62 on the basis of the detection data D1 of the low dynamic range sensor 61. Level correction 1 (S50) is switched to the measurement of the high dynamic range sensor 62 at the point p1 where the detection data D1 exceeds the threshold value X by the command of S30, as shown in the partial enlarged view of the M part in FIG. 6B. Until the measurement start point p2, the time t1 is slightly passed. Due to the elapsed time t1, a discontinuous portion occurs in the detection data D1 and the detection data D2. The level correction 1 (S50) is to make this discontinuous data continuous.

  In the correction method of level correction 1 (S50), correction is performed so that the start point data point p2 of the detection data D2 coincides with the data point p3 of the reference detection data D1 after the lapse of t1, and correction data D2 ′ is generated. To do. During this time, the high dynamic range sensor 62 continues to measure, and as shown in FIG. 7C, after the detection data D2 is measured, the detection value decreases, the detection data D3 is detected, and the analysis device 200 detects the detection data. Is transmitted (S60). At this time, the switching determination from the high dynamic range sensor 62 to the low dynamic range sensor 61 is performed in the same manner as the switching determination from the low dynamic range sensor 61 to the high dynamic range sensor 62 in S20 (S70).

In S70, it is determined whether a threshold value ± Y that is the same as or slightly over the dynamic range _RL is set, and the detection data D3 of the high dynamic range sensor 62 is within the set threshold value ± Y region. The acceleration data from the high dynamic range sensor 62 is acquired while “No” is determined in S70, that is, until the detection data D3 enters the region of the threshold value ± Y.

When the latter stage motion of the trajectory a3 shown in FIG. 3 is detected, the tennis racket 300 gradually moves toward the stop, and if the detection data D3 is in the range of the threshold value ± Y in S70, that is, it is determined as “Yes”. Then, detection of acceleration by the low dynamic range sensor 61 is started (S80). When the measurement of the low dynamic range sensor 61 in S80 is started, the acceleration measurement by the high dynamic range sensor 62 is subsequently stopped (S90). As the data of the low dynamic range sensor 61 that has started measurement in S80, detection data D4 of a detection value in the range of the dynamic range _RL is acquired as shown in FIG. 7C.

  Next, level correction 2 (S100) is performed. Similarly to level correction 1 (S50), level correction 2 (S100) is also for correcting detection data D3 of high dynamic range sensor 62 before switching with reference to detection data D4 of low dynamic range sensor 61. Level correction 2 (S100) is switched to the measurement of the low dynamic range sensor 61 by the command of S80 at the point p4 where the detection data D3 exceeds the threshold value Y, as shown in the partial enlarged view of the N part in FIG. Until the measurement start point p5, a little t2 time elapses. Due to this elapsed time t2, a discontinuous portion occurs in the detection data D3 and the detection data D4. The level correction 2 (S100) is to make this discontinuous data continuous data.

  The correction method of level correction 2 (S100) is such that the measurement stop point p6 of the detection data D3 coincides with the measurement start point p5 after elapse of t2 time of the reference detection data D4, and the correction data D3 ′. Create During this time, the low dynamic range sensor 61 proceeds to S10 where measurement is continued. Subsequently, in S20, it is determined whether or not the threshold value ± X is exceeded. It is determined as “No”, and in the motion detection (S200), it is determined as “No” in which the motion of the tennis racket 300 is not detected. finish.

For tennis racket 300 in the first embodiment, the dynamic range R _L of the low dynamic range sensor 61 + 5G~-5G about the dynamic range R _H is + 20G~-20G approximately sensors suitable for use in high dynamic range sensor 62 It is done. At this time, by setting the threshold value X to ± 4G and the threshold value Y to ± 5G, highly accurate detection data can be obtained.

  As described above, the data of the posture detection apparatus 100 obtained by the flow of S10 to S100 is obtained as continuous data of D1, D2 ', D3', and D4 shown in FIG. In this way, by switching between a low dynamic range sensor and a high dynamic range sensor and setting and switching a predetermined threshold so as to measure an acceleration region that matches the characteristics of each sensor, it is high from slow to fast movement. Acceleration can be measured with high accuracy, and high-precision posture data can be acquired together with the measurement result of the triaxial angular velocity sensor. Therefore, by analyzing the accurate posture data, it is possible to perform highly accurate trajectory analysis, and it is possible to improve the form and determine the suitability of the tool appropriate for the player. In addition, as shown in the above-described embodiment, a configuration in which the trajectory analysis can be performed simply by attaching to the end portion 300c of the grip 300a of the tennis racket 300, a special image device or the like is required regardless of the place. This makes it possible to perform trajectory analysis.

(Modification)
In the first embodiment and the second embodiment, the form of using two triaxial acceleration sensors has been described. For example, by providing three or more triaxial acceleration sensors, orbit analysis can be performed with higher accuracy. Make it possible. FIG. 8 schematically shows a graph of detection data when three three-axis acceleration sensors are used. As shown in FIG. 8, the three-axis acceleration sensor is an example in which three three-axis acceleration sensors having performances of a high dynamic range R _H , a middle dynamic range R _M , and a low dynamic range R _L are used. At this time, the judgment with the threshold value is increased with respect to the steps in the flowchart of FIG.

  First, measurement by a low dynamic sensor is performed up to a threshold value ± X1, and detection data d1 is obtained. When the threshold value ± X1 is exceeded, the medium dynamic range sensor is switched, and the obtained detection data is level-corrected in the same manner as in the second embodiment to obtain corrected detection data d2 '. When the corrected detection data d2 'next exceeds the threshold value ± X2, the detection data is switched to a high dynamic range sensor, and the obtained detection data is level-corrected to obtain corrected detection data d3'.

  When the detection data d3 'exceeds the maximum value and the measurement value of the high dynamic range sensor enters the range of the threshold value ± Y2, the medium dynamic sensor is switched, and correction data d4' is obtained by level correction. When the measured value by the middle dynamic range sensor enters the range of the threshold value ± Y1, it is switched to the low dynamic range sensor, and correction data d5 'is obtained by level correction. Then, detection data d6 measured by the low dynamic range sensor is obtained, and the measurement ends.

  Thus, by subdividing the dynamic range, detection data with higher accuracy can be obtained, and the accuracy of the trajectory analysis result can be further improved. As described above, it is possible to use three or more acceleration sensors by repeating measurement, switching, and level correction.

  DESCRIPTION OF SYMBOLS 10 ... Inertial sensor, 20 ... Attitude detection part, 30 ... Data I / F, 40 ... Calculation part, 50 ... 3-axis angular velocity sensor, 61, 62 ... 3-axis acceleration sensor, 70 ... Attitude data generation part, 80 ... Sensor control , 90 ... transmitting unit, 100 ... posture detecting device, 200 ... analyzing device, 210 ... receiving unit, 220 ... analyzing unit / storing unit, 230 ... operating unit, 240 ... notifying unit, 1000 ... trajectory analyzing device.

Claims (7)

A motion analysis device for analyzing a swing,
Sensors for selecting the second output data from the second acceleration sensor having a first output data and the second higher than the first dynamic range second dynamic range from the first acceleration sensor having a first dynamic range A control unit;
A data generation unit that generates analysis data using the first output data and the second output data ,
The sensor control unit performs a process of switching from the first output data to the second output data when the first output data exceeds a first threshold between the start of the swing and the impact; and ,
A process of switching from the second output data to the first output data when the second output data falls below a second threshold different from the first threshold between the impact and the end of the swing. A motion analysis apparatus characterized by performing.   The motion analysis apparatus according to claim 1, further comprising a level correction unit that corrects discontinuous data at the time of switching between the first output data and the second output data into continuous data.   The level correction unit connects the maximum value of the second output data after switching from the first output data to the second output data and the output value of the second output data serving as a starting point after switching. The motion analysis apparatus according to claim 2, wherein the discontinuous data is converted into continuous data by correcting an inclination of a virtual line.   The level correction unit is configured to connect a maximum value of the second output data before switching from the second output data to the first output data and an output value of the first output data serving as a starting point after switching. The motion analysis apparatus according to claim 2, wherein the discontinuous data is converted into continuous data by correcting a slope of a line. The sensor control unit, based on the magnitude of the acceleration, motion analysis device according to any one of 4 to claims 1, characterized in that the selection of the first output data and second output data. A data I / F unit for analog-digital conversion of the first output data and the second output data ;
An arithmetic unit that processes data from the data I / F unit,
The motion analysis according to claim 1 , wherein the sensor control unit selects the first output data or the second output data based on a calculation result from the calculation unit. apparatus.   A motion analysis method for analyzing a swing,
Selecting first output data from a first acceleration sensor having a first dynamic range and second output data from a second acceleration sensor having a second dynamic range higher than the first dynamic range. When,
  Generating analysis data using the selected first output data and second output data,
  The step of performing the selection performs a process of switching from the first output data to the second output data when the first output data exceeds a first threshold between the start of the swing and the impact. and,
  A process of switching from the second output data to the first output data when the second output data falls below a second threshold different from the first threshold between the impact and the end of the swing. A motion analysis method characterized by performing.

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