Mobile means estimation system, mobile means estimation method, and program

Abstract

A mobile means estimation system that estimates a mobile means of a living body using air pressure is provided. A mobile means estimation system is provided that includes an air pressure measurement unit that measures air pressure using at least one wearable sensor that measures air pressure mounted on a living body, and an estimation unit that estimates a mobile means of a living body using the measured air pressure. The mobile means estimation system measures a gait from measurement results of three-axis acceleration and three-axis angular velocity of the wearable sensor mounted, and estimates whether movement on stairs, movement on escalators, or movement in an elevator is performed using the measured air pressure and the gait.

Description

Technical Field

[0001] This invention relates to a system, method, and procedure for estimating means of movement. Background Technology

[0002] Patent document 1 describes an action status monitoring system that can fairly manage measurement results based on the installation orientation of the sensors.

[0003] Patent Document 1: Japanese Patent Application Publication No. 2022-34450 Summary of the Invention However, Patent Document 1 does not disclose the sensor's measurement of air pressure. Therefore, the object of the present invention is to provide a movement means estimation system that estimates the movement means of a living body by measuring air pressure.

[0004] The present invention provides a mobility means estimation system, comprising: A barometric pressure measuring unit that uses at least one wearable sensor for measuring barometric pressure, installed on a living body, to measure the barometric pressure; and The estimation unit uses the measured air pressure to estimate the means of movement of the living body.

[0005] Based on the above structure, a means of movement estimation system is provided that uses air pressure to estimate the means of movement of a living body.

[0006] The mobility estimation system of the present invention determines gait based on the measurement results of triaxial acceleration and triaxial angular velocity installed on the wearable sensor, and uses the measured air pressure and gait to estimate whether the movement is on a staircase, an escalator, or an elevator.

[0007] The above structure is an example of the presumed means of movement.

[0008] The mobility estimation system of the present invention determines gait based on the measurement results of triaxial acceleration and triaxial angular velocity of a plurality of wearable sensors, and uses the measured air pressure difference and the gait to estimate whether the movement is walking, wheelchair-bound, or cycling.

[0009] The above structure is an example of the presumed means of movement.

[0010] The present invention provides a method for estimating a means of movement, wherein, The air pressure is measured using at least one wearable sensor installed in a living body. The measured air pressure is used to estimate the means of movement of the living organism.

[0011] Based on the above structure, a method for estimating the means of movement of a living body using air pressure is provided.

[0012] A program of the present invention causes an information processing device to perform the following steps: The air pressure is measured using at least one wearable sensor installed in a living body. The measured air pressure is used to estimate the means of movement of the living organism.

[0013] Based on the above structure, a program is provided that causes an information processing device to perform the step of using air pressure to estimate the movement of a living body.

[0014] Invention Effects According to the present invention, a means of movement estimation system is provided that uses air pressure to estimate the means of movement of a living body. Attached Figure Description

[0015] Figure 1 This is a block diagram illustrating the structure of the presumed system of the means of movement involved in the implementation method.

[0016] Figure 2 This is a flowchart of the method for estimating the means of movement involved in the implementation method.

[0017] Figure 3 This is a diagram showing the results measured by the sensors of the motion estimation system involved in the implementation method.

[0018] Figure 4 This is a diagram illustrating an example of sensor installation in a mobile means estimation system according to the embodiment.

[0019] Figure 5 This is a diagram illustrating a first example of a wearable device that measures the air pressure difference using a sensor from a mobile means estimation system according to the implementation method.

[0020] Figure 6 This is a diagram illustrating a second example of a wearable device that uses a sensor from a mobile means estimation system to measure the pressure difference in an embodiment.

[0021] Figure 7 This is a diagram illustrating a third example of a wearable device that measures the pressure difference using a sensor from a mobile means estimation system according to the implementation method.

[0022] Figure 8 This is a diagram illustrating a fourth example of a wearable device where the pressure difference is measured by a sensor in a mobile means estimation system according to the implementation method.

[0023] Figure 9 This is a diagram illustrating an example of the results obtained by measuring the pressure difference in the mobile means estimation system involved in the embodiment.

[0024] Figure 10 This is a diagram illustrating an example of the presumed posture involved in the implementation method.

[0025] Figure 11 This is a diagram illustrating an example of measuring the air pressure difference during elevator movement in the motion estimation system involved in the implementation method.

[0026] Figure 12 This is a diagram illustrating an example of measuring the air pressure difference during stair-based movement in the motion estimation system involved in the embodiment.

[0027] Figure 13 This is a diagram illustrating an example of measuring the air pressure difference during bicycle movement in a mobility estimation system according to the embodiment.

[0028] Figure 14 This is a diagram illustrating an example of measuring the air pressure difference during wheelchair movement in a mobility estimation system according to the embodiment.

[0029] Figure 15 This is a diagram showing the structure of the information processing device involved in the implementation method. Detailed Implementation

[0030] Implementation Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, the invention as described in the claims is not limited to the following embodiments. Furthermore, not all structures described in the embodiments are necessarily necessary as means to solve the problem. For clarity of description, the following descriptions and drawings have been appropriately omitted and simplified. In the drawings, the same elements are labeled with the same symbols, and repeated descriptions are omitted as necessary.

[0031] (Description of the mobility estimation system involved in the implementation) Figure 1 This is a block diagram illustrating the structure of the presumed system of the means of movement involved in the implementation method. Figure 3 This is a diagram showing the results measured by the sensors of the motion estimation system involved in the implementation method. Figure 4 This is a diagram illustrating an example of sensor installation in a mobile means estimation system according to the embodiment. Figure 5 This is a diagram illustrating a first example of a wearable device that measures the air pressure difference using a sensor from a mobile means estimation system according to the implementation method. Figure 6 This is a diagram illustrating a second example of a wearable device that uses a sensor from a mobile means estimation system to measure the pressure difference in an embodiment. Figure 7 This is a diagram illustrating a third example of a wearable device that measures the pressure difference using a sensor from a mobile means estimation system according to the implementation method. Figure 8 This is a diagram illustrating a fourth example of a wearable device where the pressure difference is measured by a sensor in a mobile means estimation system according to the implementation method. Figure 9 This is a diagram showing an example of the results of measuring the pressure difference in the mobile means stationary system involved in the implementation method. Figure 10 This is a diagram illustrating an example of the presumed posture involved in the implementation method. Figure 11 This is a diagram illustrating an example of measuring the air pressure difference during elevator movement in the motion estimation system involved in the implementation method. Figure 12 This is a diagram illustrating an example of measuring the air pressure difference during stair-based movement in the motion estimation system involved in the embodiment. Figure 13 This is a diagram illustrating an example of measuring the air pressure difference during bicycle movement in a mobility estimation system according to the embodiment. Figure 14 This is a diagram illustrating an example of measuring the air pressure difference during wheelchair movement in the mobility estimation system described in the embodiment. (Reference) Figure 1 and Figures 3 to 14 The system for estimating the means of movement involved in the implementation method will be described.

[0032] like Figure 1 As shown, the mobility estimation system 100 according to the embodiment includes a barometric pressure measuring unit 101 and an estimation unit 102.

[0033] The barometric pressure measuring unit 101 measures barometric pressure using at least one wearable sensor installed on a living body, measuring triaxial acceleration, triaxial angular velocity, and barometric pressure. The triaxial aspect refers to the X, Y, and Z axes of a three-dimensional coordinate system. The wearable sensor is installed on a living body, particularly a human, by wrapping a strap around the upper arm, forearm, thigh, calf, back, abdomen, head, etc. When multiple wearable sensors are installed, their angles to each other can also be measured.

[0034] like Figure 3 As shown, wearable sensors can be used to observe a person's gait. Because the measurements can be made with great precision, it can be used for rehabilitation of people with disabilities. If 24-hour activity levels can be monitored during rehabilitation, further rehabilitation can be achieved.

[0035] like Figure 4 As shown, wearable sensors do not need to be installed on all selected sites. Only a few wearable sensors need to be selected and installed. For example, for rehabilitation of the right foot, sensors can be installed on the right thigh and right calf for detailed measurements.

[0036] like Figure 5As shown, the pressure difference can be the pressure difference between multiple wearable sensors. In this case, consider multiple wearable sensors installed at different heights to generate pressure differences, such as the lower leg and upper arm, back and lower leg, thigh and upper arm, thigh and back, lower leg and head, etc.

[0037] like Figure 6 As shown, the pressure difference can be the pressure difference between the mobile terminal 601, especially a smartphone, and the wearable sensor. In this case, the wearable sensor can be a single device. Alternatively, an external terminal that has determined a reference position can replace the mobile terminal 601.

[0038] The estimation unit 102 uses the measured air pressure to estimate the posture of the organism.

[0039] like Figure 10 As shown, a pressure difference is generated between the ankles and back when a person is standing, sitting, or lying down. Figure 9 This is a graph showing the measured air pressure difference. Areas with large air pressure differences can be defined as standing positions, the middle as sitting positions, and areas with small air pressure differences as lying positions. While walking, the position can be determined as standing. Furthermore, this can be determined using accelerometers and angular velocity sensors.

[0040] Thus, by pre-storing the pressure differences at each posture, the posture of a living organism can be estimated. In particular, by pre-storing at least two pressure differences, the remaining posture can also be determined.

[0041] Furthermore, it can classify patterns and determine poses based on various pieces of information. In pattern classification, supervised data is used to memorize the correct answers and make judgments. Alternatively, pattern classification can also be achieved through unsupervised learning to perform machine learning.

[0042] Alternatively, pattern classification can be performed using algorithms. The average value over a given period is divided into three segments for posture determination. In continuous patterns, moments of significant pressure change are considered posture transitions and are excluded from the average value calculation. In cases of slow changes, the average value is calculated when it crosses a certain threshold. In cases of slow changes where it's impossible to determine whether the posture is standing or sitting, a moving average is used. In this case, the time period is shortened, and the posture is determined more precisely.

[0043] Furthermore, the initially measured pressure difference can be used as a calibration for a specific posture. The posture is divided into three stages, so if it is high, it can be tested as a standing position, and if it is low, it can be tested as a supine position. In this way, posture can be estimated based on the magnitude of the measured pressure difference.

[0044] like Figure 7 and Figure 8As shown, wearable sensors other than those for measuring pressure differences can be installed. Figure 9 As shown, the air pressure difference changes significantly when postures are reversed. Therefore, false posture detection is possible. Thus, by combining the triaxial acceleration, triaxial angular velocity, and angles between multiple wearable sensors, the posture of a living organism can be estimated, thereby improving the accuracy of posture estimation.

[0045] Figure 11 The graph uses sensors worn on the back to measure the air pressure caused by the elevator's movement. From the 30th to the 32nd floor, the ascent is smooth and gradual. Escalators exhibit the same waveform, but their ascending and descending speeds differ.

[0046] Figure 12 The system uses sensors worn on the back to measure the air pressure map based on movement along the stairs. The ascent is zigzag-like, from the 30th to the 32nd floor. In this way, elevators, escalators, and stairs can be identified using air pressure differences and changes in speed. The accuracy of motion detection can be further improved by considering the presence of gait.

[0047] Figure 13 This represents the air pressure difference based on bicycle movement. Periodic air pressure changes caused by pedaling are generated by sensors mounted on the feet.

[0048] Figure 14 This represents the pressure difference caused by movement due to the wheelchair. When seated, the pressure difference remains almost unchanged.

[0049] Gait can be determined using measurements from triaxial acceleration and triaxial angular velocity sensors. Whether someone is walking can be determined by observing the activity of the triaxial acceleration and triaxial angular velocity sensors while the person is standing. Therefore, it is possible to distinguish between bicycle movement, wheelchair movement, and walking movement by using air pressure difference and triaxial acceleration and triaxial angular velocity sensors.

[0050] Based on the above structure, a means of movement estimation system is provided that uses air pressure to estimate the means of movement of a living body.

[0051] (Explanation of the method for estimating the means of movement involved in the implementation) Figure 2 This is a flowchart of the method for estimating the means of movement involved in the implementation method. Figure 15 This is a block diagram illustrating the structure of the information processing apparatus according to the embodiment. (Reference) Figure 2 and Figure 15 The method for estimating the means of movement involved in the implementation method will be explained.

[0052] First, the air pressure is measured (step S201). The air pressure difference is measured using at least one wearable sensor that measures triaxial acceleration, triaxial angular velocity, and air pressure installed on the living body. Multiple wearable sensors are used to measure the air pressure difference. Alternatively, a wearable sensor and a mobile terminal 601 are used to measure the air pressure. Next, the means of movement is estimated (step S202). The measured air pressure difference is used to estimate the person's means of movement.

[0053] Based on the above structure, a method for estimating the means of movement of a living body can be provided, which can use air pressure to estimate the means of movement.

[0054] The above method can be executed by causing an information processing device to process the information. For example... Figure 15 As shown, the information processing device 1500 includes a processor 1501 for executing programs and a memory 1502 for storing programs. The information processing device 1500 can be a single device or multiple devices. The information processing device 1500 can be a cloud server that provides part or all of the distributed processing functionality.

[0055] Part or all of the processing in the information processing apparatus 1500 can be implemented as a computer program. This program can be stored using various types of non-transitory computer-readable media and can be supplied to a computer. Non-transitory computer-readable media include various types of physical recording media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., floppy disks, magnetic tapes, hard disk drives), optical-magnetic recording media (e.g., optical disc drives), compact disc read-only memory (CD-ROM), CD-R, CD-R / W, and semiconductor memory (e.g., mask ROM, programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), flash memory ROM, random access memory (RAM)). Furthermore, the program can be supplied to the computer via various types of transient computer-readable media. Examples of transient computer-readable media include electrical signals, optical signals, and electromagnetic waves. Transient computer-readable media can provide the program to the computer via wired or wireless communication channels such as wires and optical fibers.

[0056] Furthermore, the present invention is not limited to the above-described embodiments, and appropriate modifications can be made without departing from the spirit of the invention.

[0057] Symbol Explanation 100-Mobile means estimation system, 101-Barometric pressure measuring unit, 102-Estimation unit, 601-Mobile terminal, 1500-Information processing device, 1501-Processor, 1502-Memory.

Claims

1. A system for estimating the means of movement, characterized in that, have: A barometric pressure measuring unit that uses at least one wearable sensor for measuring barometric pressure, installed on a living body, to measure the barometric pressure; and The estimation unit uses the measured air pressure to estimate the means of movement of the living body.

2. The mobility estimation system according to claim 1, characterized in that, Gait is determined based on the triaxial acceleration and triaxial angular velocity measurements installed on the wearable sensor, and the measured air pressure and gait are used to infer whether the movement is on a staircase, an escalator, or an elevator.

3. The mobility estimation system according to claim 1, characterized in that, Gait is determined based on the measurement results of triaxial acceleration and triaxial angular velocity installed on multiple wearable sensors, and the measured air pressure difference and the gait are used to infer whether the movement is walking, wheelchair-bound, or cycling.

4. A method for estimating the means of movement, characterized in that, The air pressure is measured using at least one wearable sensor installed in a living body. The measured air pressure is used to estimate the means of movement of the living organism.

5. A program, characterized in that, The information processing device performs the following steps: The air pressure is measured using at least one wearable sensor installed in a living body. The measured air pressure is used to estimate the means of movement of the living organism.

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