JP2020174787A - Finger movement estimation system - Google Patents

Abstract

To accurately estimate an amount of use of a finger.SOLUTION: A finger movement estimation system 1 comprises a ring type device 10 that is mounted on a finger and a microcomputer 60. The ring type device 10 includes an infrared distance sensor 11 that outputs infrared light and detects reflection of the infrared light at the finger to output a signal depending on a distance to the finger. The microcomputer 60 identifies a bent angle Θ at the time of extension, as a reference state of the finger, on the basis of the signal output from the infrared distance sensor 11 and, on the basis of the bent angle Θ, estimates an amount of use of the finger.SELECTED DRAWING: Figure 1

Description

The present invention relates to a finger movement estimation system.

Patent Document 1 describes as a device for estimating the amount of finger used, which is a ring-shaped device composed of magnets and which estimates the amount of finger used according to a change in magnetic force when the finger is moved. Has been done.

U.S. Patent Application Publication No. 2014/0257143

Here, the change in magnetic force with respect to the movement of the finger is minute, and it is difficult to estimate the amount of finger used with high accuracy by the device of Patent Document 1 described above.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a finger movement estimation system capable of estimating the amount of finger usage with high accuracy.

The finger movement estimation system according to one aspect of the present invention is a finger movement estimation system including a ring-type device attached to a finger and a control unit, and the ring-type device outputs light and the light on the finger. It has an optical sensor that detects bounce and outputs a signal according to the distance to the finger, and the control unit identifies the bending angle of the finger with respect to the reference state based on the signal output from the optical sensor, and the bending Estimate finger usage based on angle.

In the finger movement estimation system according to one aspect of the present invention, the optical sensor of the ring-type device outputs a signal according to the distance to the finger. Since the distance to the fingers changes according to the bending angle of the fingers, the control unit specifies the bending angle of the fingers based on the distance to the fingers. Since such a flexion angle of the fingers appropriately represents the usage state of the fingers, the control unit estimates the usage of the fingers with high accuracy by estimating the usage of the fingers based on the flexion angle. Can be done. Then, in the finger movement estimation system according to one aspect of the present invention, since the amount of fingers used is estimated based on the light detection result, for example, the change is small with respect to the finger movement, in response to a change in magnetic force. Compared with the case of estimating the amount of fingers used, the amount of fingers used can be estimated with high accuracy.

The control unit may be provided integrally with the ring type device. According to such a configuration, for the target user whose finger usage is estimated, only the ring type device needs to be worn, and the burden on the user can be reduced.

The control unit may be provided separately from the ring type device. According to such a configuration, the ring type device itself can be made a simple configuration.

The control unit may specify the bending angle based on the function model represented by the following equation (1). Θ is the flexion angle of the joint with respect to the extension, which is the reference state of the finger, x is the distance from the optical sensor to the measurement position of the finger, and r is the distance from the joint to the measurement position of the finger.
Θ = arccos (x / r) ... (1)
By using such a function model, the bending angle Θ can be easily derived with high accuracy.

For each user who uses the ring-type device, the control unit previously outputs a signal at the time of extension, which is a signal output from the optical sensor when the finger is extended, and a signal output from the optical sensor when the finger is completely bent. The bending signal is obtained, and the distance x from the optical sensor to the measurement position of the finger may be derived in consideration of the extension signal and the bending signal. There is a correspondence between the distance x and the signal (voltage) output from the optical sensor. However, which distance the value of the signal output from the optical sensor corresponds to depends on the user. In this regard, by acquiring the extension signal and the flexion signal for each user, the voltage when the distance x is the longest (minimum voltage) and the voltage when the distance x is the shortest (maximum voltage). Therefore, the distance x can be accurately derived according to the voltage output from the optical sensor.

The control unit may estimate the gesture of the finger by comparing the bending angle of the specified finger with the gesture pattern acquired in advance. As a result, in addition to the amount of fingers used, the gestures of the fingers can be estimated, and the finger movements can be estimated more specifically.

As an optical sensor, the ring-type device outputs light to the tip side of the finger and detects the bounce of the light on the finger, and outputs light to the base end side of the finger and bounces the light on the finger. It may have a second sensor that detects the light. As a result, the flexion angle of the second joint can be specified by the first sensor, and the flexion angle of the third joint can be specified by the second sensor, so that the amount of fingers used can be estimated with higher accuracy. it can.

The finger movement estimation system described above is a ring-type device in which a first device attached to a user's first finger and a second device attached to a second finger different from the same user's first finger are used. And may be provided. As a result, the movements of a plurality of fingers can be estimated at the same time.

The first device may be attached to the first finger of one hand of the user, and the second device may be attached to the second finger of one hand of the same user. This makes it possible to estimate how multiple fingers of the same hand are used.

The first device may be attached to the first finger of one hand of the user and the second device may be attached to the second finger of the other hand of the same user. This makes it possible to estimate how multiple fingers of different hands are used. As a result, the ring-shaped device is attached to the fingers of both hands, for example, a user who is paralyzed on one side of the body, and the usage state and the non-paralyzed side of the fingers of the paralyzed hand are attached. It is possible to evaluate the effect of rehabilitation from the difference from the usage state of the fingers of the hand.

According to the present invention, it is possible to provide a finger movement estimation system capable of estimating the amount of finger usage with high accuracy.

It is a figure which shows typically the structure of the finger movement estimation system which concerns on this embodiment. It is a figure which shows typically the ring side device shown in FIG. It is a figure which shows typically the ring side device shown in FIG. It is a figure explaining the method of specifying a bending angle. It is a figure explaining the specific image of a bending angle using a function model. It is a figure explaining the calibration process. It is a figure which shows the specific result of a bending angle. This is the estimation result of the amount of fingers used derived from the configuration according to the comparative example. This is the estimation result of the amount of fingers used derived from the configuration according to the comparative example. This is an estimation result of the amount of fingers used derived by the configuration according to the present embodiment. This is an estimation result of the amount of fingers used derived by the configuration according to the present embodiment. It is a figure which shows typically the ring type device which concerns on a comparative example. It is a figure which shows typically the ring type device which concerns on a comparative example.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same reference numerals are used for the same or equivalent elements, and duplicate description is omitted.

FIG. 1 is a diagram schematically showing a configuration of a finger movement estimation system 1 according to the present embodiment. The finger movement estimation system 1 is a system for estimating the amount of fingers used. The finger movement estimation system 1 quantitatively measures whether or not the amount of paralyzed limbs used by a patient (user) is increasing in rehabilitation in the convalescent / chronic phase after suffering from a cerebrovascular disease (stroke, etc.). Used in applications. The use of paralyzed limbs is effective in improving paralyzed limb function. The finger movement estimation system 1 quantitatively evaluates the effect of rehabilitation (the amount of fingers used) in a daily living environment, and at least a part thereof is composed of a wearable device (a device worn by the user on the body). ing.

As shown in FIG. 1, the finger movement estimation system 1 includes a ring-type device 10, a wiring 30, and a processing device 50.

The ring-type device 10 is a ring-type wearable device worn on a finger. In the example shown in FIG. 1, the ring-type device 10 is attached to the index finger of the right hand. The ring-type device 10 is mounted, for example, between the second and third joints of the fingers.

The details of the ring type device 10 will be described with reference to FIGS. 2 and 3. 2 and 3 are diagrams schematically showing the ring-shaped device 10 shown in FIG. As shown in FIGS. 2 and 3, the ring type device 10 has an infrared distance sensor 11 (optical sensor). The infrared distance sensor 11 is provided so as to be embedded in a part of the ring type device 10. The infrared distance sensor 11 outputs infrared rays (light), detects the bounce of the infrared rays on the finger, and outputs a signal corresponding to the distance to the finger.

The infrared distance sensor 11 has an LED (light emittingdiode) 111 as a light emitting element and a phototransistor 112 as a light receiving element. The LED 111 is provided at a position where infrared rays can be emitted toward the tip side of the finger. The phototransistor 112 is provided at a position where the bounce of infrared rays can be detected on the tip side of the finger. The phototransistor 112 is a distance sensor that outputs a signal (voltage) according to the distance to the tip side of the finger to which infrared rays are reflected. The phototransistor 112 outputs a signal having a larger voltage as the tip of the finger is closer.

The state where the distance between the phototransistor 112 and the tip of the finger is the smallest is the state where the second joint is completely bent (the angle of the second joint is 90 °), and the distance is the largest. The state is a state in which the second joint is extended (a state in which the angle of the second joint is 0 ° as shown in FIG. 2). That is, the phototransistor 112 outputs the signal having the highest voltage when the second joint is completely bent, and outputs the signal having the lowest voltage when the second joint is extended. In the present embodiment, for each user who uses the ring-type device 10, the extension signal, which is a signal output from the phototransistor 112 when the finger is extended, and the extension signal when the finger is completely bent are transmitted from the phototransistor 112 in advance. The bending signal, which is the output signal, is acquired. The voltage values of the extension signal and the bending signal are stored in, for example, a data storage 70 (see FIG. 1) described later.

Returning to FIG. 1, the wiring 30 is a wiring that electrically connects the LED 111 and the phototransistor 112 of the ring type device 10 and the processing device 50.

The processing device 50 includes, for example, a microcomputer 60 (control unit), a data storage 70, and a battery 80. The processing device 50 is attached to, for example, the user's wrist (the wrist of the hand on which the ring-type device 10 is attached). Specifically, the processing device 50 is fixed to the user's wrist by, for example, a band 90 or the like. As described above, in the present embodiment, not only the ring type device 10 but also the processing device 50 is a wearable device that is easy to carry. It should be noted that each configuration of the processing device 50 does not necessarily have to be a wearable device, and a part or all of the configurations may be provided apart from the user. Further, the microcomputer 60 may be provided separately from the ring-type device 10 as in the present embodiment, or may be provided integrally with the ring-type device 10.

The data storage 70 stores the measurement result of the infrared distance sensor 11 and the estimation result of the microcomputer 60. As described above, the data storage 70 stores the voltage values of the extension signal and the flexion signal for each user, which are measured in advance.

The microcomputer 60 specifies the bending angle Θ with respect to the reference state of the finger based on the signal output from the infrared distance sensor 11, and estimates the amount of the finger used based on the bending angle Θ. Specific processing of the microcomputer 60 will be described with reference to FIGS. 4 to 6. FIG. 4 is a diagram illustrating a method of specifying the bending angle Θ. FIG. 5 is a diagram for explaining a specific image of the bending angle Θ using a function model. FIG. 6 is a diagram illustrating a calibration process.

As shown in FIG. 4, the bending angle Θ with respect to the reference state of the finger is specified based on the distance x from the infrared distance sensor 11 to the measurement position of the finger and the distance r from the second joint to the measurement position of the finger. be able to. That is, as shown in FIG. 4, the flexion angle of the second joint with respect to the extension time, which is the reference state of the finger, is set to Θ, and for example, from the infrared distance sensor 11 to the tip (fingertip) of the finger, which is the measurement position of the finger. If the distance of is x and the distance from the second joint to the tip (fingertip) of the finger, which is the measurement position of the finger, is r, the following equation (0) holds. Then, the following equation (1) is derived from the equation (0).
cos Θ = x / r ... (0)
Θ = arccos (x / r) ... (1)

The microcomputer 60 specifies the bending angle Θ based on the function model represented by the above equation (1). As described above, Θ is the flexion angle of the joint (here, the second joint) with respect to the extension, which is the reference state of the finger, and x is the distance from the infrared distance sensor 11 to the measurement position of the finger (here, the fingertip), r. Is the distance from the joint (here, the second joint) to the measurement position of the finger (here, the fingertip). The distance x is specified in the microcomputer 60 as described later. The distance r has been acquired in advance as an individual parameter. The bending angle Θ can be rephrased as the angle of change from the time when the fingers are extended, and the distance x can be rephrased as the distance of change from the time when the fingers are bent (when the fingers are completely bent). First, the microcomputer 60 derives the distance x, inputs the distance x into the function model as shown in FIG. 5, and obtains the bending angle Θ as the output from the function model.

As shown in FIG. 6, the correspondence between the voltage value output from the infrared distance sensor 11 and the distance x can be approximated by a linear function. Here, since there are individual differences for each user, it is difficult to specify the distance x with high accuracy simply from the voltage value. In this regard, in the present embodiment, when the microcomputer 60 derives the distance x, the microcomputer 60 performs calibration on a user-by-user basis by using the extension signal and the flexion signal, which are sensor data of the user to be measured. .. Specifically, in the microcomputer 60, for each user who uses the ring-type device 10, the extension time signal, which is a signal output from the infrared distance sensor 11 when the finger is extended, and the finger are completely bent. In the state, the bending signal, which is a signal output from the infrared distance sensor 11, is acquired, and the extension signal and the bending signal are taken into consideration, and the tip of the finger, which is the measurement position of the finger, is taken from the infrared distance sensor 11. The distance x to the fingertip) is derived.

The microcomputer 60 acquires the voltage values of the extension signal and the bending signal stored in the data storage 70 for the user to be measured. As shown in FIG. 6, the voltage at the extension signal (voltage at the time of extension) is the smallest voltage in the measurement of the user, and the voltage of the signal at the time of bending (voltage at the time of complete bending) is the lowest in the measurement of the user. It is a large voltage. Then, as shown in FIG. 6, the voltage range of the signal output from the infrared distance sensor 11 (specifically, the phototransistor 112) is always the voltage range of the bending signal voltage to the extending signal voltage. Therefore, the distance x (0 ≦ x ≦ r) is specified according to the value of the voltage, where the distance x = 0 in the voltage of the bending signal and the distance x = r in the voltage of the extending signal. In this way, by performing calibration using the extension signal and the flexion signal for each user, the distance x can be appropriately set according to the signal output from the infrared distance sensor 11 in consideration of individual differences. Can be derived.

The microcomputer 60 estimates the amount of fingers used, for example, by integrating the amount of change in the bending angle Θ per unit time over time. Further, the microcomputer 60 may estimate the gesture pattern of the finger by comparing the bending angle Θ of the specified finger with the gesture pattern acquired in advance. The gesture pattern is stored in the data storage 70 in advance, for example, a gesture that does not change with time (for example, goo, choki, par, etc.), or a series of gestures that change with time (for example, a beg used in rehabilitation). Operation of insertion and removal, etc.). For gestures that do not change with time, the microcomputer 60 estimates the gesture pattern of the fingers, for example, by comparing the bending angle Θ at a certain point in time with the bending angle in each gesture pattern. Further, the microcomputer 60 compares the temporal distribution (change) of the bending angle Θ with the temporal distribution (change) of the bending angle in the series of gesture patterns changing with time for a series of gestures that change with time. By doing so, the gesture pattern of the fingers is estimated.

Next, the action and effect of this embodiment will be described.

First, the research background of the finger movement estimation system 1 according to the present embodiment will be described. For example, in stroke paralysis rehabilitation, it is important to improve the paralyzed limb function of the patient so that he / she can perform activities of daily living such as eating, changing clothes, and bathing. From the viewpoint of confirming the improvement of paralyzed limb function, there is a need for a method for quantitatively measuring whether or not the amount of paralyzed limb used by patients increases in daily life after rehabilitation intervention. A method for measuring the amount of paralyzed limbs used is required not only for confirming the improvement effect but also for promoting the use of paralyzed limbs by patients.

Conventionally, as a method of measuring upper limb function performed in hospitals and rehabilitation facilities, Action Research Arm Test, which evaluates upper limb function according to the degree of achievement of 19 tasks, and measurement time by measuring the time for inserting and removing 9 pegs. The Nine Hole Peg Test, which evaluates upper limb function, is known. Although these methods can evaluate the patient's upper limb function in the test, they cannot measure the amount of paralyzed limb used in daily life.

In addition, as a method of grasping the amount of paralyzed limbs used in daily life, a self-report method is known in which an answer is obtained from a user in the form of a question. As a self-reporting method, for example, Motor Activity Log and Stroke Impact Scale are known. In such a self-reporting method, the amount of paralyzed limb used in daily life cannot be accurately evaluated because the measurement result depends on the subjectivity and memory of the patient.

As another method for measuring the amount of paralyzed limbs used in daily life, a method of measuring the amount of paralyzed limbs used using a wristwatch-type device in which an acceleration sensor is embedded is known. However, such a device only measures the movement of the entire hand, not the amount of fingers used, and it is difficult to ensure accuracy due to noise mixed in the accelerometer. From the viewpoint of measuring the paralyzed limb usage, it is preferable to measure the finger usage, so such a device is not suitable for accurate measurement of the paralyzed limb usage.

As a method for measuring the amount of finger usage, a method of attaching a glove-type wearable device to measure the amount of finger usage and a method of measuring the amount of finger usage using a motion camera and a marker are known. However, the glove-type wearable device is cumbersome to attach, and the wearer's movement (finger movement) may be hindered, making it impossible to accurately measure the amount of fingers used. In addition, a system using a motion camera and a marker is not suitable for constant measurement because the measurement location is spatially limited.

Further, as a method for measuring the amount of fingers used, a method of measuring the amount of arms and fingers used with a magnet and a magnetometer is known. However, since the change in magnetic force with respect to the movement of the fingers is minute, it is difficult to estimate the amount of finger usage with high accuracy by a device equipped with a magnet and a magnetometer. Further, for example, a method of identifying a hand gesture based on a wrinkle pattern of the skin on the back of the hand obtained by sensing light is known, but such a method measures the amount of finger usage (movement amount). Can not do it. As described above, conventionally, a method for quantitatively measuring the amount of fingers used in daily life has not been established.

In this regard, the finger movement estimation system 1 according to the present embodiment includes a ring-type device 10 attached to the finger and a microcomputer 60, and the ring-type device 10 outputs infrared rays and bounces off the infrared rays on the fingers. The microcomputer 60 has an infrared distance sensor 11 that detects a signal and outputs a signal according to the distance to the finger, and the microcomputer 60 is based on the signal output from the infrared distance sensor 11 and is in the reference state of the finger when extended. The bending angle Θ with respect to the above is specified, and the amount of fingers used is estimated based on the bending angle Θ.

In such a finger movement estimation system 1, the infrared distance sensor 11 of the ring type device 10 outputs a signal according to the distance to the finger. Since the distance to the fingers changes according to the bending angle Θ of the fingers, the microcomputer 60 specifies the bending angle Θ of the fingers based on the distance to the fingers. Since such a bending angle Θ of the finger appropriately represents the usage state of the finger, the microcomputer 60 estimates the usage amount of the finger with high accuracy by estimating the usage amount of the finger based on the bending angle Θ. can do. Then, in such a finger movement estimation system 1, since the amount of fingers used is estimated based on the detection result of infrared rays (light), for example, the change is small with respect to the movement of the finger according to the change of the magnetic force. Compared with the case of estimating the amount of fingers used, the amount of fingers used can be estimated with high accuracy. Since the ring type device 10 and the like are easy to put on and take off and are easy to carry, it can be said that they are suitable for constant measurement. As described above, the finger movement estimation system 1 according to the present embodiment can quantitatively measure the amount of finger used in daily life with high accuracy.

The accuracy of specifying the bending angle Θ by the finger movement estimation system 1 will be described with reference to FIG. 7. FIG. 7 is a diagram showing a specific result of the bending angle Θ. The present inventors set the angles of the second joints of the fingers to 0 °, 15 °, 30 °, 45 °, 60 °, 75 °, 90 in order to evaluate the specific accuracy of the flexion angle Θ by the finger movement estimation system 1. An instrument fixed at ° was created, the voltage (sensor data) output from the infrared distance sensor 11 was measured with each instrument fixing the angle of the fingers, and the bending angle Θ was derived. The measurement of the sensor data was performed for about 3 seconds, for example. In addition, measurement was performed 10 times for each angle. The number of subjects was 10, and the sample rate of the sensor was 100 Hz.

In FIG. 7, the horizontal axis represents the actual angle, and the vertical axis represents the angle estimated by the finger movement estimation system 1. The dots shown in FIG. 7 indicate the estimation results (estimated angles) at each angle. The broken line in FIG. 7 shows a straight line when there is no difference between the estimation result and the actual angle. The solid line in FIG. 7 shows a straight line of the average estimation result of 10 subjects. The 10-person average of the correlation coefficient between the actual angle and the estimated angle was 0.99. In addition, the 10-person average of the average absolute error obtained by averaging the error, which is the difference between the angle of the estimation result and the actual angle, by the number of measurement points was 3.20 °. For example, in the above-mentioned device for measuring the amount of fingers used by a device equipped with a magnet and a magnetometer, the average absolute error was 4.7 °. From this, it was found that the bending angle Θ can be specified with higher accuracy in the finger movement estimation system 1 than in the conventional method.

According to the finger movement estimation system 1, it is possible to clearly show the difference in the amount of fingers used in various tasks as compared with the conventional method. This will be described with reference to FIGS. 8 to 11. In order to estimate the amount of fingers used in various tasks, the present inventors have eight subjects wearing the ring-type device 10 perform three types of tasks, "wipe", "fold", and "peg". , Estimated the amount of fingers used in each task. Here, "wipe" is a task of wiping the table with a cloth, "fold" is a task of folding the cloth, and "peg" is a task of inserting and removing the peg. Further, in the experiment, a triaxial acceleration sensor was mounted on the processing device 50 mounted on the subject, and the change in acceleration in each task was also measured. Then, the amount of fingers used was estimated based on the value of the acceleration. That is, in the experiment, the estimation of the amount of hand used based on the sensing result of the infrared distance sensor 11 and the estimation of the amount of hand used based on the sensing result of the acceleration sensor, which are aspects of the present embodiment (comparative example). Estimated) and at the same time. The amount of fingers used is estimated, for example, by time-integrating the amount of change in the bending angle per unit time. Further, the amount of hand usage is estimated by, for example, time-integrating the amount of change of the acceleration sensor per unit time.

8 and 9 are estimation results of the amount of hand used derived by the configuration according to the comparative example. In FIG. 8, each dot shows the estimation result (hand usage) of one subject. In FIG. 9, the range indicated by the whiskers (straight line) is the range from the subject having the maximum value to the subject having the minimum value. However, outliers are excluded. Further, in FIG. 9, the upper surface of the box shows the position of the upper 25% value, and the lower surface of the box shows the position of the lower 25% value. As shown in FIG. 9, in the measurement results of the comparative example (using the sensing results of the accelerometer), the whiskers ranges of the “wipe” and “fold”, “wipe” and “peg” tasks overlap each other. doing. Therefore, in the configuration according to the comparative example, it can be said that it is not possible to show the difference in the amount of fingers used for each task of "wipe" and "fold", and "wipe" and "peg" (each task cannot be distinguished).

10 and 11 are the estimation results of the amount of fingers used derived by the configuration according to the present embodiment. In FIG. 10, each dot shows the estimation result (the amount of fingers used) of one subject. In FIG. 11, the range indicated by the whiskers (straight line) is the range from the subject having the maximum value to the subject having the minimum value. However, outliers are excluded. Further, in FIG. 11, the upper surface of the box shows the position of the upper 25% value, and the lower surface of the box shows the position of the lower 25% value. As shown in FIG. 11, in the measurement result of the present embodiment (using the sensing result of the infrared distance sensor 11), the whiskers of the tasks of "wipe" and "fold", and "wipe" and "peg" are used. The ranges do not overlap each other. Therefore, in the configuration according to the present embodiment, it can be said that the difference in the amount of fingers used for each task of "wipe" and "fold", and "wipe" and "peg" can be shown (each task can be distinguished). ..

The microcomputer 60 may be provided integrally with the ring-type device 10. According to such a configuration, only the ring type device 10 needs to be worn by the target user whose finger usage is estimated, and the burden on the user can be reduced.

The microcomputer 60 may be provided separately from the ring-type device 10. According to such a configuration, the ring type device 10 itself can be made a simple configuration.

The microcomputer 60 specifies the bending angle Θ based on the function model represented by the following equation (1). Θ is the flexion angle of the second joint with respect to the extension, which is the reference state of the finger, x is the distance from the infrared distance sensor 11 to the measurement position of the finger, and r is the distance from the second joint to the measurement position of the finger.
Θ = arccos (x / r) ... (1)
By using such a function model, the bending angle Θ can be easily derived with high accuracy.

The microcomputer 60 is provided with a extension signal, which is a signal output from the infrared distance sensor 11 when the finger is extended, and an infrared distance when the finger is completely bent, for each user who uses the ring-type device 10. The bending signal, which is a signal output from the sensor 11, is acquired, and the distance x from the infrared distance sensor 11 to the measurement position of the finger is derived in consideration of the extension signal and the bending signal. There is a correspondence between the distance x and the signal (voltage) output from the infrared distance sensor 11. However, which distance the value of the signal output from the infrared distance sensor 11 corresponds to depends on the user. In this regard, by acquiring the extension signal and the flexion signal for each user, the voltage when the distance x is the longest (minimum voltage) and the voltage when the distance x is the shortest (maximum voltage). Therefore, the distance x can be accurately derived according to the voltage output from the infrared distance sensor 11.

The microcomputer 60 estimates the gesture of the finger by comparing the bending angle Θ of the specified finger with the gesture pattern acquired in advance. As a result, in addition to the amount of fingers used, the gestures of the fingers can be estimated, and the finger movements can be estimated more specifically. In addition, the inventors used the configuration according to the present embodiment to compare the three gestures of the state where the fingers are closed, the state where the index finger and the thumb form a ring, and the state where the fingers are open by comparing with the gesture pattern. An experiment was conducted to see if the gesture could be estimated, and the average correct answer rate was 98.9%.

Although the present embodiment has been described in detail above, the present invention is not limited to the above embodiment.

For example, as shown in FIG. 12, the ring-type device 10A, as an infrared distance sensor (optical sensor), outputs light to the tip side of the finger and detects the bounce of the light in the finger with the first sensor 11X. , A second sensor 11Y that outputs light to the base end side of the finger and detects the bounce of the light on the finger may be provided. In this case, the ring-shaped device 10A is mounted between the second joint and the third joint, the flexion angle of the second joint is specified by the first sensor 11X, and the flexion angle of the third joint is determined by the second sensor 11Y. It becomes possible to identify. This makes it possible to estimate the amount of fingers used with higher accuracy than in the case of specifying the flexion angle of only the second joint.

Further, as in the finger movement estimation system 1A shown in FIG. 13A, the ring-type device is the same as the ring-type device 10 (first device) attached to the index finger (first finger) of the user. It may include a ring-type device 10B worn on the middle finger (second finger) different from the index finger of the user. As a result, the usage amount and movement of a plurality of fingers can be estimated at the same time. As in the finger movement estimation system 1A shown in FIG. 13A, the ring-shaped devices 10 and 10B are attached to different fingers of the same hand of the user, so that a plurality of fingers of the same hand can be attached. It becomes possible to estimate whether it is used.

Further, as in the finger movement estimation system 1B shown in FIG. 13B, the ring type device 10 is attached to the index finger (first finger) of the user's right hand (one hand) (see FIG. 1), and the ring. The mold device 10C may be attached to the index finger (second finger) of the left hand (the other hand) of the same user. This makes it possible to estimate how multiple fingers of different hands are used. As a result, the ring-shaped device is attached to the fingers of both hands, for example, a user who is paralyzed on one side of the body, and the usage state and the non-paralyzed side of the fingers of the paralyzed hand are attached. It is possible to determine the rehabilitation method from the difference from the usage state of the fingers of the hand.

1,1A, 1B ... Finger movement estimation system, 10,10A, 10B, 10C ... Ring type device, 11 infrared distance sensor (optical sensor), 60 microcomputer (control unit).

Claims (10)

A finger movement estimation system including a ring-type device attached to a finger and a control unit.
The ring-type device has an optical sensor that outputs light, detects the bounce of the light on a finger, and outputs a signal according to the distance to the finger.
The control unit is a finger movement estimation system that identifies a bending angle of a finger with respect to a reference state based on a signal output from the optical sensor, and estimates the amount of the finger used based on the bending angle. The finger movement estimation system according to claim 1, wherein the control unit is provided integrally with the ring type device. The finger movement estimation system according to claim 1, wherein the control unit is provided separately from the ring type device. The control unit specifies the bending angle based on the function model represented by the following equation (1). Θ is the flexion angle of the joint with respect to the reference state of the finger during extension, x is the distance from the optical sensor to the measurement position of the finger, and r is the distance from the joint to the measurement position of the finger.
Θ = arccos (x / r) ... (1)
The finger movement estimation system according to any one of claims 1 to 3. The control unit
For each user who uses the ring-type device, the extension signal, which is a signal output from the optical sensor when the finger is extended, and the signal output from the optical sensor when the finger is completely bent, are used in advance. Get a certain bending signal and
The finger movement estimation system according to claim 4, wherein the distance x from the optical sensor to the measurement position of the finger is derived in consideration of the extension signal and the flexion signal. The finger movement estimation according to any one of claims 1 to 5, wherein the control unit estimates the gesture of the finger by comparing the bending angle of the specified finger with the gesture pattern acquired in advance. system. As the optical sensor, the ring-type device outputs light to the tip side of the finger and detects the bounce of the light on the finger, and outputs light to the base end side of the finger and the finger of the light. The finger movement estimation system according to any one of claims 1 to 6, further comprising a second sensor for detecting the bounce in the above. The claim includes, as the ring-type device, a first device attached to the first finger of the user and a second device attached to a second finger different from the first finger of the same user. Item 4. The finger movement estimation system according to any one of Items 1 to 7. The first device is attached to the first finger of one of the user's hands.
The finger movement estimation system according to claim 8, wherein the second device is attached to the second finger of the one hand of the same user. The first device is attached to the first finger of one of the user's hands.
The finger movement estimation system according to claim 8, wherein the second device is attached to the second finger of the other hand of the same user.

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