JP2024106902A - Gait state recognition device and gait state recognition method - Google Patents

Abstract

To provide a gait state recognition device and a gait state recognition method that can recognize and visualize a gait state of a subject as a change in time according to the number of steps.SOLUTION: A gait state recognition device, on the basis of the positions of the knee joint, heel and toe with the hip joint of a subject as the reference, after analyzing the gait structure for each walking cycle of the subject, time-sequentially compares the analysis result with a change in time according to the number of steps obtained as the similar analysis result from a healthy person that becomes the reference with the analysis result as the change in time according to the number of steps, analyzes the comparison result, and recognizes the gait state of the subject on the basis of the analysis result.SELECTED DRAWING: Figure 1

Description

The present invention relates to a gait state recognition device and a gait state recognition method, which are suitable for use, for example, in treatment and rehabilitation for people in the maintenance or daily living stage with lower limb disabilities or people with weakened legs.

In recent years, devices for improving movement function, known as Cybernics Treatment, which aims to improve the function of the brain, nerves, and muscles, have been approved as medical devices, and are now covered by insurance for patients with amyotrophic lateral sclerosis (ALS), spinal muscular atrophy, spinal-bulbar muscular atrophy (SBMA), Charcot-Marie-Tooth disease, muscular dystrophy, distal myopathy, congenital myopathy, and inclusion body myositis (IBM).

The lower limb type movement function improvement device for independent living support promotes the maintenance and improvement of physical functions and contributes to increasing the level of independence for people in the maintenance or daily living stage with disabilities in the lower limbs or people with weakened legs by controlling and assisting lower limb movement based on the bioelectric potential associated with voluntary muscle activity according to the individual's wishes.

This movement function improvement device needs to adaptively adjust the parameters for adjusting the amount of assistance for lower limb movement depending on the disease or condition. In fact, with the current model of movement function improvement device, more than 20 parameters need to be adjusted for each leg joint to support gait, and the current situation is that the settings vary depending on the experience of the person setting them and the condition of the subject. Furthermore, the reasons why the settings were selected are often unclear.

In order to recognize changes over time in a subject's walking function that accompany treatment or rehabilitation using such functional improvement devices, numerous methods have been proposed to evaluate the walking status of a subject.

For example, a gait analysis system has been proposed in which acceleration sensors or the like are attached to the hip joints, knee joints, or ankle joints of both legs of a walker, and the walking state of the walker is evaluated based on the joint angles of each joint measured by the acceleration sensors or the like (see Patent Document 1).

A walking motion assist device has also been proposed that calculates a thigh phase angle based on a hip joint angle-related signal detected at each sampling timing, applies the thigh phase angle at one sampling timing to a phase pattern function to calculate which walking motion timing in a walking cycle corresponds to that one sampling timing, applies the walking motion timing to an output torque pattern to calculate a torque value to be output at that one sampling timing, and controls the operation of an actuator to output an assist force of the calculated torque value, thereby providing an appropriate walking assist force in accordance with the walking state during the walking cycle even to users who have difficulty in walking normally with their lower legs (see Patent Document 2).

Furthermore, a gait evaluation device has been proposed that uses multiple sensors (posture sensor, imaging camera, load sensor, angle sensor) to acquire multiple movement amounts from the paralyzed body part of a paralyzed patient who has paralysis in the legs in accordance with the walking movement, and evaluates the walking movement as abnormal if at least one of the movement amounts satisfies any of multiple preset abnormal walking criteria (see Patent Document 3).

JP 2012-343 A JP 2018-50881 A European Patent No. 3943005

However, while the gait analysis system in the above-mentioned Patent Document 1 is capable of grasping the movement of the joints of the lower limbs and evaluating the walking state in more detail without using image processing, it does not disclose any method that suggests the walking phase, which is a unit of the walking cycle, or the relationship between both legs. In addition, it does not disclose anything about abnormal walking.

The walking motion assist device in Patent Document 2 uses a method to determine the assist torque from the pattern recognition results obtained by calculating the hip joint angle from the angle of the actuator that applies the assist force to the walking motion, and determines the torque value of the assist force by creating something similar to a walking phase using only the hip joint angle of a single leg. As a result, it is not possible to obtain a walking pattern based on the motion information of both legs, as in the walking phase, and therefore it is not possible to detect abnormal walking, nor is the walking phase used for evaluation.

Furthermore, the gait evaluation device in the above-mentioned Patent Document 3 sets multiple (seven) abnormal gait criteria for hemiplegic patients, and compares the amount of movement of the paralyzed body part at the walking timing of the swing phase and stance phase of the affected leg with the corresponding abnormal gait criteria to evaluate whether the walking movement is abnormal or not. Since it does not evaluate the walking state as an overall change over time, it is difficult to grasp the change in gait as a condition evaluation.

As described above, with the gait assessment methods described in Patent Documents 1 to 3, it is difficult to recognize the change in the walking function over time as the subject transitions from a state in which walking is difficult or abnormal to a state in which walking is equivalent to that of a healthy person. Therefore, there is a problem in that it is extremely difficult to efficiently set parameters for adjusting the amount of assistance for lower limb movement in the above-mentioned movement function improvement device.

The present invention has been made in consideration of the above points, and aims to propose a gait state recognition device and a gait state recognition method that can recognize and visualize a subject's gait state as a transition over time according to the number of steps.

In order to solve such problems, the present invention provides a gait state recognition device that recognizes the gait state of a subject by using a motion function improvement device that imparts to the subject power corresponding to each walking phase that constitutes the walking movement of the subject. The motion function improvement device includes a drive unit that actively or passively drives in conjunction with the movement of the subject's lower limbs, a joint circumference detection unit that detects physical quantities around the joints associated with the movement of the subject's lower limbs based on an output signal from the drive unit, and a knee joint, heel joint, and other joints based on the physical quantities detected by the joint circumference detection unit. The system is provided with a limb position information calculation unit that calculates the positions of the foot and toes, respectively; a gait structure analysis unit that analyzes the gait structure of the subject for each walking cycle based on the calculation results by the limb position information calculation unit; a transition comparison analysis unit that chronologically compares the analysis results by the gait structure analysis unit as a transition over time according to the number of steps with the transition over time according to the number of steps obtained as a similar analysis result from a standard able-bodied person, and analyzes the comparison results; and a gait state recognition unit that recognizes the gait state of the subject based on the analysis results by the transition comparison analysis unit.

As a result, the gait state recognition device compares the analysis results of the gait structure of the subject for each walking cycle as a change over time according to the number of steps with the change over time according to the number of steps obtained as a similar analysis result from a standard able-bodied subject, and analyzes the comparison results to recognize the subject's gait state, making it possible to efficiently set parameters for adjusting the amount of assistance for lower limb movement in the movement function improvement device.

In the present invention, the gait structure analysis unit calculates the proportion of each of a series of movement phases that constitute the gait structure for each walking cycle of the subject, and the transition comparison analysis unit generates a first graph that lists the transition of the subject's gait state by the number of steps, and compares it in time series with a second graph that corresponds to a standard healthy subject, and analyzes the comparison result. As a result, the gait state recognition device is able to visualize the gait state of the subject.

Furthermore, in the present invention, the gait state recognition unit extracts issues for each movement phase that constitutes the subject's walking cycle from the changes in the subject's walking state based on the analysis results from the transition comparison analysis unit. As a result, the gait state recognition device enables the subject himself to recognize problems in his own walking state with each step from the issues in each movement phase that constitutes the subject's walking cycle.

Furthermore, in the present invention, the gait condition recognition unit analyzes the correlation between the change in the subject's gait condition and the gait symptoms specific to a specific disease based on the analysis results by the change comparison analysis unit. As a result, the gait condition recognition device is able to detect the specific disease suffered by the subject at an early stage based on the analysis results of the correlation.

Furthermore, in the present invention, the motion phases constituting the walking cycle of the subject are made up of the following: when the subject uses one of the left and right legs as a supporting leg, a first supporting leg phase is formed when the height of the toe of the other leg and the height of the heel of the supporting leg match; a second supporting leg phase is formed when the lower knee of the supporting leg forward from the contact point becomes perpendicular to the ground; a third supporting leg phase is formed when the hip joint of the supporting leg extends dorsally; a fourth supporting leg phase is formed when the knee joint of the supporting leg relaxes and bends; a first swing leg phase is formed when the supporting leg is replaced by a swing leg and a contact point is formed; a second swing leg phase is formed when the thigh of the swing leg forward from the contact point becomes perpendicular to the ground; a third swing leg phase is formed when the front-to-back position of the heel of the swing leg matches that of the other leg; and a fourth swing leg phase is formed when the lower knee of the swing leg becomes perpendicular to the ground.

Furthermore, in the present invention, the movement function improvement device has a floor reaction force sensor that detects the pressure distribution on the soles of the left and right feet of the subject, and the limb position information calculation unit calculates the positions of the knee joint, heel, and toe based on the hip joint of the subject based on the physical quantities detected by the joint circumference detection unit and the detection results of the floor reaction force sensor.

Furthermore, in the present invention, a gait state recognition method for recognizing a gait state of a subject using a motion function improvement device that imparts to the subject power corresponding to each walking phase that constitutes the walking movement of the subject includes the following steps: a drive unit that is actively or passively driven in conjunction with the subject's lower limb movement is provided in the motion function improvement device, and the first step is to calculate the positions of the knee joint, heel, and toe of the subject based on the hip joint of the subject based on the physical quantities around the joints associated with the subject's lower limb movement detected based on the output signal of the drive unit; a second step is to analyze the gait structure of the subject for each walking cycle based on the calculation results from the first step; a third step is to compare the analysis results from the second step as a time progression according to the number of steps with the time progression according to the number of steps obtained as a similar analysis result from a standard healthy subject in a chronological order, and to analyze the comparison results; and a fourth step is to recognize the gait state of the subject based on the analysis results from the third step.

As a result, the gait state recognition method compares the analysis results of the gait structure of the subject for each walking cycle as a change over time according to the number of steps with the change over time according to the number of steps obtained as a similar analysis result from a standard able-bodied subject, and analyzes the comparison results to recognize the subject's gait state, making it possible to efficiently set parameters for adjusting the amount of assistance for lower limb movement in the movement function improvement device.

The present invention provides a gait state recognition device and a gait state recognition method that can recognize the gait state of a subject as a change over time according to the number of steps and automatically set parameters for adjusting the amount of assistance for lower limb movement in a movement function improvement device.

1 is a conceptual diagram illustrating a walking support system according to an embodiment of the present invention. 1 is a perspective view showing an external configuration of a motion improving device according to an embodiment of the present invention; 1 is a block diagram showing an internal configuration of an operation performance improving device according to an embodiment of the present invention; FIG. 1 is a block diagram showing an internal configuration of a gait state recognition device using a wearable action-assist device. FIG. 2 is an explanatory diagram showing each movement phase constituting a walking cycle of a subject. FIG. 6 is a conceptual diagram showing a state transition diagram of the walking cycle defined in FIG. 5 . 13 is a graph showing the change in the subject's gait condition when the movement function improving device is worn. 13 is a graph showing the change in average walking period for multiple trials. 13 is a graph showing the change in average walking period for multiple trials. 13 is a graph showing the change in average walking period for multiple trials. This is a diagram that summarizes the aspects of the series of movement phases that make up the walking cycle, as well as the actual state and challenges. 13 is a graph in which the detection rate by a floor reaction force sensor is superimposed on the transition of the walking cycle. This is a diagram showing the missing state of an operational phase in a heat map.

One embodiment of the present invention will be described in detail below with reference to the drawings.

(1) Configuration of the walking support system according to the present embodiment Fig. 1 shows a walking support system 1 according to the present embodiment. The walking support system 1 includes a motion function improving device 2 that assists the motion of a subject P, and a walking support device 3 that supports the rehabilitation of the subject P through walking motion. The motion function improving device 2 and the walking support device 3 are connected to each other so as to be able to communicate with each other via wire or wirelessly.

First, the walking support device 3 is configured such that a pair of left and right frames 6L and 6R are curved and erected from the tip of the treadmill 5 on either side of the treadmill 5, and the subject P can grasp the end portions of both frames 6L and 6R with both hands.

The treadmill 5 has a walking belt 7 that moves in a circular motion due to the rotation of rollers. The circulation speed of the walking belt 7 can be changed by changing the rotation speed of the rollers in response to actuator drive.

The walking support device 3 has a monitor 8, for example a liquid crystal display, mounted on a subframe (not shown) that bridges the left frame 6L and the right frame 6R that are erected from the treadmill 5, and is configured to display images of the results of operations performed by the operating unit and various information necessary to support the subject's walking.

In this way, in the walking assistance system 1, the subject P wearing the movement function improvement device 2 can support rehabilitation through walking by grasping one end of the pair of left and right frames 6L and 6R of the walking assistance device 3 with both hands to stabilize his or her posture during walking.

(2) Configuration of the Motion Function Improving Device According to the Present Embodiment Fig. 2 shows the motion function improving device 2 according to the present embodiment. The motion function improving device 2 is a device that applies to the subject power corresponding to each walking phase that constitutes the walking motion of the subject, detects bioelectric potential signals (surface myoelectric potential) generated when muscle force is generated by signals from the brain, and the motion angles of the hip joint and knee joint of the wearer, and operates to apply driving force from a driving mechanism based on these detection signals.

The lower limb type movement function improving device 2 in this embodiment has a waist frame 10 attached to the waist of the subject, a lower limb frame 11 attached to the lower limb of the wearer, a plurality of drive units 12L, 12R, 13L, 13R provided on the lower limb frame 11 corresponding to the joints of the wearer, cuffs 14L, 14R, 15L, 15R as auxiliary force application members attached to the lower limb frame 11 so as to apply the forces of the drive units 12L, 12R, 13L, 13R to the wearer from the front or rear, a control device 30 (see FIG. 3 described later) that controls the drive units 12L, 12R, 13L, 13R based on signals resulting from the wearer's lower limb movements, a back unit 16 equipped with the control device, and an operation unit (not shown) used by a caregiver.

The control device 30 (Fig. 3) can drive the lower limb frames 11 relatively around the output axes of the actuators of the drive units 12L, 12R, 13L, and 13R that correspond to the joints of the subject. Each drive unit 12L, 12R, 13L, and 13R is equipped with a group of sensors for detecting the drive torque and rotation angle of the actuator. The rear unit 16 is equipped with a battery unit (not shown) for supplying power to drive the entire device.

The waist frame 10 is a generally C-shaped member in plan view that opens forward and can receive the subject's waist and enclose it from its rear to both left and right sides. It has a rear waist frame part 17 located behind the subject, and a left waist frame part 18L and a right waist frame part 18R that extend forward while curving from both ends of the rear waist frame part 17.

The left and right hip frame sections 18L and 18R are connected to the rear hip frame section 17 via an opening adjustment mechanism (not shown). The bases of the left and right hip frame sections 18L and 18R are inserted and held within the rear hip frame section 17 so that they can slide left and right.

The lower limb frame 11 has a right lower limb frame 19R that is attached to the subject's right lower limb, and a left lower limb frame 19L that is attached to the subject's left lower limb. The left lower limb frame 19L and the right lower limb frame 19R are formed symmetrically.

The left lower leg frame 19L has a left thigh frame 20L located on the left side of the subject's left thigh, a left lower leg frame 21L located on the left side of the subject's left lower leg, and a left lower leg frame 22L on which the sole of the subject's left leg (the sole of the left shoe if shoes are worn) is placed. The left lower leg frame 19L is connected to the tip of the left waist frame section 18L via a waist connection mechanism 23L.

The right lower leg frame 19R has a right thigh frame 20R located on the right side of the subject's right thigh, a right lower leg frame 21R located on the right side of the subject's right lower leg, and a right lower leg frame 22R on which the sole of the subject's right leg (the sole of the right shoe if shoes are worn) is placed. The right lower leg frame 21R is connected to the tip of the right waist frame section 18R via a waist connection mechanism 23R.

The waist frame 10 (rear waist frame 17, right waist frame 18R, and left waist frame 18L) and the lower leg frame 11 (right lower leg frame 19R and left lower leg frame 19L) have a frame body formed into a long, thin plate shape, for example, from a metal such as stainless steel or carbon fiber, and are formed to be lightweight and highly rigid. In this embodiment, carbon fiber reinforced plastic (CFRP) and extra super duralumin, an aluminum alloy, are used as strength members.

Cuffs 14L, 14R, 15L, and 15R are provided on each of the left thigh frame 20L, right thigh frame 20R, left lower leg frame 21L, and right lower leg frame 21R.

The cuffs (hereafter referred to as "thigh cuffs") 14L, 14R provided on the left thigh frame 20L and right thigh frame 20R are supported by thigh cuff support mechanisms 24L, 24R attached to the lower ends of the thigh frame bodies. The thigh cuffs 14L, 14R have an arc-shaped attachment surface that can be fitted and placed against the subject's thigh. A fitting member is attached to the attachment surface of the thigh cuffs 14L, 14R so that they can fit closely to the subject's thigh without any gaps.

The cuffs (hereinafter referred to as "calf cuffs") 15L, 15R provided on the left crus frame 21L and right crus frame 21R are supported by crus cuff support mechanisms 25L, 25R attached to the upper ends of the upper elements. The crus cuffs 15L, 15R have an arc-shaped attachment surface that can be fitted and placed against the subject's crus. A fitting member is attached to the attachment surface of the crus cuffs 15L, 15R so that they can fit snugly against the subject's crus.

When actually putting this movement function improving device 2 on a subject, dedicated shoes 26L, 26R are put on the left and right feet, respectively, lower leg cuffs 15L, 15R are put on the left and right lower legs, respectively, and thigh cuffs 14L, 14R are put on the left and right thighs, respectively. Then, belts or the like are fastened to the shoes and cuffs so that the feet, lower legs, and thighs are integrated with the corresponding frames.

These special shoes 26L, 26R are made up of a pair of left and right shoes that hold the subject's feet in a tight fit from the toes to the ankles, and can measure load using a floor reaction force sensor (FRF sensor 60, described below) attached to the sole of the foot.

In this way, the movement function improvement device 2 can control and assist walking movements based on bioelectric potential signals associated with voluntary muscle activity according to the intentions of the subject wearing it.

(3) Internal System Configuration of the Movement Function Improving Device Fig. 3 is a block diagram showing the configuration of a control system of the movement function improving device 2. As shown in Fig. 3, the control system 2X of the movement function improving device 2 has a control device 30 that is responsible for overall control of the entire system, a data storage unit 31 in which various data is stored in a database so as to be readable and writable in response to commands from the control device 30, and drive units 12L, 12R, 13L, and 13R that actively or passively drive in conjunction with the lower limb movements of the subject.

In addition, a potentiometer 32 that detects the rotation angle of the output shaft is provided coaxially with the output shaft of the actuator in the drive units 12L, 12R, 13L, and 13R, and is adapted to detect the joint angle according to the subject's lower limb movement.

In addition, the lower limb frame 11 is equipped with an absolute angle sensor 33 for measuring the absolute angle of the thigh relative to the vertical direction. This absolute angle sensor 33 is composed of an acceleration sensor and a gyro sensor, and is used in sensor fusion, a method of extracting new information using data from multiple sensors.

To calculate the absolute thigh angle, a first-order filter is used to remove the effects of translational motion and temperature drift in each sensor. This first-order filter is calculated by weighting and adding up the values obtained from each sensor.

If the absolute angle of the thigh with respect to the vertical direction is θabs(k), the angular velocity obtained by the gyro sensor is ω, the sampling period is dt, and the acceleration obtained by the acceleration sensor is α, then θabs(t) can be expressed by the following equation (1).

A biosignal detection unit 40 having a biosignal detection sensor (group of electrodes) is placed on the body surface of the subject (mainly the body surface of the thigh) based on the joint associated with the subject's lower limb movement, and is configured to detect a bioelectric potential signal for moving the subject's knee joint.

The data storage unit 31 stores a command signal database 41 and a reference parameter database 42. The control device 30 is configured, for example, with a CPU (Central Processing Unit) chip having a memory, and includes an optional control unit 50, an autonomous control unit 51, a phase identification unit 52, and a gain change unit 53.

The optional control unit 50 causes the drive units 12L, 12R, 13L, and 13R to generate power according to the subject's will, based on the bioelectric potential signal acquired by the biosignal detection unit 40. Specifically, the optional control unit 50 supplies a command signal corresponding to the detection signal of the biosignal detection unit 40 to the power amplification unit 54. The optional control unit 50 applies a predetermined command function f(t) or gain P to the biosignal detection unit 40 to generate a command signal. This gain P is a preset value or function, and can be adjusted via the gain change unit 53 by external input.

It is also possible to select a method of controlling the actuator drive torque (torque magnitude and rotation angle) based on the knee joint angle data detected by the potentiometer 32. This method is effective in cases where the degree of gait disturbance associated with the subject's motor symptoms is relatively mild, or where the subject's skin is expected to become wet with sweat and there is a possibility that biosignal input from the biosignal detection unit 40 will not be obtained.

The data on the knee joint angle detected by the potentiometer 32, the data on the absolute angle of the thigh relative to the vertical direction detected by the absolute angle sensor 33, and the biosignal detected by the biosignal detection unit 40 are input to the reference parameter database 42.

Floor Reaction Force (FRF) sensors 60 are attached to the soles of the pair of dedicated shoes 26L, 26R to detect the pressure distribution on the soles of the subject's left and right feet. The FRF sensors 60 can measure the load acting on the soles of the feet separately for the forefoot (toes) and rearfoot (heel).

This FRF sensor 60 is composed of, for example, a piezoelectric element that outputs a voltage according to the applied load or a sensor whose capacitance changes according to the load, and can detect changes in load due to weight shifting and the presence or absence of contact between the wearer's legs and the ground.

Furthermore, with the pair of dedicated shoes 26L, 26R, the center of gravity position can be obtained from the balance of the load on the soles of the left and right feet based on the detection results of each FRF sensor 60. In this way, with the pair of dedicated shoes 26L, 26R, it is possible to estimate to which side of the subject's left or right foot the center of gravity is biased based on the data measured by each FRF sensor 60.

In addition to the shoe structure, each of the dedicated shoes 26L, 26R has an FRF sensor 60, an FRF control unit 61 consisting of an MCU (Micro Control Unit), and a transmission unit 62. The output of the FRF sensor 60 is converted into a voltage via a converter 63, and then the high frequency band is cut off via an LPF (Low Pass Filter) 64 before being input to the FRF control unit 61.

The FRF control unit 61 determines the load change and the presence or absence of contact with the ground due to the weight shift of the subject based on the detection results of the FRF sensor 60, and also determines the center of gravity position according to the load balance on the soles of the left and right feet. The FRF control unit 61 wirelessly transmits the determined center of gravity position as FRF data via the transmission unit 62 to the receiving unit 65 in the device body.

The control device 30 receives the FRF data wirelessly transmitted from the transmitter 62 of each dedicated shoe 26L, 26R via the receiver 65, and then stores the load and center of gravity position on the soles of the left and right feet based on the FRF data in the reference parameter database 42 of the data storage unit 31.

The phase identification unit 52 compares the knee joint angle data detected by the potentiometer 32 and the load data detected by the FRF sensor 60 with the knee joint angle and load of the reference parameters stored in the reference parameter database 42. Based on the comparison result, the phase identification unit 52 identifies the phase of the subject's movement.

Then, when the autonomous control unit 51 obtains the control data for the phase identified by the phase identification unit 52, it generates a command signal according to the control data for this phase and supplies the command signal to the power amplifier unit 54 to generate this power in the drive units 12L, 12R, 13L, and 13R.

The autonomous control unit 51 also receives the gain adjusted by the gain change unit 53 described above, generates a command signal according to this gain, and outputs it to the power amplifier 54. The power amplifier 54 controls the current that drives the actuators of the drive units 12L, 12R, 13L, and 13R to control the magnitude of the torque and the rotation angle of the actuators, thereby applying an assist force from the actuators to the knee joint of the subject.

In this way, the autonomous control unit 51 identifies the walking phase corresponding to the walking task of the subject based on the physical quantities detected by the joint circumference detection unit (potentiometer 32 and absolute angle sensor 33), and generates power corresponding to each walking phase in the drive units 12L, 12R, 13L, and 13R.

The power amplifier (drive current generator) 54 combines the control signals from the optional control unit 50 and the autonomous control unit 51, amplifies the drive current corresponding to the combined control signal, and supplies it to the actuators of the drive units 12L, 12R, 13L, and 13R. The torque of this actuator is transmitted to the knee joint of the subject as an assist force via the lower limb frame.

(4) Configuration of the Gait State Recognition Device According to this Embodiment In the present invention, the gait state of a subject is recognized by a gait state recognition device 70 (FIG. 4 described later) using the above-mentioned movement function improvement device 2.

On this premise, the biopotential signals of the lower limb muscles measured using the movement function improvement device 2 may be useful for recognizing the gait state of the subject, since the subject's muscle activity is measured every time walking treatment or rehabilitation is performed using the movement function improvement device 2. The biopotential signals reflect changes in the subject's neuromuscular system caused by action potentials generated during movement control.

In this invention, we focus on the posture of the lower limbs, which is measured from the angle state of the hip and knee joints in both legs of the subject, and obtain the characteristics of walking by extracting information about each step taken while walking and measuring the state from the state of the walking cycle.

This gait state recognition device 70 is a control system component provided within the control device 30 in the above-mentioned movement function improvement device 2, and as shown in FIG. 4, includes a limb position information calculation unit 71, a gait structure analysis unit 72, a transition comparison analysis unit 73, and a gait state recognition unit 74.

The limb position information calculation unit 71 calculates the positions of the knee joint, heel, and toe, with the subject's hip joint as the reference (origin position), based on the physical quantities detected by the joint circumference detection unit (potentiometer 32 and absolute angle sensor 33) described above.

In the present invention, the limb position information calculation unit 71 may calculate the positions of the knee joint, heel, and toe with respect to the hip joint of the subject based not only on the physical quantities detected by the joint circumference detection unit, but also on the physical quantities and the detection results of a floor reaction force sensor (FRF sensor 60) that detects the pressure distribution on the soles of the subject's left and right feet.

The gait structure analysis unit 72 analyzes the gait structure for each walking cycle of the subject based on the calculation results by the limb position information calculation unit 71. Specifically, the gait structure analysis unit calculates the occupancy rate of each of a series of movement phases that constitute the walking structure for each walking cycle of the subject.

Here, the motion phases constituting the walking cycle of the subject are represented as in Figures 5(A) to (H). That is, the motion phases are as follows: when the subject uses either the left or right leg as a supporting leg, a first supporting leg phase wsp1 (Figure 5(A)) is formed when a contact point is formed at which the height of the toe of the other leg coincides with the height of the heel of the supporting leg; a second supporting leg phase wsp2 (Figure 5(B)) is formed when the lower part of the knee of the supporting leg forward of the contact point becomes perpendicular to the ground; a third supporting leg phase wsp3 (Figure 5(C)) is formed when the hip joint of the supporting leg extends dorsally; and a fourth supporting leg phase wsp4 (Figure 5(D)) is formed when the knee joint of the supporting leg relaxes and bends. It consists of a fourth supporting leg phase wsp4 (Fig. 5(D)), a first swing leg phase wsw1 (Fig. 5(E)) when the supporting leg switches to the swing leg and a ground contact point is formed, a second swing leg phase wsw2 (Fig. 5(F)) when the thigh of the swing leg forward of the ground contact point becomes perpendicular to the ground, a third swing leg phase wsw3 (Fig. 5(G)) when the anterior-posterior position of the heel of the swing leg coincides with the other leg, and a fourth swing leg phase wsw4 (Fig. 5(H)) when the lower knee part of the swing leg becomes perpendicular to the ground.

The state transition diagram of the walking cycle defined above is shown in Figure 6. Starting with a phase start (or tam-out) wst, a walking cycle consisting of the first to fourth supporting leg phases wsp1 to wsp4 and the first to fourth swing leg phases wsw1 to wsw4 is repeated. In this state transition diagram, by setting the first supporting leg phase wsp1 and the first swing leg phase wsw1 to have priority in state transitions, it becomes possible to detect information for each step without stagnation in the state transitions midway.

The transition comparison analysis unit 73 compares the analysis results by the gait structure analysis unit 72 as transitions over time according to the number of steps in chronological order with transitions over time according to the number of steps obtained as similar analysis results from a standard able-bodied person, and analyzes the comparison results. Specifically, the transition comparison analysis unit 73 generates the transitions in the subject's gait state as a first graph that lists the occupancy rate of each movement phase calculated by the gait structure analysis unit 72 for each number of steps, and compares the transitions over time with a second graph corresponding to the standard able-bodied person in chronological order to analyze the comparison results.

The gait state recognition unit 74 recognizes the gait state of the subject based on the analysis results by the transition comparison analysis unit 73. Specifically, the gait state recognition unit 74 extracts issues for each movement phase that constitutes the walking cycle of the subject from the transition of the gait state of the subject based on the analysis results by the transition comparison analysis unit 73.

In this way, the gait state recognition device 70 compares the analysis results of the gait structure of the subject for each walking cycle as a change over time according to the number of steps with the change over time according to the number of steps obtained as a similar analysis result from a standard able-bodied person, and analyzes the comparison results to recognize the gait state of the subject.

As a result, the gait state recognition device 70 can efficiently set parameters for adjusting the amount of assistance for lower limb movement in the movement function improvement device 2.

In Figures 7(A)-(C), a color is assigned to each movement phase, and the changes in the subject's gait state when wearing the movement function improving device 2 are graphed for one trial for each of the subject's left and right legs, with the number of steps on the horizontal axis and the percentage of each movement phase on the vertical axis. In each of Figures 7(A)-(C), the upper row shows the changes in the gait state for the left leg, and the lower row shows the changes in the gait state for the right leg.

Figure 7(A) is the second graph corresponding to a healthy individual, Figure 7(B) is the first graph corresponding to a subject who is able to walk without wearing the movement function device 2, and Figure 7(C) is the first graph corresponding to a subject who has just started wearing the movement function improvement device 2 and has difficulty walking in everyday life. According to the second graph shown in Figure 7(A), most movement phases are always detected in the healthy individual, while according to the first graphs shown in Figures 7(B) and (C), in both cases the subjects are ill, and missing movement phases and instability in the gait cycle are visually confirmed.

For example, in the first graph shown in Figure 7 (B), if the second supporting leg phase wsp2 and the third supporting leg phase wsp3 are missing, the position of the foot when the subject's gait touches the floor differs from that of normal walking, and the lower part of the knee of the supporting leg is bent at a relatively large angle when the supporting leg touches the ground after the swing leg. This suggests that the subject is walking timidly, with the knee not fully extended during the swing leg, the hip joint swing is small, or the posture is leaning forward.

When such a missing supporting leg phase occurs, the subject can be advised to be fully conscious of the final swing of the swing leg, or if the hip joint swing is insufficient, the drive torque on the flexion side of the hip joint or the drive torque on the extension side of the knee joint can be controlled and set to be larger, thereby contributing to improving the subject's gait. In this way, the gait state recognition device 70 makes it possible to visualize the gait state of the subject.

Furthermore, Figures 8 to 10(B) show typical examples of graphs of changes in the gait state of a subject when wearing the movement function improvement device 2, averaging the occupancy rate of movement phases for each trial for the subject's left and right legs, with the horizontal axis representing the number of trials, and showing changes in the average walking cycle for multiple trials. In all of Figures 8 to 10(B), the upper row shows the changes in the gait state for the left leg, and the lower row shows the changes in the gait state for the right leg.

Figure 8 shows a graph corresponding to a healthy subject, where all movement phases are visible in every trial, although there are variations. On the other hand, Figure 9 shows a graph corresponding to a subject with spinal cord injury who is normally able to walk with the aid of a prosthetic device, where at first there are missing movement phases for both legs, then one leg, and finally both legs are clearly visible (at the same level as a healthy subject). Experiments have shown that some subjects with cerebrovascular disorders such as strokes also go through similar changes.

Figure 10(A) shows a graph corresponding to a subject with a stroke who has a strong tendency to walk with a swinging gait, and Figure 10(B) shows a graph with the physical quantity (drive angle) detected by the joint circumference detection unit (potentiometer 32 and absolute angle sensor 33) on the vertical axis, corresponding to the transition of the average walking period for each of the multiple trials in Figure 10(A).

In Figures 10 (A) and (B), although the movement phases of both feet of the subject were clearly visible (similar to that of a healthy person) (transition period a), the movement phase was missing midway and then reappeared (transition period b), and at the same time, differences in the joint angles between the left and right sides sometimes occurred (transition period c).

This is a graph shape that often occurs in subjects who have suffered a stroke, where the purpose of walking changes from a light walk (transition period a) to walking very fast (transition period b), resulting in a strong tendency towards the usual roundabout gait. In this case, the fine movements of the supporting leg, which are the second supporting leg phase wsp2, the third supporting leg phase wsp3 and the fourth supporting leg phase wsp4, are small, the swing leg is long (first swing leg phase wsw1 to fourth swing leg phase wsw4), and it can be predicted that the left leg, which has a large operating joint angle, is being locked.

In such cases, the walking speed of the subject should be increased, even if it is by walking in a circular motion, so that the subject can get used to the speed, and then the task should be shifted to walking lightly while maintaining that speed again (transition period c).

For example, Figure 11 shows a chart summarizing the aspects of a series of movement phases that make up a walking cycle, the actual state, and issues (solutions). This chart makes it possible to recognize the gait state and issues when the movement function improvement device 2 is worn from the aspects of the movement phases. Note that when averaging over trials, movement phases that are detected less frequently can be seen as having a smaller occupancy rate.

If the movement phase features a lot of fourth supporting leg phase wsp4 and fourth swing leg phase wsw4 and is unstable and variable within one trial, it can be inferred that the actual state is that the subject's gait is unstable and that the subject is walking very slowly, and the task can be identified as simply moving the lower limbs and getting the subject used to the gait.

In addition, if the detection frequency of the second supporting leg phase wsp2 is low (if it appears small when averaged within a trial), it can be inferred that the actual condition is that the subject's knee is not fully extended at the end of the leg swing, and the tasks identified are to have the subject be conscious of putting their weight on the sole of their foot, to ensure that their hip joint is fully extended during the swing leg, and to fully extend their knee before the swing leg hits the ground at the end.

Similarly, if the detection frequency of the second supporting leg phase wsp2 is low, it can be inferred that the other actual state is that the whole body is leaning forward (to the left or right), and the task can be identified as improving the subject's posture or increasing the hip joint extension.

Furthermore, if the detection frequency of the third supporting leg phase wsp3 is low, it can be inferred that the actual state is that the subject's hip joint is not fully extended, and the task can be identified as prioritizing hip joint extension in the settings of the movement function improvement device 2 and getting the subject to be conscious of kicking backwards.

Furthermore, if the detection frequency of the fourth supporting leg phase wsp4 is low, it can be inferred that the actual state is that the subject's knee is not relaxed and is in a locking state, and the task can be identified as having the subject practice relaxing the knee.

Furthermore, if the movement phase is such that the second swing leg phase wsw2 and the third swing leg phase wsw3 are detected less frequently, it can be inferred that the actual state is that the subject's hip joints are always bent and the upper body is flexed, and the task can be identified as adjusting the gait while encouraging the subject to be conscious of their posture.

Furthermore, when the motion phase is such that the second swing leg phase wsw2 and the third swing leg phase wsw3 are detected simultaneously and the detection frequency of the second swing leg phase wsw2 is low, it can be inferred that the actual state is that the subject's knee is in a locking state, and the task can be identified as having the subject practice relaxing the knee.

Furthermore, if the fourth swing leg phase wsw4 is detected less frequently, it can be inferred that the actual state is that the subject's hip joint falls before it is fully flexed, and the task can be identified as having the subject be conscious of how they place their weight on the sole of their foot when supporting with the opposite leg.

Similarly, if the movement phase aspect shows that the fourth swing leg phase wsw4 is detected less frequently, another actual state can be inferred to be that the subject's posture is leaning forward or rocking, and the task can be identified as improving the subject's posture or increasing the hip joint swing.

In this way, the gait state recognition device 70 is able to visualize the gait state of the subject by visualizing a series of movement phases that make up a walking cycle. In the gait state recognition device 70, the gait state recognition unit 74 is configured to extract issues for each movement phase that makes up the subject's walking cycle from the changes in the subject's gait state based on the analysis results by the transition comparison analysis unit 73. As a result, the gait state recognition device 70 makes it possible for the subject to recognize problems with his or her own walking state with each step, based on the issues for each movement phase that makes up the subject's walking cycle.

The gait state recognition device 70 configured as described above can recognize the subject's gait state as a change over time according to the number of steps, and can automatically set parameters for adjusting the amount of assistance for lower limb movement in the movement function improvement device 2. Therefore, if it is possible to grasp the subject's past and present condition, predict the future condition, and confirm that the subject is approaching normal walking, it will be possible to automatically support therapy that has traditionally been performed by a therapist.

(5) Other Embodiments As described above, in this embodiment, the gait state recognition device 70 is configured to visualize a series of movement phases that constitute a walking cycle. However, the present invention is not limited to this. By obtaining the ratio at which all movement phases (first to fourth supporting leg phases wsp1 to wsp4 and first to fourth swing leg phases wsw1 to wsw4) are detected while the subject is walking, the degree to which the walking state is similar to that of a healthy person may be visualized and displayed, thereby making it possible to easily visually recognize the gait state of the subject.

For example, FIG. 12 shows a graph in which the detection rate by the floor reaction force sensor (FRF sensor 60) is superimposed on a graph showing the changes in the average walking cycle for multiple trials as shown in FIG. 9 and FIG. 10(A) described above. The upper part of FIG. 12 shows the changes in the gait state for the left leg, and the lower part shows the changes in the gait state for the right leg.

The graph in Figure 12 shows the detection rate obtained by the floor reaction force sensor (FRF sensor 60) from the left and right legs superimposed on the occupancy rate of all movement phases (first to fourth supporting leg phases wsp1 to wsp4 and first to fourth swing leg phases wsw1 to wsw4), with the horizontal axis representing the number of trials and the vertical axis representing the rate of good walking phases (from 0 to 1). The closer the rate of good walking phases on the vertical axis is to 1, the closer it is to the walking of a healthy person. The graph in Figure 12 shows that the subject's right leg is significantly closer to a healthy gait, and it can also be confirmed that a gait difference has occurred between the subject's left and right legs.

In addition, in this embodiment, the gait state recognition device 70 visualizes the gait state of the subject by visualizing a series of movement phases that make up a walking cycle, but the present invention is not limited to this. For each trial, the number of times a movement phase is missing relative to the number of steps may be calculated as a ratio, and the ratio may be expressed in a chart such as the heat map diagram shown in FIG. 13. As a result, it becomes easier to visually recognize how the subject is walking and what the issues are. In addition, it is possible to predict the characteristics of the subject's gait, which can change the issues that need to be improved, leading to increased awareness of the subject.

Furthermore, in this embodiment, the gait state recognition device 70 has been described as having the gait state recognition unit 74 extract issues for each movement phase that constitutes the walking cycle of the subject, and having the subject recognize problems with his or her own walking state for each step from the issues for each movement phase; however, the present invention is not limited to this, and the gait state recognition unit 74 may analyze the correlation between the transition of the subject's gait state and walking symptoms specific to a specific disease based on the analysis results by the transition comparison analysis unit 73. As a result, the gait state recognition device 70 can detect the specific disease suffered by the subject at an early stage based on the analysis results of the correlation.

Furthermore, in this embodiment, the subject walks on the treadmill 5 of the walking assistance device 3 to assist in rehabilitation, but the present invention is not limited to this, and the subject using the motion function improvement device 2 may also walk together with a mobile walker.

1...walking support system, 2...motion function improvement device, 2X...control system, 3...walking support device, 5...treadmill, 6L...left frame, 6R...right frame, 7...walking belt, 8...monitor, 10...waist frame, 11...lower limb frame, 12L, 12R, 13L, 13R...drive unit, 26L, 26R...dedicated shoes, 30...control device, 31...data storage unit, 32...potentiometer, 33...absolute angle sensor, 40...biological signal detection unit , 41...command signal database, 42...reference parameter database, 50...optional control unit, 51...autonomous control unit, 52...phase identification unit, 53...gain change unit, 54...power amplification unit, 60...FRF sensor, 61...FRF control unit, 62...transmitting unit, 63...converter, 64...LPF, 65...receiving unit, 70...gait state recognition device, 71...limb position information calculation unit, 72...gait structure analysis unit, 73...transition comparison analysis unit, 74...gait state recognition unit.

Claims (14)

A gait state recognition device that recognizes a gait state of a subject by using a motion function improvement device that imparts to the subject power corresponding to each walking phase constituting the walking movement of the subject,
The motion enhancement device includes:
A drive unit that actively or passively drives in conjunction with the subject's lower limb movement;
a joint circumference detection unit that detects a physical quantity around the joint accompanying a lower limb movement of the subject based on an output signal from the drive unit;
a limb position information calculation unit that calculates the positions of a knee joint, a heel, and a toe of the subject based on a hip joint of the subject on the basis of the physical quantities detected by the joint circumference detection unit;
a gait structure analysis unit that analyzes a gait structure for each walking cycle of the subject based on a calculation result by the limb position information calculation unit;
a transition comparison analysis unit that compares the analysis result by the gait structure analysis unit as a transition over time according to the number of steps with a transition over time according to the number of steps obtained as a similar analysis result from a standard able-bodied person, and analyzes the comparison result;
a gait state recognition unit that recognizes a gait state of the subject based on an analysis result by the transition comparison analysis unit. the gait structure analysis unit calculates an occupancy rate of a series of motion phases constituting a gait structure for each gait cycle of the subject,
2. The gait state recognition device according to claim 1, wherein the transition comparison analysis unit generates a first graph, which lists the transition of the gait state of the subject, an occupancy rate of each of the movement phases calculated by the gait structure analysis unit, for each number of steps, and compares the first graph with a second graph corresponding to a reference able-bodied person in chronological order, to analyze the comparison result. 3. The gait state recognition device according to claim 1, wherein the gait state recognition unit extracts issues of each movement phase constituting a walking cycle of the subject from the transition of the gait state of the subject based on a result of the analysis by the transition comparison analysis unit. 3. The gait condition recognition device according to claim 1, wherein the gait condition recognition unit analyzes a correlation between a transition of the gait condition of the subject and a gait symptom specific to a specific disease based on an analysis result by the transition comparison analysis unit. Each movement phase constituting the walking cycle of the subject is
3. The gait state recognition device according to claim 1 or 2, characterized in that, when one of the left and right legs of the subject is used as a supporting leg, the gait state recognition device comprises: a first supporting leg phase when a ground contact point is formed at which the height of the toe of the other leg and the height of the heel of the supporting leg match; a second supporting leg phase when a lower part of the knee of the supporting leg forward of the ground contact point becomes perpendicular to the ground; a third supporting leg phase when the hip joint of the supporting leg extends dorsally; a fourth supporting leg phase when the knee joint of the supporting leg relaxes and bends; a first swing leg phase when the supporting leg switches to a swing leg and the ground contact point is formed; a second swing leg phase when the thigh of the swing leg forward of the ground contact point becomes perpendicular to the ground; The motion function improving device has a floor reaction force sensor that detects pressure distribution on the left and right soles of the subject,
The gait state recognition device according to claim 1 or 2, characterized in that the limb position information calculation unit calculates the positions of the knee joint, heel and toe of the subject based on the hip joint based on the physical quantities detected by the joint periphery detection unit and the detection results of the floor reaction force sensor. The motion enhancement device includes:
a biosignal detection unit having a group of electrodes arranged on a body surface of the subject based on a joint associated with a lower limb movement of the subject, for detecting a bioelectric potential signal of the subject;
an optional control unit that generates a power according to the will of the subject in the drive unit based on the biopotential signal acquired by the biosignal detection unit;
an autonomous control unit that identifies a walking phase according to a walking motion of the subject based on the physical quantity detected by the joint circumference detection unit, and causes the drive unit to generate a power corresponding to each of the walking phases;
a drive current generating unit that synthesizes control signals from the voluntary control unit and the autonomous control unit and supplies a drive current corresponding to the synthesized control signal to the drive unit. A gait state recognition method for recognizing a gait state of a subject using a motion function improving device that imparts to the subject power corresponding to each walking phase constituting the walking movement of the subject, comprising:
A first step of calculating the positions of the knee joint, heel, and toe of the subject relative to the hip joint based on physical quantities around the joints associated with the subject's lower limb movement detected based on an output signal from the drive unit, the drive unit being provided in the motion function improving device and being capable of actively or passively driving in conjunction with the subject's lower limb movement;
A second step of analyzing a gait structure for each walking cycle of the subject based on a result of the calculation in the first step;
a third step of comparing the analysis result obtained by the second step as a time progression corresponding to the number of steps with a time progression corresponding to the number of steps obtained as a similar analysis result from a standard healthy subject in a time series manner, and analyzing the comparison result;
and a fourth step of recognizing a gait state of the subject based on a result of the analysis in the third step. In the second step, an occupancy rate of a series of motion phases constituting a gait structure is calculated for each gait cycle of the subject,
9. The gait state recognition method according to claim 8, wherein in the third step, a transition of the gait state of the subject is generated as a first graph in which an occupancy rate of each of the movement phases calculated in the second step is enumerated for each number of steps, and the first graph is compared in time series with a second graph corresponding to a reference able-bodied person, and a result of the comparison is analyzed. 10. The gait state recognition method according to claim 8 or 9, wherein in the fourth step, a problem of each movement phase constituting a walking cycle of the subject is extracted from a transition of the gait state of the subject based on a result of the analysis in the third step. 10. The gait condition recognition method according to claim 8 or 9, wherein in the fourth step, a correlation between a transition of the gait condition of the subject and a gait symptom specific to a specific disease is analyzed based on a result of the analysis in the third step. Each movement phase constituting the walking cycle of the subject is
10. The gait state recognition method according to claim 8 or 9, characterized in that, when one of the left and right legs of the subject is used as a supporting leg, the method comprises: a first supporting leg phase when a ground contact point is formed at which the height of the toe of the other leg and the height of the heel of the supporting leg match; a second supporting leg phase when a lower part of the knee of the supporting leg forward of the ground contact point becomes perpendicular to the ground; a third supporting leg phase when the hip joint of the supporting leg extends dorsally; a fourth supporting leg phase when the knee joint of the supporting leg relaxes and bends; a first swing leg phase when the supporting leg switches to a swing leg and the ground contact point is formed; a second swing leg phase when the thigh of the swing leg forward of the ground contact point becomes perpendicular to the ground; a third swing leg phase when the front-to-rear position of the heel of the swing leg matches that of the other leg; and a fourth swing leg phase when the lower part of the knee of the swing leg becomes perpendicular to the ground. The motion function improving device detects pressure distribution on the left and right soles of the subject,
10. The gait state recognition method according to claim 8, wherein in the first step, positions of a knee joint, a heel, and a toe of the subject relative to a hip joint are calculated based on the physical quantities around the joints and the pressure distribution on each of the soles of the feet. The gait state recognition method according to claim 8 or 9, characterized in that the movement function improvement device combines and performs voluntary control in which the drive unit generates a power in accordance with the will of the subject based on a bioelectric potential signal acquired from a body surface part of the subject with reference to a joint associated with the lower limb movement of the subject, and autonomous control in which the drive unit generates a power corresponding to each of the walking phases, identifying walking phases corresponding to the walking movement of the subject based on physical quantities around the joints associated with the lower limb movement of the subject detected based on the output signal of the drive unit, and supplies a drive current corresponding to the combined control signal to the drive unit.

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