A waist assisting exoskeleton and a control method thereof

Abstract

This invention provides a lumbar assistive exoskeleton and its control method, aiming to achieve posture and movement recognition of the lumbar assistive exoskeleton to meet functions such as walking assistance and carrying assistance. The hardware components of this method mainly include a sensing system and a control system. The sensing system consists of angle sensors and tilt sensors, while the control system consists of a control circuit board, control buttons, joint motors, and a battery. This method uses one lumbar tilt sensor and two hip joint angle sensors to determine the user's gait and lumbar posture, thereby avoiding the increased signal processing time and reduced signal stability caused by numerous sensors. This improves the stability and anti-interference capability of the exoskeleton control. The control system provides corresponding power according to the user's movement state and mode requirements to achieve walking, carrying, and other related assistance.

Description

Technical Field

[0001] This invention belongs to the field of assistive exoskeletons, and relates to an exoskeleton for assisting walking and carrying with lumbar support, and a control method thereof. Background Technology

[0002] Whether it's lower back pain caused by prolonged walking or lumbar injuries due to occupational strain, "lower back pain" is a common condition in modern society. To enhance physical fitness and reduce energy consumption during exercise, assistive exoskeletons have emerged. Based on the location of assistance, exoskeletons can be categorized into lower limb exoskeletons, upper limb exoskeletons, lumbar exoskeletons, and full-body exoskeletons. Lumbar assistive exoskeletons can assist in hip joint rotation, aiding in walking and the upright and flexing movements of the lower back. Summary of the Invention

[0003] To achieve functions such as posture and motion recognition and assistance in active exoskeletons, it is necessary to select appropriate sensing and driving methods based on the mechanical structure. The control method will greatly affect the assistive performance of the exoskeleton.

[0004] This invention proposes a lumbar assistive exoskeleton, which includes: a sensing system and a control system; The sensing system is used to sense the angles of the left and right hip joints and the lumbar inclination of the human body. The working modes of the lumbar-assisted exoskeleton include: carrying mode and walking mode; In handling mode, the control system uses a long short-term neural network to determine the human posture based on the angles of the left and right hip joints and the lumbar tilt angle, and predicts the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state. Based on the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state, and in combination with the level of assistance selected by the user, the system provides corresponding handling assistance. In walking mode, the control system determines the phase of the human walking gait based on the angles of the left and right hip joints and the lumbar tilt angle. Based on the phase of the human walking gait, it predicts the human movement trend and provides assistance to the left and right hip joints according to the human movement trend.

[0005] In one embodiment, the sensing system includes a left hip joint angle sensor, a right hip joint angle sensor, and a tilt sensor; The left hip joint angle sensor is used to detect the angle of the left hip joint in a human body; The right hip angle sensor is used to detect the angle of the right hip joint in a human body. Tilt sensors are used to detect the tilt angle and acceleration of the human waist.

[0006] In one embodiment, it further includes: a left hip joint motor and a right hip joint motor; The left hip joint module consists of a left hip joint motor and a left hip joint angle sensor; the left hip joint angle sensor collects the rotation angle of the left hip joint motor. The right hip joint module consists of a right hip joint motor and a right hip joint angle sensor; the right hip joint angle sensor collects the rotation angle of the right hip joint motor.

[0007] In one embodiment, it further includes: a control panel, the control panel including a left panel and a right panel; The left panel includes a power button and a power display device for the waist-assisting exoskeleton, while the right panel is used to control the assist level and switch working modes.

[0008] This invention also proposes a control method for a lumbar-assisted exoskeleton, which includes: The working modes of the lumbar-assisted exoskeleton include: carrying mode and walking mode; In handling mode, the control system uses a long short-term neural network to determine the human posture based on the angles of the left and right hip joints and the lumbar tilt angle, and predicts the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state. Based on the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state, and in combination with the level of assistance selected by the user, the system provides corresponding handling assistance. In walking mode, the control system determines the phase of the human walking gait based on the angles of the left and right hip joints and the lumbar tilt angle. Based on the phase of the human walking gait, it predicts the human movement trend and provides assistance to the left and right hip joints according to the human movement trend.

[0009] In one embodiment, it further includes: detecting the angle of the left hip joint of the human body using a left hip joint angle sensor; The angle of the right hip joint of a human body is detected using a right hip joint angle sensor. Tilt sensors are used to measure the tilt angle and acceleration of the human waist.

[0010] In one embodiment, it further includes: using a control panel to control the assist level and switch working modes.

[0011] The advantages of this invention compared to existing technologies are: a simple overall framework and fewer sensors. It uses only a waist tilt sensor and two hip joint angle sensors to determine human gait and waist posture, thereby avoiding the increased signal processing time and reduced signal stability caused by numerous sensors, and improving the stability and anti-interference ability of exoskeleton control. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the lumbar support exoskeleton structure of the present invention; Figure 2 This is a schematic diagram of the waist-assisted exoskeleton control method of the present invention. Detailed Implementation

[0013] This invention provides a lumbar assistive exoskeleton, which includes: a sensing system and a control system; The sensing system is used to sense the angles of the left and right hip joints and the lumbar inclination of the human body. The working modes of the lumbar-assisted exoskeleton include: carrying mode and walking mode; In handling mode, the control system uses a long short-term neural network to determine the human posture based on the angles of the left and right hip joints and the lumbar tilt angle, and predicts the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state. Based on the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state, and in combination with the level of assistance selected by the user, the system provides corresponding handling assistance. In walking mode, the control system determines the phase of the human walking gait based on the angles of the left and right hip joints and the lumbar tilt angle. Based on the phase of the human walking gait, it predicts the human movement trend and provides assistance to the left and right hip joints according to the human movement trend.

[0014] The sensing system includes a left hip angle sensor, a right hip angle sensor, and a tilt sensor. The left hip angle sensor detects the angle of the left hip joint; the right hip angle sensor detects the angle of the right hip joint. The tilt sensor detects the lumbar tilt angle and acceleration.

[0015] The left hip joint motor and the left hip joint angle sensor constitute the left hip joint module; the left hip joint angle sensor collects the rotation angle of the left hip joint motor; the right hip joint motor and the right hip joint angle sensor constitute the right hip joint module; the right hip joint angle sensor collects the rotation angle of the right hip joint motor.

[0016] The left panel includes a power button and a power display device for the waist-assisting exoskeleton, while the right panel is used to control the assist level and switch working modes.

[0017] Figure 1 This is a schematic diagram of a lumbar assistive exoskeleton. It describes the electronic control components and signal and power wiring methods of the lumbar assistive exoskeleton. It includes a tilt sensor 1, a controller 2, a 48V lithium battery 3, a left hip joint module 4, a right hip joint module 5, a left panel 6, and a right panel 7.

[0018] The tilt sensor 1 detects the angle and acceleration of the human lower back and communicates with the controller 2 via the CAN protocol. The controller 2 handles overall system signal processing, decision-making, and motion control. A 48V lithium battery 3 provides system power, supplying 48V DC power to the joint modules, which is then converted to voltage by a voltage converter and supplied to the controller 2, left panel 6, and right panel 7. The left hip joint module 4 and right joint module 5 include an angle sensor and a motor. The angle sensor is integrated inside the motor to collect the angle of motor rotation. Each joint module collects angle information and provides assist output at one hip joint. The left panel 6 includes a power button and a power display, while the right panel 7 contains two illuminated buttons for switching assist levels and operating modes.

[0019] The design incorporates two operating modes: a handling mode and a walking mode. In handling mode, angle sensors and lumbar tilt sensors acquire human posture information, which is then processed by a long short-term neural network to determine the posture and predict the next state of human angle change. Combined with the user-selected level of assistance, corresponding handling assistance is provided. In walking mode, sensors acquire hip joint angle information and lumbar angle to determine the human walking gait phase, and hip joint walking assistance is provided based on the movement trend.

[0020] like Figure 2 The present invention also proposes a control method for a lumbar assistive exoskeleton, which includes: The working modes of the lumbar-assisted exoskeleton include: carrying mode and walking mode; In handling mode, the control system uses a long short-term neural network to determine the human posture based on the angles of the left and right hip joints and the lumbar tilt angle, and predicts the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state. Based on the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state, and in combination with the level of assistance selected by the user, the system provides corresponding handling assistance. In walking mode, the control system determines the phase of the human walking gait based on the angles of the left and right hip joints and the lumbar tilt angle. Based on the phase of the human walking gait, it predicts the human movement trend and provides assistance to the left and right hip joints according to the human movement trend.

[0021] The left hip joint angle sensor is used to detect the angle of the left hip joint of the human body, the right hip joint angle sensor is used to detect the angle of the right hip joint of the human body, and the tilt sensor is used to measure the tilt angle and acceleration of the human waist.

[0022] Use the control panel to adjust the boost level and switch working modes.

[0023] like Figure 2The tilt sensor 1 detects the angle and acceleration of the human lower back and communicates with the controller 2 via the CAN protocol. The controller 2 handles overall system signal processing, decision-making, and motion control. A 48V lithium battery 3 provides system power, supplying 48V DC power to the joint modules, which is then converted to voltage by a voltage converter and supplied to the controller 2, left panel 6, and right panel 7. The left hip joint module 4 and right joint module 5 include an angle sensor and a motor. The angle sensor is integrated inside the motor and collects the angle of motor rotation. Each joint module collects angle information at one hip joint and provides assist output. The left panel 6 includes a power button and a power display, while the right panel 7 contains two illuminated buttons for switching assist level and operating mode.

[0024] The hardware of this invention includes: a sensing system and a control system. The sensing system consists of an angle sensor and a tilt sensor; the control system consists of a control circuit board, control buttons, a joint motor, and a battery.

[0025] The angle sensor includes a left hip joint angle sensor and a right hip joint angle sensor, which are mainly used to detect the rotation angle of the human hip joint.

[0026] The tilt sensor is a waist tilt sensor, mainly used for human back posture detection.

[0027] The control circuit board includes a control system chip, a voltage conversion module, and an information interface, and mainly realizes signal analysis and overall circuit control.

[0028] The control buttons include a power button, a power assist adjustment button, and a mode adjustment button.

[0029] The joint motors include a left hip joint motor and a right hip joint motor, which are mainly used to drive the movement of the human hip joint to achieve the assistive function.

Claims

1. A lumbar support exoskeleton, characterized in that, It includes: Sensing and control systems; The sensing system is used to sense the angles of the left and right hip joints and the lumbar inclination of the human body. The working modes of the lumbar-assisted exoskeleton include: carrying mode and walking mode; In handling mode, the control system uses a long short-term neural network to determine the human posture based on the angles of the left and right hip joints and the lumbar tilt angle, and predicts the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state. Based on the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state, and in combination with the level of assistance selected by the user, the system provides corresponding handling assistance. In walking mode, the control system determines the phase of the human walking gait based on the angles of the left and right hip joints and the lumbar tilt angle. Based on the phase of the human walking gait, it predicts the human movement trend and provides assistance to the left and right hip joints according to the human movement trend.

2. The lumbar support exoskeleton according to claim 1, characterized in that, The sensing system includes a left hip joint angle sensor, a right hip joint angle sensor, and a tilt sensor; The left hip joint angle sensor is used to detect the angle of the left hip joint in a human body; The right hip angle sensor is used to detect the angle of the right hip joint in a human body. Tilt sensors are used to detect the tilt angle and acceleration of the human waist.

3. The lumbar support exoskeleton according to claim 1, characterized in that, Further includes: Left hip joint motor, right wide joint motor; The left hip joint module consists of the left hip joint motor and the left hip joint angle sensor. The left hip joint angle sensor collects the rotation angle of the left hip joint motor. The right hip joint module consists of a right hip joint motor and a right hip joint angle sensor; the right hip joint angle sensor collects the rotation angle of the right hip joint motor.

4. The lumbar support exoskeleton according to claim 1, characterized in that, Further includes: Control panel, which includes a left panel and a right panel; The left panel includes a power button and a power display device for the waist-assisting exoskeleton, while the right panel is used to control the assist level and switch working modes.

5. A method for controlling a lumbar-assisted exoskeleton, characterized in that, It includes: The working modes of the lumbar-assisted exoskeleton include: carrying mode and walking mode; In handling mode, the control system uses a long short-term neural network to determine the human posture based on the angles of the left and right hip joints and the lumbar tilt angle, and predicts the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state. Based on the changes in the angles of the left and right hip joints and the lumbar tilt angle in the next state, and in combination with the level of assistance selected by the user, the system provides corresponding handling assistance. In walking mode, the control system determines the phase of the human walking gait based on the angles of the left and right hip joints and the lumbar tilt angle. Based on the phase of the human walking gait, it predicts the human movement trend and provides assistance to the left and right hip joints according to the human movement trend.

6. The control method for the lumbar assist exoskeleton according to claim 5, characterized in that, Further includes: The angle of the left hip joint of a human body is detected using a left hip joint angle sensor. The angle of the right hip joint of a human body is detected using a right hip joint angle sensor. Tilt sensors are used to measure the tilt angle and acceleration of the human waist.

7. The lumbar support exoskeleton according to claim 1, characterized in that, Further includes: Use the control panel to adjust the boost level and switch working modes.

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