An intelligent lower limb rehabilitation training wheelchair and training method

Abstract

The present invention discloses an intelligent lower limb rehabilitation training wheelchair and a training method. The lower limb rehabilitation training wheelchair includes an electric wheelchair body, a pressure sensor, a rehabilitation training controller, and two execution units. The pressure sensor collects the lower limb muscle strength of the user and sends the data to the rehabilitation training controller. The rehabilitation training controller identifies the lower limb muscle strength level of the user, and according to the lower limb muscle strength level, gives the output thrust value of the execution unit, and completes the lower limb rehabilitation training of the user by driving the execution unit. During the lower limb rehabilitation training stage, the training method can adjust the output thrust of the execution unit in real time, and through multiple rehabilitation stages, help the user to carry out lower limb rehabilitation training and lower limb muscle strength strengthening.

Description

Technical Field

[0001] The present invention relates to rehabilitation training equipment, and particularly to an intelligent lower limb rehabilitation training wheelchair and a training method. Background Art

[0002] According to the statistics of the United Nations Population Division in 2017, as of 2017, the global elderly population aged 60 and above was approximately 962 million, accounting for 12.7% of the world's total population. In 2050, the population aged 60 and above will reach 2.1 billion. At the same time, the number of patients with nerve injuries caused by strokes and the like is also increasing year by year globally. Most elderly people and patients with nerve injuries will have varying degrees of motor dysfunction, such as hemiplegia, paraplegia, etc. Whether it is the elderly or the disabled, due to their limited lower limb mobility, it seriously affects their ability to take care of themselves, bringing a heavy burden to families and society. In addition to conventional treatment methods such as surgery and drugs, patients also need to undergo long-term rehabilitation training to maximize their motor recovery ability and prevent sequelae. How to better help them technically and meet their needs in life and work, thereby improving their quality of life, has become an important direction in the research of rehabilitation engineering.

[0003] Early lower limb rehabilitation training relied on one-on-one guidance training by rehabilitation therapists. Therefore, the rehabilitation effect largely depended on the level and experience of rehabilitation therapists. The gradual increase in the number of patients, the shortage of rehabilitation therapists, and the uneven treatment levels have promoted the development of lower limb rehabilitation trainers. However, due to their large volume and high price, they are mostly applicable to the rehabilitation departments and rehabilitation treatment centers of hospitals and are difficult to popularize to ordinary families. As a common disability assistance mobile device, wheelchairs have been widely used in the market. Currently, the main wheelchairs in the market are manual wheelchairs, electric wheelchairs, and a small number of intelligent wheelchairs. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent lower limb rehabilitation training wheelchair and a training method, which are particularly suitable for the elderly and the disabled, solve the problem of inconvenient rehabilitation training for users, enable users to complete rehabilitation training at home without going to a rehabilitation center or hospital, and provide a more convenient and simple intelligent lower limb rehabilitation training method for users.

[0005] The technical solution for realizing the present invention is: an intelligent lower limb rehabilitation training wheelchair, including an electric wheelchair, a plurality of pressure sensors, a rehabilitation training controller, and two execution units. The pressure sensors are fixed on the inner wall of the lower limb leg guards of the electric wheelchair. When the user binds the lower limbs, the pressure sensors fit against the calf muscles of the user. The execution unit includes a lead screw, a servo motor, and a servo motor driver. One end of the lead screw is connected to the servo motor, and the other end is connected to a pedal of the electric wheelchair.

[0006] The pressure sensor and the servo motor driver are respectively connected to the rehabilitation training controller. The servo motor and the servo motor driver are connected. The pressure sensor collects the lower limb muscle strength of the user and sends it to the rehabilitation training controller. The rehabilitation training controller identifies the lower limb muscle strength level, and according to the lower limb muscle strength level, gives the output thrust value of the execution unit and sends the thrust value to the servo motor driver. The pedal is controlled through the servo motor and the lead screw to complete leg training.

[0007] A training method for an intelligent lower limb rehabilitation training wheelchair is as follows:

[0008] Step 1: According to the lower limb muscle strength collected by the pressure sensor, establish a lower limb muscle strength mapping model. The lower limb muscle strength mapping model is:

[0009]

[0010] where τ h is the knee joint torque; ω1 is the weight coefficient of the RMS1 eigenvalue for the estimated joint torque, ω2 is the weight coefficient of the RMS2 eigenvalue for the estimated joint torque, ω3 is the weight coefficient of θ mesu for the estimated joint torque, where ω1 ∈ (0.85, 0.9), ω2 ∈ (0.7, 0.8), ω3 ∈ (0.95, 1); RMS1 represents the pressure eigenvalue collected by the pressure sensor, RMS2 represents the output thrust eigenvalue of the execution unit; θ mesu is the knee joint lift angle.

[0011] Step 2: According to the lower limb muscle strength, and introducing force information feedback and motion information feedback, obtain the lower limb muscle strength level, and calculate the force required for leg lifting. The formula for the force required for leg lifting is as follows:

[0012]

[0013]

[0014] where V out1 is the analog voltage value output by the pressure sensor, V out2 is the analog input voltage value of the execution unit; Vcc is the rated voltage value of the pressure sensor, f max is the rated measurement value of the pressure sensor, d(V) is the current output torque of the execution unit, f p is the force required for leg lifting; f t is the output torque of the execution unit.

[0015] Step 3: According to the lower limb muscle strength mapping model, the lower limb muscle strength level and the force required for leg lifting, obtain the output thrust of the execution unit; complete the rehabilitation training.

[0016] Compared with the prior art, the remarkable advantages of the present invention are as follows:

[0017] (1) By installing lower limb rehabilitation training equipment on the electric wheelchair body, the integration of the electric wheelchair and the lower limb rehabilitation equipment is realized, enabling users to complete lower limb rehabilitation training in suitable scenarios.

[0018] (2) The intelligent control of the user's lower limb rehabilitation training is realized, including the following functions: 1) Collect the user's lower limb muscle strength and identify the lower limb muscle strength level; 2) Obtain the output thrust of the execution unit (4) according to the muscle strength level; 3) During the lower limb treatment process, the lower limb muscle strength level is detected in real time and the output thrust is adjusted. 4) During the training process, voice broadcast is carried out to help the trainer understand the training process.

[0019] (3) Adjust the training plan in a timely manner according to the user's lower limb training needs, and realize the multi-function of the intelligent lower limb rehabilitation wheelchair. Description of the Drawings

[0020] Figure 1 is a schematic structural diagram of the intelligent lower limb rehabilitation training wheelchair of the present invention.

[0021] Figure 2 is a block diagram of the working principle of the intelligent lower limb rehabilitation training wheelchair of the present invention. Detailed Embodiments

[0022] In order to better understand the steps, advantages and implementation process of the present invention, the present invention will be further described below with reference to the accompanying drawings of the specification.

[0023] Combined with Figure 1 , an intelligent lower limb rehabilitation training wheelchair described in the present invention includes an electric wheelchair 1, a rehabilitation training controller 3, two execution units 4 and a plurality of pressure sensors 2. The pressure sensors 2 are fixed on the inner wall of the lower limb leg guards of the electric wheelchair 1. When the user binds the lower limbs, the pressure sensors 2 fit against the user's calf muscles; the execution unit 4 includes a lead screw, a servo motor and a servo motor driver. One end of the lead screw is connected to the servo motor, and the other end is connected to a pedal of the electric wheelchair 1.

[0024] The lower limb muscle strength is generated by the rectus femoris, vastus lateralis and vastus medialis muscles driving the knee joint. By obtaining the lower limb muscle strength, the lower limb muscle strength level is identified and the lower limb rehabilitation training plan is determined. The pressure sensors 2 and the servo motor driver are respectively connected to the rehabilitation training controller 3, the servo motor and the servo motor driver are connected. The pressure sensors 2 collect the user's lower limb muscle strength and send it to the rehabilitation training controller 3. The rehabilitation training controller 3 identifies the lower limb muscle strength level, gives the output thrust value of the execution unit 4 according to the lower limb muscle strength level, and sends the thrust value to the servo motor driver. The pedal is controlled through the servo motor and the lead screw to complete the leg training.

[0025] The intelligent lower limb rehabilitation training wheelchair further includes a voice module connected to the rehabilitation training controller 3. The voice module is arranged on the electric wheelchair 1 and conducts voice broadcasts during the lower limb rehabilitation training to help the user understand the training process and control the start and stop of the training. Phased voice broadcasts are adopted. In different training stages, the user is prompted by voice about the current execution steps. If the user feels unwell during the training, the start and stop of the training can be controlled through the voice module at any time.

[0026] Combined with Figure 2 , a specific implementation method of a training method for an intelligent lower limb rehabilitation training wheelchair includes the following steps:

[0027] Step 1: Establish a lower limb muscle strength mapping model based on the lower limb muscle strength collected by the pressure sensor 2. The lower limb muscle strength mapping model is:

[0028]

[0029] where τ h is the knee joint torque; ω1 is the weight coefficient of the RMS1 eigenvalue for the estimated joint torque, ω2 is the weight coefficient of the RMS2 eigenvalue for the estimated joint torque, ω3 is the weight coefficient of θ mesu for the estimated joint torque, where ω1 ∈ (0.85, 0.9), ω2 ∈ (0.7, 0.8), ω3 ∈ (0.95, 1); RMS1 represents the pressure eigenvalue collected by the pressure sensor 2, and RMS2 represents the output thrust eigenvalue of the execution unit 4; θ mesu is the knee joint lift angle.

[0030] By obtaining the values of the pressure sensor 2, the output thrust of the execution unit 4, and the knee joint angle, the knee joint torque is calculated. The knee joint angle is obtained by calculating the rotation angle of the servo motor of the execution unit 4. The original data of the pressure sensor 2 and the output thrust data of the execution unit 4 have obvious tremors and are not smooth. In this step, the RMS eigenvalues of the two types of data are extracted to reduce noise interference.

[0031] Step 2: Based on the lower limb muscle strength, and introducing force information feedback and motion information feedback, obtain the lower limb muscle strength level, and calculate the force required for leg lifting. The formula for the force required for leg lifting is as follows:

[0032]

[0033]

[0034] where V out1 is the analog voltage value output by the pressure sensor 2, V out2 is the analog input voltage value of the execution unit 4; Vcc is the rated voltage value of the pressure sensor 2, fmax is the rated measurement value of the pressure sensor 2, d(V) is the current output torque of the execution unit 4, and f p is the force required to lift the leg; f t is the output torque of the execution unit 4.

[0035] Step 3: Obtain the output thrust of the execution unit 4 according to the lower limb muscle strength mapping model, the lower limb muscle strength level, and the force required to lift the leg; complete the rehabilitation training.

[0036] During the lower limb rehabilitation training process, the magnitude of the output thrust is adjusted in real time to determine the training intensity control strategy of the rehabilitation training intensity controller. According to the feedback signal of the pressure sensor and the magnitude of the Nth output thrust, determine the magnitude of the (N + 1)th output thrust. The control strategy of the rehabilitation training intensity controller is as follows:

[0037] f N+1 = F(f N , f 测 )

[0038] where f N is the magnitude of the Nth output thrust, f 测 is the force measured by the pressure sensor, and f N+1 is the magnitude of the (N + 1)th output thrust.

[0039] The lower limb rehabilitation training process is divided into the following three stages: the assisted leg-lifting stage, the free leg-lifting stage, and the resistance leg-lifting stage, and the rehabilitation plan is determined by judging the muscle strength level. The assisted leg-lifting stage is suitable for users who cannot lift their legs independently. The execution unit 4 is used to complete the leg-lifting action to help users with low lower limb muscle strength complete lower limb training, so as to restore partial lower limb muscle strength. The free leg-lifting stage is suitable for users who can barely complete the leg-lifting action. The lower limb muscle strength is used to complete the lower limb training to help users complete the leg-lifting action rehabilitation training without auxiliary power. The resistance leg-lifting stage is suitable for users who can complete the normal leg-lifting action. Under the condition of obtaining normal lower limb muscle strength, the lower limb strength is strengthened, and the execution unit 4 is used to apply resistance, and the user needs to resist the resistance for intensive training.

[0040] Function and effect of the embodiment

[0041] To verify the effectiveness of an intelligent lower limb rehabilitation training wheelchair and its training method proposed by the present invention, 10 volunteers were selected for the experiment and the results were recorded. In order to accurately and intuitively reflect the rehabilitation effect of the intelligent lower limb rehabilitation training wheelchair, the first group of five volunteers was the control group, and volunteers with normal lower limb muscle strength were selected. The second group of five volunteers was the experimental group, and volunteers with weaker lower limb muscle strength were selected. The control group collected the pressure sensor data and lower limb muscle strength data during normal leg-lifting training, and the experimental group observed the experimental effect through lower limb rehabilitation training. The final effect is shown in Table 1:

[0042] Table 1 Analysis of Lower Limb Strength in Three Test Conditions

[0043]

[0044] As can be seen from the table, after a lower limb intelligent rehabilitation training wheelchair designed by the present invention completes the basic training plan, the user can move from an almost stationary leg-lifting movement before the experiment to the pressure sensor data and lower limb muscle strength data reaching 74% of the normal person control group. After the intensive training experiment, these two data can reach 94% of the normal person control group, which can reflect that: after the basic lower limb rehabilitation training, the lower limb muscle strength of the user is basically restored and can meet the basic needs of daily activities. After the intensive training, the lower limb strength of the user is restored to the normal muscle strength level, and the training effect is remarkable.

Claims

1. A method for calculating the execution output thrust of an intelligent lower limb rehabilitation training wheelchair, characterized in that, Intelligent lower limb rehabilitation training wheelchair, comprising an electric wheelchair (1), a rehabilitation training controller (3), two execution units (4) and a number of pressure sensors (2). The pressure sensors (2) are fixed to the inner wall of the lower limb leg bindings of the electric wheelchair (1). When the user binds the lower limbs, the pressure sensors (2) fit against the user's calf muscles. The execution unit (4) includes a lead screw, a servo motor and a servo motor driver. One end of the lead screw is connected to the servo motor, and the other end is connected to a pedal of the electric wheelchair (1). The pressure sensors (2) and the servo motor driver are respectively connected to the rehabilitation training controller (3). The servo motor is connected to the servo motor driver. The pressure sensors (2) collect the user's lower limb muscle strength and send it to the rehabilitation training controller (3). The rehabilitation training controller (3) identifies the lower limb muscle strength level, and according to the lower limb muscle strength level, gives the output thrust value of the execution unit (4), and sends the thrust value to the servo motor driver, and controls the pedal through the servo motor and the lead screw to complete the leg training. It further includes a voice module connected to the rehabilitation training controller (3). The voice module is arranged on the electric wheelchair (1) and conducts voice announcements during the lower limb rehabilitation training to help the user understand the training process and control the start and stop of the training. The lower limb muscle strength is generated by the rectus femoris, vastus lateralis and vastus medialis muscles driving the knee joint. The steps for calculating the execution output thrust are as follows: Step 1: According to the lower limb muscle strength collected by the pressure sensors (2), establish a lower limb muscle strength mapping model. The lower limb muscle strength mapping model is: Among them, τ h is the knee joint torque; ω1 is the weight coefficient of the RMS1 eigenvalue for the estimated joint torque, ω2 is the weight coefficient of the RMS2 eigenvalue for the estimated joint torque, ω3 is the weight coefficient of θ mesu for the estimated joint torque, where ω1 ∈ (0.85, 0.9), ω2 ∈ (0.7, 0.8), ω3 ∈ (0.95, 1); RMS1 represents the pressure eigenvalue collected by the pressure sensor (2), and RMS2 represents the output thrust eigenvalue of the execution unit (4); θ mesu is the knee joint lift angle; Step 2: According to the lower limb muscle strength, and introducing force information feedback and motion information feedback, obtain the lower limb muscle strength level, and calculate the force required to lift the leg. The formula for calculating the force required to lift the leg is as follows: Among them, V out1 is the analog voltage value output by the pressure sensor (2), V out2 is the analog input voltage value of the execution unit (4); Vcc is the rated voltage value of the pressure sensor (2), f max is the rated measurement value of the pressure sensor (2), d(V) is the current output torque of the execution unit (4), f p is the force required to lift the leg; f t is the output torque of the execution unit (4); Step 3: According to the lower limb muscle strength mapping model, the lower limb muscle strength level and the force required to lift the leg, obtain the output thrust of the execution unit (4).

2. The method for calculating the execution output thrust of the intelligent lower limb rehabilitation training wheelchair according to claim 1, characterized in that: During the lower limb rehabilitation training process, the thrust magnitude of the execution unit (4) is output in real time.

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