CN111588376A - Lower limb gait information extraction equipment based on electromyographic signals and angle signals - Google Patents

Abstract

The invention relates to a lower limb gait information extraction device based on electromyographic signals and angle signals, which comprises a test bed base, a Hall angle sensor, a flange coupler, a 9V battery, a single chip microcomputer, an upper computer and a human body fixing bandage, wherein the upper computer is a computer serial port debugging assistant and can quickly read serial port data; the muscle extracted by the electromyographic signal is rectus femoris and biceps femoris. The lower limb gait information acquisition system acquires human gait information by measuring four signals of a human body rectus femoris electromyographic signal, a human body biceps femoris electromyographic signal, a hip joint angle signal and a human body knee joint angle signal, and improves the accuracy, the anti-interference performance and the timeliness of human gait recognition by a method of combining the electromyographic signal and a physical signal.

Description

A device for extracting lower limb gait information based on EMG and angle signals

technical field

The invention relates to the technical field of gait detection and health monitoring, in particular, to a device for extracting gait information of lower limbs based on myoelectric signals and angle signals.

Background technique

Human gait information has a very broad application prospect and can provide a research basis for many research fields. It is a behavioral feature that combines biology and kinematics. With the rapid development of manufacturing, computer industry, and rehabilitation medical industry, gait, as the most commonly used behavioral feature of the human body, has been applied in more and more fields.

For example, in the rehabilitation medical industry, through the acquisition of human gait, it can help doctors to better observe the patient's lower limb condition, provide targeted treatment plans, and check the patient's rehabilitation treatment effect; in the field of robotics, lower limb gait is very important for exoskeleton robots. and lower extremity prosthetics play a vital role. It can help the control system to clearly identify the motion intention of the human body, help the system to analyze effectively and adopt the correct control strategy; in the field of video games and VR, gait acquisition can add rich game experience to the game and increase the scalability of game development . At present, there are many ways to obtain gait information. The main signal sources include human electromyography signals, joint angle signals, acceleration signals, plantar pressure signals and images. EMG is a biological signal. When the human body needs to perform an action, the brain will issue instructions in the form of electrical pulses, which are transmitted to the muscles through neurons and the spinal cord. After the signal is transmitted to the muscle, the muscle will generate an action potential, and the action potential will move along the muscle fiber method, forming a weak current on the skin surface, generating a muscle electrical signal. The EMG signal can quickly reflect the movement trend of the human body, but it has the shortcomings of poor anti-interference and easy to be affected by the outside world. EMG signals are mostly acquired with surface electrode stickers. The physical signal is acquired by various sensors, which has strong anti-interference ability, but has the shortcomings of slow response speed and untimely feedback. The image signal is too dependent on external equipment, and it is necessary to perform image processing on the collected image, so it is difficult to avoid the characteristics of inaccurate recognition.

For example, the Chinese invention patent with publication number CN110731784A discloses a platform-based gait measurement system. The subject cannot be measured on a mobile platform. The gait data analysis and storage device electrically connected to the output end of the image acquisition device and the fixed Visual markings on the left and right feet of the subject to identify the location of the left and right feet. The camera acquisition module performs gait analysis on the acquired images after photographing the subject's left and right feet. When this method is used, it needs a certain platform foundation, and there are certain limitations only for the recognition of feet, and it is easily disturbed by the surrounding environment in the process of image processing.

Another example is the Chinese invention patent with the publication number CN108992071A, which discloses a lower limb skeletal gait analysis system, which uses an inertial measuring instrument, an angle encoder and a multi-sensor module of a plantar pressure distribution sensor to collect motion data of the lower limbs of the human body, And perform human gait analysis. The three signal sources used in the invention are all physical signals, and the disadvantage is that the time delay is difficult to control when reflecting the movement gait.

Another example is the Chinese invention patent with publication number CN110327054A, which discloses a gait analysis method and device based on acceleration and angular velocity sensors. time, calculate the ground-to-air ratio, and then collect the state of human foot movement. Since the device only collects foot signals, it has certain limitations in use.

SUMMARY OF THE INVENTION

In order to solve the problem of high use cost in the prior art, the present invention provides a lower limb gait information extraction device based on myoelectric signal and angle signal. The movable device is worn on the side of the lower limbs of the human body to obtain the gait signals of the lower limbs, and the EMG signals of the rectus femoris and biceps femoris, which are the most active in the lower limbs of the human body, and the angle signals of the hip and knee joints are extracted as signals. source.

The lower limb gait information extraction device based on the electromyographic signal and the angle signal of the present invention solves the problems of complex structure and poor adsorption effect in the prior art.

A device for extracting lower limb gait information based on EMG signals and angle signals, including a test bench base, a Hall angle sensor, a flange coupling, 4 9V batteries, an rduino Uno microcontroller, a host computer and a human body fixing strap The upper computer is a computer serial port debugging assistant, which can quickly read serial port data. The lower limb gait information extraction device also includes a muscle electrical signal sensor. After the muscle electrical signal is transmitted by the human body to the muscle, the muscle will produce action. Potentials, action potentials move along the muscle fibers, and form weak currents on the surface of the skin; the muscles extracted from EMG signals are the rectus femoris and biceps femoris. The lower limb gait information acquisition system obtains human gait information by measuring four kinds of signals: human rectus femoris EMG signal, biceps femoris EMG signal, hip joint angle signal, and knee joint angle signal. The combined method improves the accuracy, anti-interference and timeliness of human gait recognition.

The lower limb gait information extraction device based on the EMG signal and the angle signal of the present invention has the characteristics of being wearable, portable and convenient to move. The straps are located at the waist, calf, and ankle joints. When wearing the test bench, the hip and knee joints of the lower limbs can move freely without hindrance.

Preferably in any of the above solutions, the test bench base is composed of three 3mm colorless transparent acrylic plates, the three acrylic plates represent the waist, thigh and calf respectively, and the lengths are 110mm, 450mm and 350mm respectively. , the width is 40mm.

Preferably in any of the above solutions, the Hall angle sensor is a non-contact Hall magnetic angle sensor, capable of 360° rotation without dead angle, using Japanese NSK bearings, with a resolution of 4096 bits, an operating voltage of 5V, and an output of 5V. 0-5V voltage, and small size, small damping, easy installation.

In any of the above solutions, preferably, the electrical muscle signal sensor is a sensor that directly outputs electrical muscle pulse signals. The muscle electrical signal sensor is a sensor that is small in size, fast in transmission and can directly output muscle electrical pulse signals. This muscle electrical sensor adopts a wearable design.

In any of the above solutions, preferably, the muscle electrical signal sensor is equipped with three electrodes, which are a middle electrode, an end electrode and a reference electrode, respectively, and are powered by 9V.

In any of the above solutions, it is preferable that the electrical muscle signal sensor is directly connected to the microprocessor, the signal is amplified, corrected and smoothed by ADC, and the EMG pulse signal or the raw electrical muscle signal is output.

In any of the above solutions, preferably, the microcontroller is an Arduino Uno microcontroller.

In any of the above solutions, preferably, the inner diameter of the flange coupling is 6 mm, and the outer diameter is 10 mm.

Preferably in any of the above solutions, the Hall angle sensor is a KALAMOYI Hall angle sensor.

In any of the above solutions, preferably, the human body strap is a 5cm wide Velcro.

Description of drawings

FIG. 1 is a schematic structural diagram of a preferred embodiment of a device for extracting lower limb gait information based on myoelectric signals and angle signals according to the present invention.

Fig. 2 is an enlarged view of position A in the preferred embodiment shown in Fig. 1 of the device for extracting gait information of lower limbs based on myoelectric signals and angle signals according to the present invention.

Fig. 3 is an enlarged view of position B in the preferred embodiment shown in Fig. 1 of the device for extracting gait information of lower limbs based on myoelectric signals and angle signals according to the present invention.

4 is a schematic structural diagram of the flange coupling matched with the preferred embodiment shown in FIG. 1 of the device for extracting gait information of lower limbs based on myoelectric signals and angle signals according to the present invention.

5 is a schematic diagram of hardware wiring constructed by the preferred embodiment shown in FIG. 1 of the device for extracting lower limb gait information based on myoelectric signals and angle signals according to the present invention.

Detailed ways

The specific implementations of the device for extracting lower limb gait information based on myoelectric signals and angle signals of the present invention will be further described below with reference to the accompanying drawings.

As shown in FIG. 1 , a schematic structural diagram of a preferred embodiment of a device for extracting lower limb gait information based on myoelectric signals and angle signals according to the present invention.

A device for extracting lower limb gait information based on EMG signals and angle signals, including a test bench base, a Hall angle sensor, a flange coupling, 4 9V batteries, an rduino Uno microcontroller, a host computer and a human body fixing strap The upper computer is a computer serial port debugging assistant, which can quickly read serial port data. The lower limb gait information extraction device also includes a muscle electrical signal sensor. After the muscle electrical signal is transmitted by the human body to the muscle, the muscle will produce action. Potentials, action potentials move along the muscle fibers, and form weak currents on the surface of the skin; the muscles extracted from EMG signals are the rectus femoris and biceps femoris. The lower limb gait information acquisition system obtains human gait information by measuring four kinds of signals: human rectus femoris EMG signal, biceps femoris EMG signal, hip joint angle signal, and knee joint angle signal. The combined method improves the accuracy, anti-interference and timeliness of human gait recognition.

The lower limb gait information extraction device based on the EMG signal and the angle signal of the present invention has the characteristics of being wearable, portable and convenient to move. The straps are located at the waist, calf, and ankle joints. When wearing the test bench, the hip and knee joints of the lower limbs can move freely without hindrance.

In this embodiment, the base of the test bench is composed of three 3mm colorless and transparent acrylic plates, the three acrylic plates represent the waist, thigh and calf respectively, the lengths are 110mm, 450mm, and 350mm, respectively, and the widths are 40mm. The joint between the acrylic plates is connected with the Hall angle sensor through the flange coupling, and it can freely rotate with the joint of the human body. The three acrylic plates represent waist part 1, thigh part 2, and calf part 3 respectively.

During the work, first use 3mm screws to fix the flange coupling to the fixing holes of the joints of waist part 1 and thigh part 2 as shown in Figure 1 (see Figure 2 and Figure 3); then use 5mm screws Fix the Hall angle sensor on the thigh part 2 and calf part 3 joints of the acrylic plate as shown in Figure 1-3 (as shown in Figure 2 and Figure 3), and finally use 3mm screws to fix the Hall angle sensor. The angle sensor bearing is fixed with the middle hole of the flange coupling as shown in Figure 4, so as to realize the joint movement of the acrylic plate.

In this embodiment, the Hall angle sensor is a non-contact Hall magnetic angle sensor, which can rotate 360° without dead angle, adopts Japanese NSK bearing, the resolution reaches 4096 bits, the working voltage is 5V, and the output voltage is 0-5V , and the volume is small, the damping is small, and the installation is simple.

In this embodiment, the electrical muscle signal sensor is a sensor that directly outputs electrical muscle pulse signals. The muscle electrical signal sensor is a sensor that is small in size, fast in transmission and can directly output muscle electrical pulse signals. This muscle electrical sensor adopts a wearable design.

In this embodiment, the muscle electrical signal sensor is equipped with three electrodes, namely the middle electrode, the terminal electrode and the reference electrode, which are powered by 9V, and the middle electrode and the end electrode of the two muscle electrical signals are respectively attached to the rectus femoris muscle. The center position of the muscle and biceps femoris muscle, the reference electrode is attached to the position of less active muscle.

In this embodiment, the Arduino Uno, the electrical muscle signal sensor, and the 9V battery are fixed on the acrylic board 2 with Velcro, which is convenient for disassembly.

In this embodiment, the muscle electrical signal sensor is directly connected to the microprocessor, and the signal is amplified, corrected and smoothed by the ADC, and the EMG pulse signal or the original muscle electrical signal is output.

In this embodiment, the microcontroller is an Arduino Uno microcontroller.

In this embodiment, the inner diameter of the flange coupling is 6 mm, and the outer diameter is 10 mm.

In this embodiment, the Hall angle sensor is a KALAMOYI Hall angle sensor.

In this embodiment, the human body strap is a 5cm wide Velcro. When working, the lower limb signal acquisition test bench is worn, using Velcro straps to fix the test bench on the waist, calf and ankle joints of the human body respectively.

Finally, referring to FIG. 5 , a schematic diagram of hardware wiring constructed according to the preferred embodiment shown in FIG. 1 of the device for extracting lower limb gait information based on myoelectric signals and angle signals of the present invention.

In this embodiment, each EMG signal sensor is powered by two 9V batteries, and the Arduino Uno is connected to the host computer and powered by the host computer.

The acquisition process is to connect the Arduino Uno to the host computer, turn on the 9 battery power, the Arduino Uno and the sensor start to work, open the serial port debugging assistant of the host computer, the host computer starts to read the serial port data, and the human body starts to move.

After the human body wears the experimental bench, the surface electrodes of the EMG sensor are pasted to the center of the rectus femoris and biceps femoris muscles, and each joint is moved, and the tightness of the straps is adjusted to a comfortable level. Arduino Uno is connected to the host computer, the 9V battery is turned on, the system starts to supply power, the data starts to transmit, and the serial port for programming prints the rectus femoris EMG signal, biceps femoris EMG signal, hip joint angle signal, and knee joint angle in dictionary format. Signal, the voltage value is converted into an angle value using the characteristics of the Hall angle sensor before printing. Output sEMG1, sEMG2, Angle1, and Angle2 as a set of data.

It is not difficult for those skilled in the art to understand that the device for extracting lower limb gait information based on myoelectric signals and angle signals of the present invention includes any combination of various parts in this specification. Due to space limitations and for the sake of brevity of the description, these combinations are not described in detail here, but the scope of the present invention constituted by any combination of the various parts constituted by this specification is self-evident after reading this specification.

Claims (10)

1. The utility model provides a low limbs gait information draws equipment based on flesh electrical signal and angle signal, includes test bench base, hall angle sensor, flange shaft coupling, 4 sections 9V batteries, rduino Uno singlechip, host computer and human fixed bandage, the host computer is computer serial ports debugging assistant, can read serial data its characterized in that fast: the lower limb gait information extraction equipment also comprises a muscle electrical signal sensor, wherein muscle electrical signals are weak currents formed on the surface of the skin when the muscle electrical signals are that after a human body transmits an execution action signal to muscles, the muscles can generate action potentials which move along a muscle fiber method; the muscle extracted by the electromyographic signal is rectus femoris and biceps femoris.

2. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1, characterized in that: the test bed base is composed of three 3mm colorless transparent acrylic plates, the three acrylic plates respectively represent a waist part, a thigh part and a shank part, the length is 110mm, 450mm and 350mm, and the width is 40 mm.

3. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1, characterized in that: the Hall angle sensor is a non-contact Hall magnetic angle sensor.

4. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1, characterized in that: the muscle electric signal sensor is a sensor directly outputting muscle electric pulse signals.

5. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1 or 4, characterized in that: the muscle electric signal sensor is provided with three electrodes which are respectively a middle electrode, a tail end electrode and a reference electrode and adopt 9V for power supply.

6. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1 or 4, characterized in that: the muscle electric signal sensor is directly connected with the microprocessor, amplifies, corrects and smoothes signals through the ADC, and outputs EMG pulse signals or muscle electric original signals.

7. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1, characterized in that: the singlechip is Arduino Uno singlechip.

8. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1, characterized in that: the inner diameter of the flange coupler is 6mm, and the outer diameter of the flange coupler is 10 mm.

9. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1, characterized in that: the Hall angle sensor is a KALAMOYI Hall angle sensor.

10. The lower limb gait information extraction device based on electromyographic signals and angle signals according to claim 1, characterized in that: the human bandage is 5cm wide magic subsides.

Images