阅读说明：本技术 一种基于肌电信号和角度信号的下肢步态信息提取设备 (Lower limb gait information extraction equipment based on electromyographic signals and angle signals ) 是由 程光 陈天麟 戴佺民 马勇杰 孙佰鑫 刘伟锋 许晓容 于 2020-05-07 设计创作，主要内容包括：本发明涉及一种基于肌电信号和角度信号的下肢步态信息提取设备,包括试验台基座、霍尔角度传感器、法兰联轴器、9V电池、单片机、上位机和人体固定绑带,上位机为计算机串口调试助手,能够快速读取串口数据,该下肢步态信息提取设备还包括肌肉电信号传感器,肌肉电信号为人体将执行动作信号传递给肌肉后,肌肉会产生动作电位,动作电位沿着肌肉纤维方法运动,在皮肤表面形成的微弱的电流；肌电信号提取肌肉为股直肌与股二头肌。下肢步态信息获取系统通过测量人体股直肌肌电信号,股二头肌肌电信号,髋关节角度信号,膝关节角度信号四种信号来获取人体步态信息,通过肌电信号与物理信号结合的方法,提高人体步态识别的准确性,抗干扰性和时效性。(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.)

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.

Technical Field

The invention relates to the technical field of gait detection and health monitoring, in particular to lower limb gait information extraction equipment based on electromyographic signals and angle signals.

Background

The human gait information has very wide application prospect, can provide research foundation for a plurality of research fields, and is a behavior characteristic combining biology and kinematics. With the rapid development of the manufacturing industry, the computer industry and the rehabilitation medical industry, gait is applied to more and more fields as the most common behavior characteristics of human bodies.

For example, in the rehabilitation medical industry, by acquiring human gait, doctors can be helped to better observe the lower limb conditions of patients, a targeted treatment scheme is provided, and the rehabilitation treatment effect of the patients is checked; in the field of robotics, lower limb gait plays a vital role for exoskeleton robots as well as lower limb prostheses. The system can help the control system to clearly distinguish the movement intention of the human body, and help the system to effectively analyze and adopt a correct control strategy; in the fields of electronic games and VR, gait acquisition can add abundant game experience to games and increase the extensibility of game development. At present, there are many ways to acquire gait information, and the main signal sources include human body muscle electrical signals, joint angle signals, acceleration signals, plantar pressure signals and images. The electromyographic signal is a biological signal, and when a human body needs to perform actions, the brain sends out commands in the form of electric pulses and transmits the commands to muscles through neurons and spinal cords. After the signal is transmitted to the muscle, the muscle can generate action potential, the action potential moves along the muscle fiber method, weak current is formed on the surface of the skin, and muscle electric signal is generated. The electromyographic signals can quickly reflect the movement trend of the human body, but have the defects of poor anti-interference performance and easy influence by the outside. The electromyographic signals are mostly acquired by surface electrode pastes. Physical signals are acquired by various sensors, so that the anti-interference capability is strong, but the defects of low response speed and untimely feedback exist. The image signal excessively depends on external equipment, image processing needs to be carried out on the acquired image, and the characteristic of inaccurate identification is difficult to avoid.

For example, chinese patent publication No. CN110731784A discloses a platform-based gait measurement system, in which a subject is not moving on a mobile platform, a gait data analyzing and storing device electrically connected to an output terminal of an image capturing device, and visual markers fixed to the left and right feet of the subject to identify and position the left and right feet are used. After the camera acquisition module shoots the left foot and the right foot of the tested person, gait analysis is carried out on the acquired image. When the method is used, a certain platform foundation is needed, and only certain limitation exists for the identification of the feet, so that the method is easily interfered by the surrounding environment in the image processing process.

For another example, chinese patent publication No. CN108992071A discloses a lower limb skeleton gait analysis system, which uses a method of combining an inertial measurement unit, an angle encoder, and a plantar pressure distribution sensor multi-sensor module to collect human lower limb movement data and perform human gait analysis. The three signal sources used by the invention are all physical signals, and the defect of the invention is that the time delay is difficult to control when the movement gait is reflected.

For another example, chinese patent publication No. CN110327054A discloses a gait analysis method and device based on acceleration and angular velocity sensors, in which the acceleration and angular velocity sensors are placed on shoes, and the ground contact and lift-off ratio is calculated from the time of foot contact and the time of foot lift-off, so as to acquire the state of foot movement of a human body. The device only collects foot signals, so the device has certain limitation in use.

Disclosure of Invention

In order to solve the problem of high use cost in the prior art, the invention provides lower limb gait information extraction equipment based on electromyographic signals and angle signals.

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

A lower limb gait information extraction device based on electromyographic signals and angle signals comprises a test bed base, a Hall angle sensor, a flange coupler, 4 sections of 9V batteries, a rduino Uno 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.

The lower limb gait information extraction equipment based on the electromyographic signals and the angle signals has the characteristics of being wearable, portable and convenient to move, is fixed on the side surface of the lower limb of a human body through the magic tape and the fixing holes in the acrylic experiment base, and the binding bands are respectively positioned at the waist, the lower leg and the ankle joint. When the test bed is worn, the hip joints and the knee joints of the lower limbs can move freely without obstruction.

In any of the above embodiments, the test bed base is preferably 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.

In any of the above schemes, preferably, the hall angle sensor is a non-contact hall magnetic angle sensor, can rotate at 360 degrees without dead angle, adopts a japanese NSK bearing, has resolution up to 4096 bits, has a working voltage of 5V, outputs a voltage of 0-5V, and has small volume, small damping and simple installation.

In any of the above embodiments, preferably, the muscle electrical signal sensor is a sensor that directly outputs a muscle electrical pulse signal. The muscle electric signal sensor is small in size, high in transmission speed and capable of directly outputting muscle electric pulse signals, and the muscle electric sensor is designed to be wearable.

In any of the above embodiments, preferably, the muscle electrical signal sensor is provided with three electrodes, namely a middle electrode, a terminal electrode and a reference electrode, and is powered by 9V.

In any of the above schemes, preferably, the muscle electrical signal sensor is directly connected to the microprocessor, and the correction and smoothing signal is amplified by the ADC to output an EMG pulse signal or a muscle electrical raw signal.

In any of the above schemes, preferably, the single chip microcomputer is an Arduino Uno single chip microcomputer.

In any of the above aspects, preferably, the flange coupling has an inner diameter of 6mm and an outer diameter of 10 mm.

In any of the above aspects, preferably, the hall angle sensor is a KALAMOYI hall angle sensor.

In any of the above schemes, preferably, the human body bandage is a magic tape with a width of 5 cm.

Drawings

Fig. 1 is a schematic structural diagram of a preferred embodiment of a lower limb gait information extraction device based on an electromyographic signal and an angle signal according to the invention.

Fig. 2 is an enlarged view of a portion a of the preferred embodiment of the lower limb gait information extraction apparatus based on the electromyographic signals and the angle signals according to the invention shown in fig. 1.

Fig. 3 is an enlarged view of a portion B of the preferred embodiment of the lower limb gait information extraction apparatus based on the electromyographic signals and the angle signals according to the invention shown in fig. 1.

Fig. 4 is a schematic structural diagram of a flange coupling of the lower limb gait information extraction device based on electromyographic signals and angle signals, which is matched with the preferred embodiment shown in fig. 1, according to the invention.

Fig. 5 is a schematic hardware wiring diagram constructed in the preferred embodiment of the lower limb gait information extraction device based on electromyographic signals and angle signals shown in fig. 1 according to the present invention.

Detailed Description

The following describes a further embodiment of the lower limb gait information extraction device based on electromyographic signals and angle signals according to the present invention with reference to the drawings of the specification.

As shown in fig. 1, a schematic structural diagram of a preferred embodiment of a lower limb gait information extraction device based on electromyographic signals and angle signals according to the invention is shown.

A lower limb gait information extraction device based on electromyographic signals and angle signals comprises a test bed base, a Hall angle sensor, a flange coupler, 4 sections of 9V batteries, a rduino Uno 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.

The lower limb gait information extraction equipment based on the electromyographic signals and the angle signals has the characteristics of being wearable, portable and convenient to move, is fixed on the side surface of the lower limb of a human body through the magic tape and the fixing holes in the acrylic experiment base, and the binding bands are respectively positioned at the waist, the lower leg and the ankle joint. When the test bed is worn, the hip joints and the knee joints of the lower limbs can move freely without obstruction.

In this embodiment, the base of the test bed is composed of three 3mm colorless transparent acrylic plates, which represent the waist, thigh and shank, respectively, and have a length of 110mm, 450mm and 350mm and a width of 40 mm. The joints between the acrylic plates are connected with the Hall angle sensor through the flange couplings, and the Hall angle sensor can freely rotate along with joints of a human body. The three acrylic plates respectively represent a waist part 1, a thigh part 2 and a shank part 3.

In the working process, a flange coupler is fixed on fixing holes (shown in figures 2 and 3) of joint parts of a waist part 1 and a thigh part 2 shown in figure 1 by using 3mm screws; and then fixing the Hall angle sensor on fixing holes (shown in figures 2 and 3) at joints of a thigh part 2 and a shank part 3 of the acrylic plate shown in figures 1-3 by using 5mm screws and nuts, and finally fixing the Hall angle sensor bearing and a middle hole of the flange coupling shown in figure 4 by using 3mm screws, thereby realizing joint movement of the acrylic plate.

In this embodiment, the hall angle sensor is a non-contact hall magnetic angle sensor, can rotate at 360 degrees without dead angles, adopts a japanese NSK bearing, has resolution up to 4096 bits, has a working voltage of 5V, outputs a voltage of 0-5V, and has a small volume, small damping and simple installation.

In this embodiment, the muscle electrical signal sensor is a sensor that directly outputs a muscle electrical pulse signal. The muscle electric signal sensor is small in size, high in transmission speed and capable of directly outputting muscle electric pulse signals, and the muscle electric sensor is designed to be wearable.

In this embodiment, the muscle electrical signal sensor is provided with three electrodes, which are a middle electrode, a terminal electrode and a reference electrode, respectively, and adopts 9V power supply, so that the middle electrode and the terminal electrode of two muscle electrical signals are respectively attached to the central positions of rectus femoris muscles and biceps femoris muscles, and the reference electrode is attached to a position with less muscle activity.

In this embodiment, with Arduino Uno, muscle electric signal sensor, the 9V battery uses the magic subsides to be fixed in inferior gram force board 2 on, convenient dismantlement.

In this embodiment, the muscle electrical signal sensor is directly connected to the microprocessor, and the correction and smoothing signal is amplified by the ADC to output an EMG pulse signal or a muscle electrical raw signal.

In this embodiment, the singlechip is the Arduino Uno singlechip.

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

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

In this embodiment, the human bandage is 5cm wide magic subsides. During operation, the wearing mode of the lower limb signal acquisition test bed is adopted, and the magic tape bandage is used for fixing the test bed at the waist, the position of the crus and the position of the ankle joint of a human body respectively.

Finally, referring to fig. 5, a hardware wiring diagram of the lower limb gait information extraction device based on electromyographic signals and angle signals according to the present invention is shown, which is constructed according to the preferred embodiment shown in fig. 1.

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

The collection process is that Arduino Uno connects the host computer, opens 9 battery power, and Arduino Uno and sensor begin work, open host computer serial ports debugging assistant, and the host computer begins to read serial ports data, and the human body begins to move.

After a human body wears the experiment table, the surface electrode of the myoelectric sensor is attached to the centers of the rectus femoris muscle and the biceps femoris muscle, each joint is moved, and the tightness of the binding band is adjusted to a comfortable degree. The method comprises the following steps that an Arduino Uno is connected with an upper computer, a 9V battery power supply is turned on, the system starts to supply power, data starts to be transmitted, a program compiling serial port prints rectus femoris electromyographic signals, biceps femoris electromyographic signals, hip joint angle signals and knee joint angle signals in a dictionary format, and voltage values are converted into angle values by utilizing the characteristics of a Hall angle sensor before printing. The outputs sEMG1, sEMG2, Angle1, Angle2 are a set of data.

It will be understood by those skilled in the art that the lower limb gait information extraction device based on electromyographic signals and angle signals of the invention includes any combination of the parts in the present specification. These combinations are not described in detail herein for the sake of brevity and clarity, but the scope of the invention, which is defined by any combination of the parts constructed in this specification, will become apparent after review of this specification.