CN102499692B - Ultrasonic gait detection method - Google Patents

Abstract

The invention discloses an ultrasonic gait detection device and method, which is characterized in that the ultrasonic detection system is installed in front of the walker robot platform, and the distance between the left and right legs of the subject and the ultrasonic detection platform is respectively detected by multi-channel ultrasonic sensors. distance, extract the gait information when the human body walks, analyze and calculate the gait parameters, including average step length, average pace speed, stride frequency, instantaneous speed and other parameters; the device includes an ultrasonic transmitting and receiving device, a data acquisition and transmission device, a step Gait data processing unit, gait feature parameter calculation and analysis unit. In the present invention, the detection device is installed on the walker robot platform, and no equipment is installed on the subject, so that the gait detection of the subject can be performed without any restrictions, reducing the mental burden of the test subject during gait detection , the extracted gait feature parameters are more accurate, the detection system is simple in structure, easy to use and install, and low in cost.

Description

An Ultrasonic Gait Detection Method

technical field

The present invention relates to a walking aid rehabilitation training device and method, in particular to a walking aid robot platform based on the installation of multi-channel ultrasonic sensors to detect the distance between the legs and the ultrasonic detection platform when a person walks, and through the detected distance data An ultrasonic gait detection device and method for processing and analyzing and extracting gait parameters when the human body walks, including average step length, average pace speed, stride frequency, etc. the

Background technique

At the beginning of November 2011, the world's total population has reached 7 billion. According to the latest census report released by China, the total population of the country is 134 million, and the population aged 60 and above is 177 million, accounting for about 13% of the total population. %. The proportion of the population aged 60 and above increased by 2.93 percentage points, and the proportion of the population aged 65 and above increased by 1.91 percentage points. As the phenomenon of population aging in China is gradually intensifying, there are a large number of patients with lower limb motor dysfunction among the elderly. In addition to early surgical treatment and necessary drug treatment, correct and scientific rehabilitation training is very important for recovery or rehabilitation of these patients. Improving lower extremity motor function plays an important role. Walking aid rehabilitation training robots can provide timely, scientific and effective lower limb rehabilitation training for patients with motor dysfunction in the lower limbs, and timely detection and analysis of the gait information of such patients is the theory of rehabilitation training for such patients Basis and prerequisites. the

The current mainstream gait feature extraction methods are based on computer vision and sensor-based methods. L. Lee et al. used matrix features based on each part of the image contour to analyze gait. Li-Shan Chou, Kenton et al. used 27 reflective sheets to be attached to the main joints of the subjects for image acquisition. J.P.Foster et al. proposed a model-based automatic tracking system to process and analyze image data by establishing a human motion model. These image-based processing methods will bring errors to the system due to the position of the camera and the movement of the sensor. Correct camera methods and calibration systems must be available, and operators must have professional skills. the

In the published world patent No. 5831937, an ultrasonic sensor is used to detect the gait characteristics of human walking. The ultrasonic transmitter is installed behind the waist of the subject, and the receiver is installed at a fixed position at the same height as the transmitter. Data extraction of human gait information. the

In the published Chinese patent application No. 200420059643.5, a strain-type three-dimensional force plate method is proposed to detect gait information. The three-dimensional force plate needs to be installed on a special walkway, which is cumbersome to install and high in cost. the

In the published Chinese patent application number 200910069062.7, a kind of gait measurement device is proposed by putting an ultrasonic sensor into the sole of the shoe to detect the distance signal. This detection method is very low in cost, but it can only detect the step length when the feet are on the ground. and frequency. the

In the published Chinese patent application No. 200910154024.1, it is proposed to install a two-axis acceleration sensor in front of the waist of the human body to measure the gait speed of the human body. This gait detection method is simple and low in cost, but the sensor is installed on the subject. On the body, the installation of the sensor position requires multiple adjustments, and the vibration of the sensor carried on the subject's body during the detection process will cause a lot of interference. the

Contents of the invention

The purpose of the present invention is to solve the above-mentioned problems in the prior art, and provide a multi-channel ultrasonic gait detection device and method. The device and method proposed by the present invention can detect gait characteristic data when the human body walks, process and analyze the data, and calculate gait characteristic parameters such as step length, average pace speed, and stride frequency. the

The technical scheme provided by the present invention is: this multi-channel ultrasonic gait detection method uses an ultrasonic sensor to detect the gait characteristics of human walking, and is characterized in that the ultrasonic detection device is installed in front of the walker robot platform, The tester does not install any detection equipment on the body, and the distance between the subject's left and right legs and the ultrasonic detection platform is detected by multiple ultrasonic sensors, and the gait information of the human body is extracted, and the gait parameters are analyzed and calculated. , including average step length, average pace speed, stride frequency, instantaneous speed and other parameters. the

The ultrasonic detection device set on the walker robot platform moves with the subject at the same time, and the multi-channel ultrasonic detection detects the relative distance data between the left and right legs of the subject and the ultrasonic detection platform during walking, and analyzes the subject through the detected distance data. The gait information of the subject, multiple independent ultrasonic waves and their transmitting and receiving devices, are transmitted to the subject's legs through ultrasonic waves and returned to the receiving end. the

When the multi-channel ultrasonic wave detects the relative distance data between the left and right legs of the subject and the ultrasonic detection platform during walking, the multi-channel ultrasonic wave is used for cyclic data detection. the

The setting of the detection area by the detection system includes:

(1) The platform of the ultrasonic detection system is perpendicular to the walking direction of the subject. the

(2) Increase the width of the detection area by increasing the number of ultrasonic sensors. the

(3) Set the maximum detection distance of the single-channel ultrasonic sensor through the software to avoid the interference of the walking robot and other obstacles on the data detection. the

(4) Change the angle between the ultrasonic sensor and the detection platform through structural design to reduce the interference generated during ultrasonic detection. the

The setting of the sampling time, by sampling within the set sampling period, the sampling time is shorter than the sampling period, which increases the sampling density and ensures that each sampling period is the same. the

The ultrasonic sensor is controlled by the single-chip microcomputer to collect data, and the serial communication is carried out with the computer through the single-chip microcomputer, and the collected data is transmitted to the computer. the

The data processing method includes removing noise in the data, smoothing and filtering the data, merging the collected data, and detecting the peak value of the data. the

Noise is removed by judging the difference between adjacent sampling data, judging the data difference of multi-channel data at the same sampling time and merging multiple data, and judging the peak value through the change of local data. the

The method for extracting the gait information after data processing includes judging the gait cycle through the peak value, determining the average step length, determining the average pace speed, and determining the stride frequency. the

Calculate the step length according to the maximum difference between the detected data of the left leg and the right leg after processing, calculate the step length through the relationship between the detected data and the step length, determine the step length and gait cycle time through peak detection, and calculate the average step length , average pace and cadence. the

This multi-channel ultrasonic gait detection device provided by the present invention is characterized in that it includes: an ultrasonic gait detection device based on a walker robot platform, multi-channel independent ultrasonic waves and its transmitting and receiving device, single-chip data acquisition and transmission The device is a gait data processing unit and a gait characteristic parameter calculation and analysis unit installed in the computer. the

In order to better realize the purpose of the present invention, the ultrasonic wave and its transmitting and receiving device adopt an ultrasonic ranging module, which integrates an ultrasonic signal trigger, an ultrasonic transmitting and receiving circuit, and controls the ultrasonic transmitting signal through the trigger signal, and then passes the pressure The electric effect transducer converts the received ultrasonic signal into DC5V voltage, and detects the distance and position of obstacles by detecting the return voltage time. the

(1) Main technical parameters

Practical voltage: DC5V. Quiescent current: 2mA. Level output: high 5V, low 0V. Induction angle: no more than 15 degrees. Detection distance: 2cm-450cm. Accuracy: up to 1mm

(2) Wiring method:

VCC, trig (control terminal), echo (receiving terminal), GND

(3) How to use:

A control port sends a 10us high-level signal, the signal trigger of the module emits a 40k Hz square wave, waits for a high-level output at the receiving end to detect whether there is a signal return, and starts a timer to count when there is an output. Read the value of the timer when the terminal becomes low level, this time is the time of distance measurement, detection distance=(high level time*sound speed (340m/s))/2. the

The design of the structure of the four-way ultrasonic acquisition system: the ultrasonic position and distance data are designed according to the physical distance of the omni-directional rehabilitation walker robot, and the optimal position is designed after repeated testing experiments, which can make the maximum The data detection interference between the two legs and the interference caused by the car body to the detection are excluded to a minimum. 1, 2-channel ultrasonic detection data when the left leg is walking, 3, 4-channel ultrasonic detection data when the right leg is walking. the

For better realizing the purpose of the present invention, described single-chip microcomputer data acquisition and transmission device

Using PIC16F877A single-chip microcomputer, the maximum push-pull current capability of each I/O port is 20mA, which is enough to meet the quiescent current requirement of each ultrasonic wave of 2mA. Use the four I/O ports of the microcontroller as trigger signals, and use the four I/O ports to receive return signals. Eliminate the interference between ultrasonic waves by circularly detecting four-way ultrasonic data, use timer 0 to set the sampling time of single-channel ultrasonic waves, use timer 1 to obtain ultrasonic detection time, and perform ultrasonic detection within the specified sampling time, so the setting of sampling time It should be longer than the ultrasonic detection time, and the sampling is carried out within the sampling period, which is different from the previous sampling, which greatly reduces the sampling time and obtains more data per unit time. the

Ultrasonic detection distance is limited. The detection range of the ultrasonic transmitting and receiving device is 2cm-450cm, and the maximum distance that this detection system needs to detect is 70cm. After calculation, by detecting the value of the TMR1H register of the timer, judge whether the value of TMR1H exceeds If the detected value of 70cm exceeds the end of the test, the next ultrasonic test will be carried out. the

During the single-channel ultrasonic detection process, a 20-microsecond high-level trigger signal is given to the ultrasonic control terminal trig through the I/O pin of the single-chip microcomputer, and the timer 1 is turned off after 20 microseconds with timer 1, and the ultrasonic receiving terminal Intervene in the I/O pin of the single-chip microcomputer, wait for the receiving end to return a high-level signal, and use timer 1 to calculate the duration of returning the high-level signal. the

Detection data compression, timer 1 is a 16-bit timer, without affecting the analysis of gait data, compressing 16-bit data to 8-bit data can reduce the detection time and reduce the difficulty of data processing, and pass the maximum detection distance of 70cm , the maximum number of digits that timer 1 needs to store is 11 digits, the last three digits are omitted, and the data is compressed into 8 digits. At the same time, the accuracy has changed to a distance of 8 microseconds, which is 1.36 mm. This accuracy can meet the requirements of gait data detection and analysis. The detected data is transmitted to the computer through the serial port, and then the sampled data is processed. the

In order to better realize the purpose of the present invention, the gait data processing and analysis unit installed in the computer is based on the data detected by the four-way ultrasonic wave, the data is merged, denoised, filtered, peak detection, period division and so on, the merged two-way data are the distance between the left leg and right leg and the detection platform, the maximum distance between the legs in each gait cycle is determined by the peak value, and the actual step is calculated after the scale transformation After calculating the average value of all step lengths, the average step length can be calculated. According to the sampling time extraction and peak detection, the average pace speed and stride frequency can be calculated. the

By differentiating the processed distance data and time, the instantaneous velocity value of each sampling point can be calculated. the

It is also possible to analyze the gait symmetry of the subject at a later stage by analyzing the different positions, velocities, and cycle phases of the detected left and right leg data in the same cycle. the

The accuracy of the ultrasonic gait detection device is judged by comparing and analyzing the calculated gait parameters with the actual gait parameters. the

Compared with prior art, the beneficial effect of the present invention is:

(1) An ultrasonic gait detection system is built based on the walking aid robot platform, and no equipment is installed on the subject, and the gait data detection of the subject can be performed without any restrictions. This greatly improves the psychological quality of the subjects during the testing process, increases confidence in the rehabilitation of patients with lower limb motor dysfunction, and can frequently and efficiently perform gait testing on different subjects. the

(2) Install multi-channel ultrasonic sensors in front of the omnidirectional walker robot, and define the detection range in a fixed detection area where the subject walks. Eliminate the echo interference between ultrasonic waves through cyclic detection, and then rationally optimize the mechanical structure of the detection device to reduce the interference between the legs of the subject during data sampling when walking. the

(3) The method of setting the sampling period is different from the previous sampling method. Sampling is performed within the set sampling period, and the next sampling is performed after the sampling period is over, which increases the density of sampling data. the

(4) The detected data is the distance data between the legs and the detection platform when the human body is walking. Through the data, the state at each moment of walking can be determined, and the instantaneous speed at each moment can also be calculated. According to the corresponding processing and calculation of the detected data, the characteristic parameters of the gait can be easily extracted, including the extraction of the average step length, average pace, stride frequency and instantaneous speed, and the symmetry and stability of the gait in the later period can also be calculated. gender analysis. the

(5) Compared with other methods, the extraction of gait parameters by this method is simple and easy to understand, the cost is low, the use and installation are convenient, and the data processing speed is fast. However, the biggest shortcoming of this method lies in the various interferences generated during ultrasonic testing, which can be greatly reduced by optimizing the detection algorithm and designing the mechanical structure of the detection device. the

Description of drawings

Figure 1 is a schematic diagram of an ultrasonic gait detection system based on a walker robot, where 1 is the walker robot, 2 is the ultrasonic detection system, and 3 is the subject. the

Figure 2 is a block diagram of the principle of ultrasonic detection. the

Figure 3 is a structural design diagram of the ultrasonic gait detection system, in which 4, 5, 6, and 7 are four ultrasonic sensors. the

Figure 4 is a schematic diagram of the definition of basic gait parameters, where 8 is the step length, 9 is the stride length, 10 is the gait cycle, 11 is the inner step width, and 12 is the outer step width. the

Fig. 5 is a set of gait data curves after data processing, wherein A is the detected gait data curve of the right leg, and B is the detected gait data curve of the left leg. the

Fig. 6 is a schematic diagram of calculating parameters by step length, wherein 13 is an ultrasonic sensor. the

Detailed ways

The technical solutions of the present invention will be described in further detail below in conjunction with the accompanying drawings and examples. the

One step detection device

As shown in Figure 1, the ultrasonic detection system is installed in front of the walker robot platform to detect the gait data at the same height as the ultrasonic wave when the person walks, and convert the detected data to the corresponding ratio to calculate the step length value. the

The detection principle of the ultrasonic receiving and transmitting module is shown in Figure 2. By triggering a 20 microsecond high-level signal on the ultrasonic control terminal, the module modulates the signal to generate a 40 kHz oscillating pulse signal and emits ultrasonic waves. When an obstacle is encountered, the ultrasonic signal returns , after the signal is amplified, it is sent to the return end timer for timing, and then sent to the control end. the

The structural design of the ultrasonic testing system is shown in Figure 3, where the units are centimeters. The maximum sensing angle of each ultrasonic wave is 15 degrees, and the maximum detection distance is 70cm. The shaded part is the ultrasonic detection area, and the black frame is the inner boundary of the walker robot. In the figure 1, 2 two-way ultrasonic detection data when the left leg is walking, 3, 4 two-way ultrasonic detection data when the right leg is walking. The distance between 1-way and 2-way, 3-way and 4-way ultrasound is 9cm. The inner step width of normal people is 5cm-10cm, and the outer step width is 25cm-30cm. The definition of basic gait motion parameters is shown in Figure 4. In order to reduce the interference of ultrasonic detection when two legs are walking, and through experimental verification, Set the time distance of sensors 2 and 3 to 17cm. In order to remove the interference between the ultrasonic waves when the left and right legs are walking, the 2nd and 3rd ultrasonic waves are at an angle of 7.5 degrees to the detection platform, and the 1st and 4th ultrasonic waves are placed parallel to the detection platform. the

Connect the ultrasonic sensor with the microcontroller, four I/O ports provide trigger signals, and the other four I/O ports receive return signals. Use the USB port of the laptop to provide power for the single-chip microcomputer, and connect the single-chip microcomputer with a serial port to USB device and a serial port line, so that the single-chip microcomputer and the computer can perform asynchronous serial communication. the

Two data processing

Calculate the average difference of the adjacent sampling point data of each channel of ultrasonic waves. If one of the data is more than 3 times the average difference, it is considered that this data is a jump point. If the derivatives of the 10 data points before and after these jump points are equal to If the value is positive or negative, these jump points are replaced by the mean value of the 10 data points before and after these jump points. The average value of the data points of the number is replaced, which avoids the error in the calculation of gait parameters. The same principle is used for peak detection. If the derivatives of 10 data points before and after a certain data point have different signs, the data point is considered as the peak point. The data of channels 1, 2 and channels 3 and 4 are combined into one channel of ultrasound respectively. The data of channels 1 and 2 are used to detect the data of the left leg. The difference between the two channels of data is very small. If the value is greater than 3 times of the average difference, the data value with smoother data value is taken, that is, the data with the smaller difference between adjacent data, if the difference between the two data is small, the larger of the two ultrasonic detections is taken In this way, the abnormal data during detection is excluded to the greatest extent, and the two channels of ultrasound are combined without affecting the gait analysis, and the 3 and 4 channels of ultrasound are also combined according to the same principle. Afterwards, each data is subjected to five-point secondary smoothing filtering, which is defined as:

${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 3</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 12</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; 17</span>}\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 12</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 3</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 35</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Among them, x _i is the i-th data value, and y _i is the data value of x _i after smoothing and filtering.

Calculation of three gait characteristic parameters

After denoising and filtering the detected gait data, the data characteristics of the 1, 2, 3, and 4 channels are synthesized into the left and right leg gait data curves, and the data is processed by the smoothing filter method and then the peak value is detected. Calculate the peak and valley data and time. Figure 5 is a schematic diagram of a set of data curves after data processing, in which the solid line and the dotted line represent the relationship between the distance and time between the right leg and left leg and the ultrasonic testing platform, and the difference between the two data curves is 180 degrees phase and changes periodically. the

Figure 6 is a schematic diagram of the relationship between some calculation parameters and the step length when extracting gait information through detection data, where H ₁ and H ₂ are the distances between the subject's hip joint and the ultrasonic sensor and the ground, respectively. D ₁ and D ₂ are respectively the distance data between the left and right legs and the sensor detected by the ultrasonic sensor. L _V is the step length value to be sought, and L ₁ is set as the subject's leg length, then the above parameters have the following two relationships,

$\frac{{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

${{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="1"\; label="h"\; filenames="HDA0000114512760000022.png,HDA0000114512760000031.png"\; state="\{\{state\}\}">h</figure-callout></span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; V</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>{{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="1"\; label="L"\; filenames="HDA0000114512760000022.png,HDA0000114512760000031.png"\; state="\{\{state\}\}">L</figure-callout></span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

The value of the step length L _V can be obtained through the above two relational expressions. In the same way, all the step length values can be obtained, and then the average step length can be obtained. Let S be the total distance from the first step to the nth step, then

$\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

Wherein L _i (i=1,..., n) is the step length value of the i-th gait cycle, and T is the total time of the detection process, then the values of the average step length L, the average pace V and the step frequency F can be obtained by the following formulas, respectively:

The average step length, pace, and stride frequency are:

L=S/n (5)

V＝S/T (6)

F＝60/(T/n)            (7) 

Four experiments and data analysis

The gait detection experiment was carried out on 10 healthy people respectively, and the average step length, average pace speed and stride frequency value of each group of data were calculated according to the calculation principle of gait parameters. Then compare with the actual gait parameter value to calculate the relative error value. The calculation results are shown in Table 1. The data sources of the actual step length, pace speed and step frequency are: actual step length L _real : the quotient of the actual distance traveled by the detected person and the number of actual step length cycles. Actual pace V _real : the speed of the lower limb rehabilitation robot in all directions. Actual stride frequency F _real : the number of step cycles in one minute. Use the quotient of the time recorded during detection and the number of steps to find the actual step cycle, and then calculate the number of step cycles in one minute. Among them, E _L , E _V and E _F are the relative errors between the measured and calculated gait parameter values and the actual gait parameter values, respectively. It can be seen from Table 1 that the relative error E _L of the step length does not exceed 4%, the relative error E _V of the pace does not exceed 3%, and the relative error E _F of the step frequency does not exceed 2%. The system can accurately detect the gait parameters of the subject.

Table 1 shows the data comparison between the extracted gait parameters and the actual parameters. the

Claims (1)

1. a ultrasonic gait detection method, adopt the gait feature of ultrasonic sensor human body walking, it is characterized in that ultrasonic wave detecting system to be arranged on assistant robot platform the place ahead, on experimenter's health, do not install any checkout equipment additional, distance while detecting respectively the lower limb walking of experimenter left and right by multiplex ultrasonic sensor and between ultrasonic wave detecting system, gait information while extracting human body walking, analytical calculation gait parameter, comprise average step length, average leg speed, cadence, instantaneous velocity parameter, the ultrasonic wave detecting system and the experimenter that are arranged on assistant robot platform move simultaneously, multiplex ultrasonic detects experimenter's relative distance data between left and right lower limb and ultrasonic wave detecting system in the process of walking, by the range data detecting, analyze experimenter's gait information, multichannel independently ultrasound wave and its sending and receiving apparatus emits ultrasonic acoustic waves into experimenter's shank by transmitting terminal and turns back to the receiving terminal of sending and receiving apparatus, it is to carry out loop-around data detection by multiplex ultrasonic during the relative distance data between left and right lower limb and ultrasonic wave detecting system in the process of walking that multiplex ultrasonic detects experimenter, the setting of described ultrasonic gait detection method to surveyed area scope, comprise:

(1) ultrasonic wave detecting system is vertical with experimenter's direction of travel;

(2) by increasing ultrasonic sensor quantity, increase the width of surveyed area;

(3) the maximum detection distance of each road ultrasonic sensor is set by software, avoids assistant robot and other barriers that Data Detection is produced and disturbed;

(4) by structural design, change the angle between ultrasonic sensor and described ultrasonic wave detecting system, the interference producing while reducing ultrasound examination.

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