[IEEE 2013 3rd International Conference on Instrumentation, Communications, Information Technology,...

Design of Shoe-Integrated Running Gait Analysis Device For Normal People Case Study

Megantara Pura, Barman Tambunan, Aulia Arif IskandarSwiss German University

Biomedical Engineering Department, Faculty of Life SciencesEdu Town BSD City, Tangerang 15339, Indonesia, +6221 30450045

e-mail: [email protected], [email protected], [email protected]

Abstract— Running is one of the recommended activities to maintain health. An improper technique may result in inefficient energy usage or injury. This research aims to design a mobile device that can analyze and process the parameter that is obtained from the running activity. The device uses accelerometer to measure running parameter. The subjects for this research are 20-22 years old people with non-athlete background, varies on gender, weight, and how often they do sport activity. Subject runs 10m with the device attached to their foot. Subjects that doing sport activity often use front-foot strike as their running style. Subjects that doing sport activity seldomly use rear-foot strike. Front-foot strike reduces acceleration to the ground, therefore minimizing the risk of injury. To reduce the risk of injury, acceleration to the ground must be lower than 55 m/s2, and the force to the ground must not exceed 5 times the body weight.

Keywords— Running gait, mobile device, acceleration, front-foot strike, rear-foot strike.

I. INTRODUCTION

Running is one of the recommended activities to maintain health. However, there are certain techniques used when running, such as frequency and deepness of breaths and stride distance. An improper technique may result in inefficient energy usage or injury. Different types of shoes also affect the running gait of the user.

There are two methods to carry out gait analysis. The first method is a qualitative analysis, which is inexpensive, but the results depend on the capability of the clinician. The second method is a quantitative analysis, which is expensive and only carried out in a motion laboratory. Available device to analyzerunning technique usually depends on the camera, which is used only in one place only [1]. This research aims to design a mobile device that can analyze and process the parameter that is obtained from the running activity, thus displaying the result to improve running technique.

In running gait cycle, one complete stride consist of initial contact, mid stance, toe off, mid swing, until second initial contact. There are two periods of float when neither foot is in contact with the ground, happens after toe off and before second initial contact. This results in decreased time in stance phase and increased time in swing phase. As velocity continues to increase, further reduction in stance phase occurs,

whereas swing phase duration increases. Unlike walking, the forward momentum that is needed for running is produced by the swinging leg and arms, rather than the stance leg [2].

Fig 1. Running gait cycle

Forefoot or front-foot strike means landing on toe first during foot strike, while rearfoot strike means landing on heel first. Front-foot striking resulting in lower ankle stiffness and increased knee stiffness compared to rearfoot striking. It is said that lower ankle stiffness and increased knee stiffness results in increased running speed [3]. It is also said that switching to front-foot strike might avoid shock related injuries such as stress fractures.

Fig 2. Left: Rear-foot strike. Right: Front-foot strike

Typically, during submaximal running (running without making much velocity), part of the foot that will contact first to the ground during foot strike is heel. On the other hand, during speed running part of the foot that will contact first is midfoot or toe. A person that is doing sport activity daily will

2013 3rd International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME)

324

Bandung, November 7-8, 2013

��

use forefoot strike when running; while a person that is doing sport activity seldom will use rearfoot strike when running [3]

II. METHODOLOGY

The order of the research follows the structured method of human movement analysis [4]. This research is divided into four stages with modification: preparation stage, observatory stage, data analysis stage, and conclusion phase.

In this research, subject is selected first. There are various types of subjects, with the variety based on age, gender, height, weight, occupation, and how often the subject does sport activity. In this research the variety narrows to subjects of age 20-22 years with non-athlete background. These selected subjects vary on gender, height, weight, and how often they do sport activity. In the end, 6 subjects are selected for this research.

Fig 3. Flowchart of data recording procedure

One of the factors that determine the risk of injury in running is the running style that is used by the runner. To analyze this, semi-quantitative analysis method is used to determine the running style that is used by the subjects, whether the subject use rearfoot strike or forefoot strike. This research assumes that subject that is often or used to do sport activity will resort to use forefoot strike. Different attribute of each subject is also analyzed whether it is correlated to their running style.

Accelerometer is preferred as the wearable sensor that can measure acceleration. The block diagram of the overall device is on this figure. Running involves a specific gait pattern,

which will be seen from ankle acceleration. The acceleration will be recorded using remote monitoring instrument, then the data will be sent over wireless connection to the PC. The software inside the PC will display and store the result for further analysis.

Accelerometer is used to record foot movement. Each recorded data from its respective axis are passed through a low-pass butterworth filter. This filter is used to reject vibration noise. After filtering, those data are going to analog inputs of the microcontroller, which will be sent using wireless interface to the computer.

Fig 4. Block diagram of remote monitoring instrument.

The microcontroller has a built-in analog-to-digital converter, therefore separate A/D Converter is not needed. The microcontroller is an electrical component that is designed to control other electrical devices. It has three main works which are input scanning or getting the input from sensors, input processing using the embedded program and set the output. It has ROM, RAM, and I/O facilities [5]. The signal from each input will be stacked, including a constant for data control, as a series of data.

Fig 5. Block diagram of the data receiver.

The computer will receive data from the wireless receiver. The software embedded will do further processing to display the data to the display monitor and interpret the data to convert it into the information for the user. The warning light is also added as the warning to the user whether the user needs to change their running technique to avoid injury.

Since data that is sent from wireless kit is in the form of series, it needs to be demultiplexed to their respective axes. Shift register will be used to convert series of signal to parallel signal. The first three channels will go to the equation formula. This formula is obtained from accelerometer calibration. Afterward, the result will be displayed with graph. The last channel, as the control, will be feed to the loop control switch. In case the series of data is scrambled because of the lag, the last channel will break the loop iteration, stopping the program


325


from running. Subject’s mass will be added as the input for calculating force.

To test the device, subjects will be asked to wear this device. The subject will be asked to fill their weight, height, shoe number, and how often they do sport activity. Data recording session is held on the place seen in this figure, also with start point mark and end point mark.

Fig 6. Process of data recording.

Subject’s run will be evaluated based on the running style that is used, front-foot strike or rear-foot strike. The subjects that use rear-foot strike is asked to run the second session. In this session subject is asked to use front-foot strike for his/her running style and both data are stored. Some of the subjects is also run under specific conditions, such as increased running speed or run barefoot. Depends on the result, the subject may not need to do second session of data recording.

The data that is stored in the computer after recording are opened using Microsoft Excel. From this the graph of the data can be obtained with much more detail, and several other variables can be obtained. These data can be compared each other and the conclusion of this research can be obtained. These data also can be used to see the limitation of the device.

III. RESULT AND ANALYSIS

The MMA7361 accelerometer has come with output connection and sensitivity switch, therefore the modifications that are needed are extending the cable. A Low-pass butterworth filter is made using LM324N amplifier, pair of 100k resistors, and two capacitors with value of 1nF and 2.2nF.The package of accelerometer board are equipped with low-pass filter already, however since the cable are extended, noise might intervene the signal. Therefore the filter is added to prevent such noise without losing any information from the accelerometer.

The output of each filter are feeded to the analog input of Arduino Uno board. However, since Xbee wireless transmitter shield is attached to the microcontroller board, the output is connected over the shield. Also, two voltage sources from arduino board, 3.3 and 5V, are used to supply the accelerometer and filter respectively.

Fig 7. Circuit diagram of remote monitoring instrument.

Fig 8. Remote monitoring instrument placed on the subject.

Software used for this research is constructed using LabVIEW. The software consist of setting the connection port, data demultiplexer which is using shift register, conversion to acceleration unit, and graph to display the result. Warning light is also added. Accelerometer is calibrated using earth gravity as the reference.

Fig 9. User interface of the software in LabVIEW.

The accelerometer reacts to the change of velocity, therefore sudden changes of velocity (such as hitting the ground) will create a peak. In gait cycle, each time the foot reaches the ground, an acceleration peak will be happened. This peak will be used to calculate total acceleration that is received on the ankle during foot strike.

The distance of each peak indicates the period of one gait cycle. X-axis peak indicates frontal acceleration/deceleration, Y-axis peak indicates transversal acceleration, and Z-axis indicates sagital acceleration that is happened on the ankle.

Force estimation is done using Newton’s second law, where:

F = m.a

Where F is the force, m is the subject’s mass and a is the acceleration. However, in terms of Y-axis, the gravitation needs to be added, which results to:

F = m(a + g)

Where g is the gravitation. On Y-axis, the accelerometer has read the gravitation, therefore the acceleration read on Y-axis has been added with gravitation. During foot strike, the lower limbs need to withstand the whole body mass, resulting to force on X-axis and Z-axis become less significant [6].


326


It also need to be noted that the force that can be calculated is when there is a change of velocity, means there are acceleration. Force that is happened because of the compression or pressure cannot be calculated by using accelerometer only.

Subject 5’s data are used as the example of subject that is seldom doing sport activity. On first session, Subject 5 uses rear-foot strike. The result comes as follows.

Fig 10. Result of subject 5 run, first session.

Since the subject is using heel strike, the accelerationexceeds 50 m/s2. This number comes from taking the averageof the peak on the Y axis. The average vertical acceleration and force calculation are:

Average vertical acceleration:

Average vertical force:

The next session subject is asked to use front-foot strike as his running style. Subject is also taught how to run using front-foot strike. The result is shown in the figure.

Fig 11. Result of Subject 5 run, second session.

The large peak occurs because the subject’s foot hitting the floor hard when the subject reaches end line. However, during the running the graph is much lower compared to the first run.

Each peak is under 50 m/s2. This session further proves that front-foot strike as the proper running style reduces the ankle acceleration to the ground. The average verticalacceleration and force calculation are:



The next result comes from the subject that does sport activity frequently. Since the subject uses front-foot strike, the warning light is not active during the entire session.

Fig 12. Result of subject 4 run.

This result shows a proper running gait by using front-foot strike. The average vertical acceleration and force calculation are:


327




From data of each subjects, vertical acceleration are affected by running technique used and the footwear, and not affected by subject’s mass and running speed. The table below shows the summary of the subjects data.

TABLE 1SUMMARY OF SUBJECTS DATA

Subject Avg. vertical a(m/s2)

Avg. vertical F(N)

Condition

1 48.3 2994.6

2 62.53 42.47 2688.9 1826.1 Rearfoot strike on first session

3 39.67 2856.0 Increased running speed

4 31.15 3246.5

5 58.62 37.1 3517.5 2226 Rearfoot strike on firstsession

6 44.1 2072.7 Barefoot

IV. CONCLUSION

Using front-foot strike, the average vertical acceleration of the subjects are below 50 m/s2. Using rearfoot strike, the acceleration can exceed 55 m/s2 or more. However, exact number can’t be obtained caused by the limitation of the accelerometer.

The force that is given to the ankle depends on the weight of each subject. It can be seen that using rearfoot strike creates excessive force. Repeated excessive force may result to the limitation of the ankle strength holding the load, which means serious injury could be happened if the subject keeps using rearfoot strike for running. Using the front-foot strike removes all the excess force, therefore reducing the risk of injury. Other subject that is using front-foot strike only receives less than five times subject’s body weight on stance phase. From the data, it is recommended that the force to the ground must not exceed 5 times the body weight to reduce the risk of injury.

The device is able to differentiate whether subject using front-foot strike or rearfoot strike. It is seen each time subject use rearfoot strike, a warning light is active, despite its limitation to measure exact acceleration when the subject uses rearfoot strike. Therefore, this device proven to be successfully differentiates running style that the subject uses.

Most subjects said that the device is too complex to wear, however subject’s movement are not affected when using the device. All of the subjects said that the user interface needs readable information in order to make the subject know how to use it. Subjects said that they understand the result only if the researcher explains them the meaning of their result. These opinions are used for device improvement for future research.

REFERENCES

[1] Bamberg, S. J. M., A. Y. Benbasat, D. M. Scarborough, D. E. Krebs, and J. A. Paradiso. 2008. ”Gait analysis using a shoe-integrated wireless sensor system”. IEEE Transactions On Information Technology in Biomedicine 12(4):413-423.

[2] Dugan, S. A., and K. P. Bhat. 2005. “Biomechanics and analysis of running gait”. Physical Medicine and Rehabilitation Clinics of North America 16(1):603-621.

[3] Laughton, C. A., I. M. Davis, and J. Hamill. 2003. “Effect of strike pattern and orthotic intervention on tibial shock during running”.Journal of Applied Biomechanics 19(1):153-168.

[4] Bartlett, R. 2007. Introduction to Sport Biomechanics 2nd Edition. New York, NY: Routledge.

[5] Saputra, M. K. 2011. Design and Development of Automatic Continous Passive Motion Therapeutic System. BS Thesis. Department of Biomedical Engineering, Swiss German Univerity, Tangerang, Indonesia.

[6] Burdett, R. G. 1982. “Forces predicted at the ankle during running”.Medicine and Science in Sports and Excercise 14(4):308-316.


328


[IEEE 2013 3rd International Conference on Instrumentation, Communications, Information Technology,...

Documents

Transcript of [IEEE 2013 3rd International Conference on Instrumentation, Communications, Information Technology,...