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Forces on the Foot During Various Exercises

Forces on the Foot During Various Exercises

Group E2: A. KADAKIA, J.R. LINDNER , and J. VINCENT

1. Introduction

The objective of our project is to design and test a force/pressure sensing system capable of measuring the

force from the bottom of a shoe during different loading applications. Current force/pressure testing systems

are expensive and it is often difficult to obtain accurate readings. Therefore, we hope our technology will be

both inexpensive and accurate in comparison. Our system can be used to determine differences in forces

exerted on the bottom of the foot during activities such as walking, walking at different inclines, and jogging.

These results can be applied to numerous applications. Doctors will be able to use this sensing system to

suggest appropriate shoes to patients with joint/bone pain. The results from this sensing system could help in

designing prosthetic devices and could also be used to help choose materials for implants, based on the

stresses and strains seen in peoples’ feet. The force/pressure sensing system works by attaching pressure

sensors to the front and heel of an insole that can be inserted into a shoe. The pressure sensors are connects is

processed through a circuit board and is then connected to LabVIEW to be further analyzed. The LabVIEW

front panel illustrates the force and percent body weight the person exerts on different parts of the foot.


2. Experimental Set-up


BLAH.bmp

Our system works by attaching 2 100-lb FlexiForce pressures to the bottom of the foot, one at the heel and

one at the front of the foot. The sensors are connected to a breadboard which processes the signal according to

the diagram above. We powered the pressure sensors with 0.3 volts. We used a LM741 operational amplifier

rather than the suggested MCP6001 ship and powered it with 5 volts. Additionally, the resistance across the

circuit (R

f) was 1000 ohms. When force is applied to the sensor, the resistance of the sensor decreases. In

order to use the sensors, we had to calibrate them by applying known forces to the sensors and equating the

sensor resistance output to the forces. From that, we had to create a force vs. conductance curve to find a

linear interpolation. This was used to display the forces in our LabVIEW program. From the breadboard, our

signals from the sensors lead into a DAQ board to be further analyzed with our LabVIEW VI. The LabVIEW

program displays the force exerted on each sensor on the foot. You can also input the body weight of the

person using the system to display the percent body weight being exerted onto each sensor.


3. Results

The results of our experiments were relatively conclusive. We found that as the speed of walking increases

from 1.5 to 4 MPH the force exerted on the heel and the forefoot increased. However, forces on the heel

increased more. This increase is due to the fact that the foot hit the ground harder the faster you walk. The

forces on the heel were larger because the heel absorbs most of the initial impact from walking. However, the

test subject began to jog at 4.5 MPH, the forces on the heel decreased significantly due to the fact that the

subjects ran on the front of their feet and avoided heel slamming. As the graph below shows, as the force

exerted on the forefoot sensor also decreased because this particular subject ran on the outside of his foot

where there was no sensor. From our test, we also found that as the incline of walking increased, the force on

the heel sensor went to almost zero and there was a relatively constant force on the forefoot sensor regardless

of the grade since that particular subject walked on the outside of his foot. This data can be seen below.

BLAH.bmp

Our system met the acceptance criterion. We wanted to be able to accurately quantify the forces exerted on

the bottom of the foot during various exercise. We were able to successfully do that. However, due to the

budget, time, and durability of the sensors, we were unable to incorporate more sensors into our system to get

more robust results. However, from the data we acquired we were also able to determine whether subjects

walk and run on the inside or outside of their feet. Our system was very reliable and we were able to get very

repeatable results. However, we were required to constantly recalibrate the sensors due to the drift and

fragility of the sensors.


4. Discussion and Conclusions

The goal of our experiment was to design a force measuring system capable of measuring the forces exerted

on the feet during various exercises. To implement this system, force sensors were attached to a running shoe

insole. The sensors were connected to a LabVIEW VI which recorded and displayed the forces each sensor

experienced. Originally, we planned to implement four sensors on the insole in order to diagnose the way a

person walks and runs, but the sensors proved to be fragile; one broke and we were left with only two sensors

and a backup sensor.

From our experiments we have concluded that walking puts more force on the heel of the foot than on the

forefoot and these forces increase linearly with speed. At the transition from walking to jogging, the larger

forces are experienced at the forefoot rather than the heel. While walking up inclines, the heel experiences

little to no force while the forefoot bears most of the force. With only two sensors and their positioning on the

insole, forces could have been distributed to other areas of the foot that were not being recorded. The sensors

were very noisy at low forces which led to difficult analysis in the range of zero to five pounds. Our system

can be vastly improved by implementing more force sensors on the insole, more accurate sensors, and by

adding a wireless system. With more sensors, we could determine how a person runs and walks and the

average force that person's foot experiences. A wireless system would allow tests to be conducted at higher

speeds of running and allow a wider range of mobility.


5. Application

Our current system does not allow us to diagnose in real time how a person walks and runs (pronation or

supination). We must analyze the data after the experiment has been conducted. We would like to implement

a real time diagnosis, but in order to accomplish this, we would require at least four sensors to provide a

reasonable diagnosis. With real time diagnosis, people can be told how they walk, which shoes and insoles

would provide adequate support to alleviate pain experienced accompanying walking. In addition, athletic

trainers could suggest proper running shoes for athletes to minimize injury during athletic training.

Attachment: Original Report

Contributors