Download Integrated Sensor System for Gait Analysis

International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) - 2016
Integrated Sensor System for Gait Analysis
Jyoti Patil
Assistant Professor: dept. of Instrumentation Technology
B.V.Bhoomaraddi College of Engg & Technology
Hubballi, India
[email protected]
Abstract— The paper is about the work done for the requirement
of gait analysis on the shoe for a limped person. The method
adopted can help the doctor to treat a person with gait
abnormalities. Gait analysis deals with the study of walking
pattern, in order to understand the gait abnormalities. To treat
these gait abnormalities it’s necessary to analyse gait parameters
such as foot angle, stride distance, step distance, step count,
cadence, speed, progression line etc. This project presents a shoe
device to measure these parameters with the help of various sensors
such as accelerometer, ultrasonic sensor, gyroscope, foot pressure
sensor, flex sensor etc. These sensors can be placed in the shoe such
that sensors can accurately measure these parameters. The digital
output of these sensors can be integrated through a controller and
the result of the patient is sent to the doctor’s phone or to a GSM
device. Hence, this wireless shoe device helps to overcome the
disadvantages of the existing system which is practiced in gait
motion analysis laboratory. Results of shoe device can be compared
with the gait of a normal person in order to differentiate and study
the abnormal and normal gait of a person. The development of shoe
device is mainly concerned with features like low cost, portable,
ease of use and accurate measurements of gait parameters. The
objective of shoe integrated sensor system for gait analysis is to
provide better digital output results of the abnormal parameters
and efficient way of analyzing than clinical gait. This device has
various applications in sports for exercise training, medicinally in
treating paralyzed patients and in biometric and forensics to
identify/improve individual patient by making minor variations.
Keywords — gait analysis, step length, GSM, Internet of Things
I. INTRODUCTION
The technological aspects of design and developing healthcare
systems to cope with the increase of global widespread of
chronic neurological disorders related to human locomotion.
Locomotion involves standing, walking, jogging, running, etc.
The systematic study of locomotion is called Gait Analysis.
In simple terms Gait can be defined as manner or
style of walking and its analysis is the combination of
kinematics and kinetics data. A gait abnormality is a deviation
from normal walking. Cerebral vascular disease is the main
cause of gait disability; it may result in long-term disability
and handicap. The quality of life depends on the mobility of a
person hence the walking recovery becomes main aim of a
gait Analyst, which determine the status, activities of patients.
978-1-4673-9939-5/16/$31.00 ©2016 IEEE
Deeksha Nandur, Meghana Mellikeri, Kritika Naik
and Pallavi Kulkarni
B.E: dept. of Instrumentation Technology
B.V.Bhoomaraddi College of Engg & Technology
Hubballi, India
[email protected]
The gait of hemispheric stroke patients is characterized by
several abnormal disabilities such as asymmetry of stride time
and length, poor joint and posture control, muscle weakness,
abnormal muscle activation patterns, abnormal muscle tone
and altered energy expenditure, mostly affecting the paretic
side. The causes of these Gait abnormalities can also be the
result of muscle weakness or tightness, leg fracture or any
damage to legs and feet. The basic pathological gaits that can
be attributed to neurological conditions are Hemiplegic,
neuropathic, Parkinsonian, Myopathic, spastic diplegic etc.
Gait analysis is seen in conditions such as Parkinson’s disease,
cerebral palsy, and neuromuscular disorder.
Quantitative gait analysis provides an objective
assessment of the effectiveness of various treatments focusing
on improving gait abnormality. For instance, gait analysis, as
an evaluation tool, has been used in a shoe for the benefits
after the person undergoing orthopedic surgeries and relieve
muscle spasms in persons with gait disability. Gait analysis in
earlier days was performed in motion analysis laboratory [4]
where several high-resolution cameras are used to get the
patient’s motion on the walkway setup. The patient walks with
certain sensors connected to his body where gait parameters
are to be obtained. The clinical gait analysis is wired system
network were output is obtained on the computer monitor and
complete analysis of the human body. Alternative to clinical
gait analysis treatment, where mild gait disability is found,
doctors used the traditional way of diagnosing the patient by
observation. In the observational method of treating the
person, the results are quite appropriate but not possible to
recognize small deviation from naked eye and there can be
random errors in treating the patient.
Fig.1. Motion analysis laboratory
Recently Quantitative Gait analysis has become a
tool through which doctors can measure gait parameters and
treat the persons with walking disabilities. The proposed
system is different from observational gait analysis in terms of
tool usage and result generation. The observational analysis is
just watching a walking of individual and analyzing it which
can be quick but not accurate. Quantitative analysis can be
time-consuming and costlier than observational due to the
involvement of instruments to exactly measure gait parameters
but there are exact results which help a doctor to treat gait
abnormality person. The proposed work is to overcome all the
above traditional methods and give a new dimension to the
analysis of gait disability by digitalizing the output.
II. METHODOLOGY
The survey of many patients with different types of
gait abnormalities has been done. By this survey, we found
that gait abnormalities were found irrespective of age, from
birth defects to old age. Also in psychological and
neurological disorders such as conversion disorder, cerebral
palsy, Parkinson, leg injuries etc. The available devices and
systems provide the output in the analog form [6]. Analog
signals have distortion which creates a loss of signals and it is
not able to recover the attenuated signals. These were difficult
for doctors to understand and analyze the output of gait
abnormality. This limitation has been taken as the main
objective of the project to do it with sensors and get digital
output. The traditional way of calculating and treatment of the
abnormalities required heavy instruments and the process is
time-consuming. We found a simple method in which the
patient’s abnormality report could be easily calculated.
Furthermore, this information would be used by the doctor to
treat the patient or patient can use it for self-treatment. So
there is need to develop a portable device which measures the
gait parameters and helps in rectification of gait abnormalities
and provides better walking and running abilities for a person.
A. BLOCK DIAGRAM
measure foot angle and micro switch measures step count.
The output of these sensors is integrated through Arduino.
The Arduino board used to develop software for the
sensors and for communication is done through the
controller. Controller is connected to USB to UART
convertor and result obtained in Arduino is sent to the
GSM device. Universal Serial Bus (USB) to Universal
Asynchronous Receiver Transmitter (UART) convertor is
used for two different communication modules i.e.
Arduino and GSM to communicate with same voltage
level control. Here serial communication is used in order to
confirm whether data is successfully transmitted or not
through ACK signal, this ACK feature is not available in
parallel communication. Parallel communication requires
more hardware than serial communication hence in order
to get the output of all the sensors consequently serial
communication is suitable for the project. Results of a
patient are sent to doctors phone through which doctor can
treat gait disability patients; it can also be sent to patient’s
phone so that he would be able to note the performance of
his walk. The output is the data how many steps the patient
walks, average angle tilted by the foot, distance between
the two steps taken. This is implemented by making a
patient wear this shoe device and asking him to walk a few
no of steps. This is experimented with shoe device by
collecting results from different gait disability patients.
B. CONTROLLER AND SENSORS
1.
Controller
The controller used in this work is Arduino UNO,
which is an open-source controller. The controller is used
for interfacing all the sensors and integrates the results of
each sensor. These sensors are programmed and the code is
embedded in the Arduino. This controller supports SPI,
USB, and UART; here UART has been used for
asynchronous serial communication. Arduino also provides
a GSM module interface required in the project to transmit
the messages.
Sensor type
Flex sensor
Ultrasonic
sensor
Micro switch
TABLE 1
SENSORS FOR GAIT ANALYSIS
Parameters
Output
Resistance change
Foot angle
corresponding to angle.
Signal transmitted and
Step length
received corresponding
to distance.
Voltage change
Step count
corresponding to step
count.
Fig.2. Block diagram of gait analysis
The Fig.2 shows the overall work that is done in this
project. The sensors are used to measure gait parameters.
The ultrasonic sensor is used to measure the distance
between 2 steps. Flex sensor is a resistive sensor used to
2.
Flex sensor
Flex sensor is a type of transducer which provides
variation in resistance as we change the angle of a flex
sensor. Hence, it consists of carbon resistive elements in
the thin flexible strip. As the angle changes, there will be a
change in carbon concentration. Bend in flex
sensor is directly proportional to change in resistance. It is
used in gait analysis to provide a variation of resistance
between 22K ohm to 40K ohm when it bent up to 0-30°.
3. Ultrasonic sensor HC-SR04
Fig.5. Ultrasonic sensor
Fig.3. Flex sensor
Smaller the bend value, higher is the resistance, this
change in resistance further connected to voltage divider
circuit where we get a change in voltage. Then this change
in voltage is connected to one of the Arduino’s analog
input.
TABLE2
Flex sensor angle
Output voltage
in degree
in volts
0°
1.74
In the present work the use of ultrasonic sensor is to
calculate the distance between two steps. It takes the input
voltage as 5V which is connected to the Arduino UNO board.
The triggering point for the ultrasonic sensor depends on the
micro switch which is placed in a shoe sole. When the
ultrasonic sensor is triggered with the minimum triggering
time i.e. 10us then it waits for echo signal which is reflected
from next forward step. This signal is used to find the time
taken between trigger and echo signal from which further
calculation is taken to calculate the exact distance (in cm)
between two steps.
Step distance is calculated by the formula:
Step distance = time / 58.8
Patients
TABLE 3
Time taken
Step distance
in cm
22
10°
1.95
Patient X
in min
3
20°
2
Patient Y
3
18
2.10
Patient Z
3
25
30°
3. Micro switch:
4.
USB to UART convertor
A micro switch is a type of momentary contact switch. The
actuator of the switching has a hinged wheel placed on the
push button. For switch action, the connection is made to the
C (common) and NO (normally open) terminals. The switch
will be open when not pressed and closed when pressed.
The interface of the micro switch to the Arduino in the usual
manner as shown here.
Fig.6. USB to UART convertor
Fig.4. Connection of micro switch with arduino
Micro switch output gives the result of a number of steps
taken by a person.
The use of USB to UART convertor is to provide
proper communication between Arduino and GSM. So the
voltage level for both communication modules has a different
level indication for logic 0 and 1. This convertor has an IC
MAX 232 which does a job of voltage level controller
between two different communication modules. In Arduino
module, TTL logic representation is used. In TTL, logic 1 is
represented by +5V and logic 0 is represented by 0V. In GSM
module, CMOS logic is used. Logic 1 is represented by +3.3
to +5V and logic 0 is represented as -3.3 to -5V.
III. RESULTS AND DISCUSSION
The final outcome of the project is the average result of all the
sensor parameters calculated. The results are compared with
normal person’s gait to see the deviations in the patient. The
results are analyzed by a doctor for improvement or treatment
in gait disability.
It is portable when compared to the present day
equipment available. The cost is low and is affordable by all
classes of society.
The further advancement of this work can be
extended as an Internet of Things (IoT) application instead of
GSM. The integrated setup of sensor controlled by Arduino
supports IoT. Through IoT, the results obtained by sensors can
be stored and transmitted to the doctor. The task may involve
many numbers of doctors and patients to communicate. IoT
helps the doctor to treat the patients from anywhere at any
time using the database of results. This is can also maintain
the previous and present records of the patients for further
diagnosis. Use of IOT incredibly benefits health care system.
Acknowledgment
We are thankful to Dr. Vasudev V Vader,
physiotherapist for his partial support. We also thank our Head
of the department Dr. Nalini Iyer and our department
Instrumentation Technology for their support and cooperation.
Fig.7. Shoe device used for gait analysis
References
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Alexander Rampp, Jens Barth, Samuel Schulein, Karl-Gunter Gaßmann,
Jochen Klucken, and Bjorn M. Eskofier, “Inertial Sensor-Based Stride
Parameter Calculation From Gait Sequences in Geriatric Patients.” IEEE
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Fig.8. Result obtained in phone after the analysis
The final output of the project is as shown as in Fig.8.
The system gives a message as the patient completes walking.
This message can be given to any number that is fed to GSM
module. The patient can monitor his statistically significant
changes in the phase of walking. Gait shoe device is used by
sports person for better gait pattern. It keeps the track of
sportsman mobility and flexibility. Functional strength and
movement analysis can be precisely done.
IV. CONCLUSION AND FUTURE SCOPE
Gait analysis helps in detecting the defects which are
difficult to spot from a physical test or by observation. Shoe
integrated system helps in spotting these defects exactly by
quantifying it using the techniques of instrumentation and
study of sensors. Different results were obtained from a
number of patients wearing a shoe. The doctor observed the
results through the GSM to treat the patients accordingly. This
device helps in accurate analysis and the results will be
obtained immediately which helps in improving the quality
life for patients.
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Alberto Ferrari, Pieter Ginis, Michael Hardegger, Filippo Casamassima,
Laura Rocchi and Lorenzo Chiari. “A Mobile Kalman-Filter Based
Solution for the
Real-Time Estimation of Spatio-Temporal Gait Parameters.”
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