mihradi 2011

2011 International Conference on Instrumentation, Communication, Information Technology and Biomedical Engineering

8-9 November 2011, Bandung, Indonesia

3D Kinematics of Human Walking Based on

Segment Orientation

S. Mihradi, A. I. Henda, T. Dirgantara, A. I. Mahyuddin*

Faculty of Mechanical and Aerospace Engineering,

Institut Teknologi Bandung, Indonesia

*Corresponding author: [email protected]

Abstract-Human walking analysis is instrumental in medical

rehabilitation because it gives quantitative information of

human body segment during walking. The present work is a

part of research on the development of 3D gait analyzer

system. The system consists of a program to process and

display 3D kinematics parameter of human gait based on

position and displacement of markers. Observational data is in

the form of marker position as a function of time in x, y, z axis.

This data is then processed to obtain somegait parameters. To

achieve good results, the marker position data is initially

smoothed to eliminate noises before further processing. The

program developed in the present research could succesfully

calculate some parameters of human gait such as spatio

temporal parameters, linear kinematics and angular

kinematics of joints.

Keywords: 3D Kinematics, Human Body Model, Gait

Analysis

I. INTRODUCTION

Human movement analysis has long been studied and

applied in various fields. The one that specifically studied

the characteristics of human walking is called gait analysis.

Human gait analysis is instrumental in medical rehabilitation

because it gives quantative information of human body

segment during walking.

In general, human gait can be measured by direct

measurement techniques and also imaging (optical)

measurement techniques. The main problem in direct

measurement techniques is subject has to carry many cables

or other components that can affects walking motion [1].

Most of the problems encountered by direct measurement

techniques can be overcame by imaging (optical)

measurement techniques.

Recently, the authors have developed an affordable

system for 2D kinematics and dynamics analysis of human

gait [2] by using a 25 fps home video recorder. The system

is further improved to overcome the occlusion problem of

markers [3] and has been successfully used to determine 2D

gait parameters of Indonesian people as an effort to develop

the first Indonesian gait database [4-5]. However,

information obtained from 2D measurement, i.e. in sagittal

plane is not as much as information obtained from 3D

measurement. Although the sagittal plane is probably the

most important one, where much of the movement

parameters could be observed, there are certain gait

pathologies where another plane (e.g., the frontal plane)

would yield useful information [6]. Therefore, development

of 3D gait analysis system is needed to obtain gait

parameters in frontal and transverse planes.

The present work is a part of research on development of

3D gait analyzer system. Acomputer program to process and

display 3D kinematics parameter of human walking based

on position and displacement of markers attached to some

body segments is developed. Observational data in the form

of marker position as a function of time in 3D space is

obtained from the 3D optical motion-capture system.

However, for the present analysis, dummy data is used

instead, in order to check the reliability of the developed

program by comparing kinematics parameters calculated by

the program with the ones from literature.

II. KINEMATICS MODEL

To observe the kinematics of human walking, a model

of human body should be constructed first. In this research,

human body is modeled by 8 segments as shown in Fig. 1.

This model is an improvement of a model introduced by

Vaughan, where he divides the human body into 7 segments,

where pelvis and HAT (Head Arm Trunk) is in one segment

[6]. For the present model, pelvis and HAT is divided into 2

segments. Therefore, the 8 segments are right foot, right

calf, right thigh, pelvis, HAT, left thigh, left calf, and left

foot.

In analyzing the kinematics of a system, reference axes is

required. Reference axes provides the position and

orientation of each segment. Fig. 2 illustrates the local

reference system (LRS) and global reference system (GRS).

The GRS has X-Y-Zaxes, and this axes are fixed for any

given camera arrangement. The second referenceis LRS

with x-y-z axes,where each of LRS is attached to one

segment. The LRS is called anatomical axes and there are 8

anatomical axes to describe orientation of 8 segments [7].

386978-1-4577-1166-4/11/$26.00 ©2011 IEEE



Fig.1. Human body model

Fig.2. Reference axes system

III. MARKER SYSTEM

The marker system described here referred to Vaughan

Kit Marker Set, developed by Vaughan [6]. The set uses 15

markers attached to lower part of human body.Thepositions

of markers are depicted in Fig 3.

To check whether or not the dummy data that represent

the markers position met the system of Vaughan Kit Marker

Set, at first, those data is visualized by the developed

program as skeleton display as depicted in Fig. 4. Red

circles describe positions of markers and the blue ones

describe approximate position of the joints.

IV. SMOOTHING PROCEDURE

To obtain good results, at first the marker position data

should be smoothed to eliminate noises. This step is

necessary since calculation of second or third order

parameters such velocity and accelaration is very sensitive

to noises. If those data are

Fig.3. Vaughan Kit Marker Set [2]

Fig.4. Skeleton display based on marker position data

used directly in the kinematics analysis, the results will be

highly inaccurate, as shown by dashed line in Fig. 5and6. In order to remove the noises, smoothing spline technique

is adopted to the raw data [8]. By using the smoothed data,

then the foot velocities and accelerations are calculated as

represented by solid lines in Fig. 5 and 6.

To obtain the most appropriate smoothing parameter

value, trial and error process is conducted until the obtained

curve is close to the one in the literature. Literature used in

the process is the velocity-accelaration curve of Vaughan

[6]. The process is illustrated in Fig. 7. Curves on the left are

calculation results obtained by varying the smoothing

parameter value.The curve on the right is from literature.

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Fig.5.Right foot velocity in x-y-z direction before (dashed line) and after

(solid line) smoothing

Fig.1. Right foot acceleration in x-y-z direction before (dashed line) and

after (solid line) smoothing

V. KINEMATIC ANALYSIS PROCEDURE

The procedure for kinematics calculations is described in

the flowchart shown in Fig. 8. Based on the flowchart and

the method described in [6], a computer program is

developed by using MATLAB. The graphical user interface

(GUI) is also constructed to help user to execute the

program easily. The GUI is shown in Fig. 9.

VI. RESULTS AND DISCUSSION

The program developed in the present workis used to

calculate general gait /spatio temporal parameters (cycle

time, cadence, stride length and speed), linear kinematics

parameters and angular kinematics parameters. The obtained

parameters are presented in the subsequent sub-chapters.

Fig.2. Smoothing parameter selection process

Fig.3. Flowchart of kinematics analysis.

Fig.4. Program developed in the presentwork.

A. Spatio Temporal

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Since the distance, the time and the number of steps are

all known from simulation, the kinematics gait parameters

could be easily calculated using the following formula:

1. Cycle time (s) = time (s) × 2/(steps counted)

2. Cadence (steps/min) = (steps counted)× 60/time (s)

3. Stride length (m) = distance (m) × 2/(steps counted)

4. Speed (m/s) = distance (m)/time (s)

Table 1 shows several calculated spatio temporal

parameters of the present data of human gait.

Table 1. Several kinematics parameters

Cadence

(steps/min)

Cycle

time (s)

Stride length

(m)

Speed

(m/s)

96 1.25 1.3 1.03

B. Linear Kinematics

At present, the program could calculate somelinear

kinematics parameter such as joint/segment position, its

velocity and linear acceleration. Fig. 10 shows right foot

position versus time, while velocity and linear acceleration

of the foot are depicted in Fig. 11 and 12.

Fig.5. Right foot position in x-y-z direction

Fig.6. Right foot velocities in x-y-z direction

Fig.7. Right foot accelerations in x-y-z direction

C. Angular Kinematics

Angular kinematics parameters obtained by the program

are joint angles, angular velocities and accelarations. The

results are shown in Figs. 13-17.

Fig.8. Joint angles of sagittal plane

Fig.9. Joint angles of transverse plane

Fig.10 Joint angles of frontal plane

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Fig.11. Right calf angular velocities

Fig.12. Right calf angular accelarations

VII. CONCLUSIONS

In the present research, a computer program to process

and display 3D kinematics parameter of human walking

based on position and displacement of markers attached to

some body segments has been developed. The program

could successfully calculate spatio temporal, linear and

angular kinematics parameters of human walking.

To ensure the reliability of the developed program, the

results have been compared to some parameters obtained

from the literature. The comparison showed that the

developed program sufficiently accurate and feasible to use.

ACKNOWLEDGMENT

The authors gratefully acknowledge the support from

Program Riset dan Inovasi KK ITB 2011 for the present

project.

REFERENCES

[1] David A. Winter, Biomechanics and Motor Control of Human

Movement, 4th ed. New Jersey: John Wiley and Son Inc., 2009.

[2] A. I. Mahyuddin, S. Mihradi, T. Dirgantara. A. Sukmajaya, N.

Juliyad, U. Purba, ”Development of an Affordable System for 2D

Kinematics and Dynamics Analysis of Human Gait”, Proceedings of

SPIE - The International Society for Optical Engineering, Volume

7522, 2010, Article number 75222L.

[3] Ndaru Juliyad, Sandro Mihradi, Tatacipta Dirgantara, and Andi Isra

Mahyuddin, "2D Observational Optical Motion System for Analysis

of Human Gait," in Regional Conference on Mechanical and

Aerospace Technology, Bali, 2010.

[4] A. I. Mahyuddin, S. Mihradi, T. Dirgantara, P.N. Maulido, "Gait

Parameters Determination by 2D Optical Motion Analyzer System",

Applied Mechanics and Materials, vol. 83, pp. 123-129, 2011.

[5] Prisanto Novapriya Maulido, "Penyusunan Basis Data Awal

Karakteristik Gait Berjalan Normal Indonesia Menggunakan Sistem

Analisis Gerak 2 Dimensi," Institut Teknologi Bandung, Bandung,

Tugas Sarjana 2011.

[6] Vaughan, C. L., Davis, B. L., O’Connor, J. C. Dynamic of Human

Gait, 2rd Edition, Kiboho Publishers, Cape Town, South Africa,

1999.

[7] Winter, D.A., “Biomechanic and Motor Control of Human

Movement”, 2nd Edition, John Wiley and Son Inc., New York., 1990.

[8] Purba, U. M., Mihradi, S., Dirgantara, T., and Mahyuddin, A.I. An

Inverse Dynamics of Human Walking Based on Experimental Motion

Analysis, RCMAE, Bali, Indonesia, 2010.

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