Ijmet 10 01_105

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International Journal of Mechanical Engineering and Technology (IJMET)
Volume 10, Issue 01, January 2019, pp.1014-1025, Article ID: IJMET_10_01_105
Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=1
ISSN Print: 0976-6340 and ISSN Online: 0976-6359
© IAEME Publication Scopus Indexed
ERGONOMIC DESIGN AND RULA ANALYSIS
OF A MOTORISED WHEELCHAIR FOR
DISABLED AND ELDERLY
Bobby P Paul
Assistant Professor(Sr.), SAINTGITS College of Engineering, Kerala, India
Research Scholar, Karunya Institute of Technology and Sciences, Coimbatore, India
Darius Gnanaraj S
Professor, School of Mechanical Engineering, VIT University, Vellore, Tamil Nadu, India
Sam Paul
Professor, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India
ABSTRACT
Motorised Wheelchair plays a pivotal role in the social life of Persons with
disability (PwD) or elderly. Indian Motorised Wheelchair users scuffle to identify
right Ergonomic Motorised Wheelchair because there are only very few designs
developed by Ergonomic approach. The paper describes the methods to design an
Ergonomic Motorised wheelchair and analyzes the design with Human Digital
Models(HDM). Authors also demonstrate analyses of user comfort and some
Ergonomic design methods. The analysis of user comfort while in the design stage
using a Manikin by applying Indian Anthropometric Data makes the wheelchair a
better fit for the Indian users. Thus, the design of user-friendly wheelchairs by HDM
Ergonomic analysis. Authors also discuss RULA analysis of Motorised Wheelchair
with 5th, 50th and 95th percentile HDM. The paper also estimates Indian
Anthropometric Dimensions on HDM for Motorised Wheelchair. The paper also
presents some design innovations on the footrest
Keywords: Assistive Technology· Motorised Wheelchair CATIA RULA·Human
Digital Models· Ergonomic Work Bench.
Cite this Article: Bobby P Paul, Darius Gnanaraj S and Sam Paul, Ergonomic Design
and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly,
International Journal of Mechanical Engineering and Technology, 10(01), 2019,
pp.1014-1025.
http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=1
1. INTRODUCTION

Bobby P Paul, Darius Gnanaraj S and Sam Paul
Motorized Wheelchair use rose to remarkable numbers due to the rise in the aging population.
Data from WHO shows 15% of the world population lives with some form of disability and 2-
4% experience severe difficulties in functioning [1]. India reported 20 million people in 2012
with disabilities, out of that, 11 million are locomotors disabled. Statistics in rural areas shows
approximately 1046 per 100,000 people and urban areas 901 per 100,000 people with are
locomotive disability [2]. Analysis of cost benefits of the ergonomic wheelchair is a challenge
because of the difficulty in collecting data on costs and benefits. The scarcity of data is also
another difficulty, as the motorized wheelchairs are uncommon [3].
In the past product-designers ignored the ergonomic requirements of the product in the
conceptual stage. However, further Ergonomic analysis is kept aside until a prototype.
Designers also neglected Ergonomic analysis as suitable virtual tools were unavailable. The
advancement of computers and the ability to compute faster brought significant improvement
in Software and its applications in different areas of Engineering. Computational Ergonomics
also leaped, and now it is not mere calculation by formulas, questionnaires, filling up tables or
accumulating empirical data. Instead, Human Digital Models (HDM) started a new phase of
computer-aided design technology. CATIA caters a variety of Ergonomic tools by using
Human Digital Models. HDM can aid computational analysis on human-machine interactions
and facilitates better ergonomic designs in the absence of real users [4].
Motorized wheelchair users are susceptible to lower back and other Musculoskeletal
Disorders (MSD) [5,6]. Ergonomic Motorized Wheelchairs designed for reducing repetitive
stress injuries, increased comfort, and safety of wheelchair users. Ergonomic Wheelchairs
improves the user experience while travel, getting on and off and in rough surfaces. Applying
Ergonomics is one of the significant challenges as the users are either lower limb disabled or
with some other severe disability on their motor functions. Analysis of cost benefits before
and after applying Ergonomics is a significant challenge for designers [3]. Literature shows
that the exposure of the wheelchair user to injuries is proportional to the wrong movements he
makes while shifting to and from the wheelchair. Long-term injuries for wheelchair users are
back pain or pain on hands and wrist while using the joystick for a more extended period. The
right form of lower back and wrist support can improve user safety, comfort and reduce long-
term Musculoskeletal injuries. Introduction of DHMs to represent the wheelchair user sitting,
and applying the right anthropometric data improves the design of the Motorized wheelchairs
[7]. RULA analysis using HDM makes the design process manageable and economical.
The paper discusses the process of Ergonomically optimizing the design using CATIA-
Human Digital Models and details on possible design changes, which makes it Ergonomic
and user-friendly. HDM made of Indian Anthropometric Data is placed on the Motorised
Wheelchair, and RULA analysis asses the user discomfort. After RULA analysis, exact
locations of discomfort are redesigned to increase the comfort of the user. Figure.2 in the
paper shows methods adopted for the Ergonomic Design of Motorised Wheelchairs using
Human Digital Models.
2. DESIGN METHODS
2.1. Folding Hinge
One purpose of the Motorised Wheelchair design is to enhance the fold-ability. Figure 1
shows the Motorised Wheelchair folding hinge for the multipurpose ladder joints. The four
legs and the seat are on hinges as in Fig.9(a, b&c). The steel hinge can bare load up to 150kg.
The weight of one hinge is 1.05kg and thickness of the plates used to manufacture the hinge is
2mm. The Motorised Wheelchairs uses hinges with self-locks for saftey[8].

Ergonomic Design and RULA Analysis of a Motorised Wheelchair for Disabled and Elderly
Figure 1 Hinge with Locks Ergonomic Design and RULA Analysis of a Motorised Wheelchair for
Disabled and Elderly
2.2. Ergonomics in CATIA
The motorized wheelchair comfort depends on material quality, structure, shape, handling,
and stability. Structure and shape in the design of motorized wheelchair depend on available
Anthropometric data of users, as Indian Anthropometric data is available in book form[9].
CATIA Ergonomic Work Bench can be of aid for Ergonomic analysis of Wheelchairs.
CATIA is the fist of its kind to suggest computational study by Human Digital Model to
analyze man-machine design [4]. Figure 2 shows the methodology adopted for the design of
Motorized Wheelchair by Human Digital Model using CATIA. RULA (Rapid Upper Limb
Assessment) virtually analyses user comfort on Motorized Wheelchair Design. There are four
modules in CATIA for Ergonomic Design and Analysis, Human Measurement Editor Module
(HME), Human Action Analysis Module (HAA), Human Posture Analysis Module (HPA)
and Human Builder Module (HBM). HME, HPA & HBA is used to analyze the user comfort
in Motorized Wheelchair. Indian Anthropometric Data for sitting posture is applied to HDM
using HME. RULA analysis uses HBM and HPA for appropriate postures. RULA is repeated
on the wheelchair model until the score turns acceptable for the design [4, 10]. The flow chart
shows the steps for optimizing a model using RULA.

Figure 2 RULA Analysis using CATIA - Methodology
2.3. Concise Description of Human Activity Analysis
The activities are pushing, pulling, lowering, effects of lifting, and comfort while sitting are
analyzed and optimized by Human Activity Analysis. CATIA Ergonomic analysis does not
require a real workplace or a person to execute. The virtual analysis in CATIA can investigate
and improve products and workplaces. Human Activity Analysis uses Manikin to evaluate
postures by a range of tools and methods in the digital environment. The designer can
virtually test and improve the design by applying different techniques. The Ergonomic fit of
Human Manikin determines product shape, size, and dimensions [11].
2.4. RULA on Assessment Sheet vs RULA Assessment in CATIA
Rapid Upper Limb Assessment (RULA) analyzes the upper extremity ergonomic risk factors.
The purpose of RULA is to check bio-mechanical and postural load requirements for the
neck, trunk, and upper extremities. The RULA assessment sheet is a single page worksheet,
used to assess the force, posture, and repetitions of work. In RULA worksheet, section A
assesses arms, wrists and section B assess of the neck and trunk. The score for sections A & B
is totaled to assess the risk of MSD. RULA analysis by mere observation, the results could
slightly vary from person to person. Manual RULA assessment is a single sheet of postures
and scores [12–14].
The digital RULA score complies for the Manikin. Once we place the HDM on the
digitally modeled workplace or product, the whole analysis that is conducted by observation
is just within reach of a single mouse click. According to analysis, the postures of the Manikin
varies. Optimize criteria in I.K Behavior panel, aids to optimize posture for RULA analysis or
Postural score. RULA Analysis tool is launched to select Manikin. Figure 3(a) shows criteria
for conducting RULA analysis in CATIA. The side of HDM to analyze and predetermined
best-suited posture is selected. There are three types of postures, Static, Intermittent, and
Repeated.

Table 1 5th, 50th and 95th Percentile Indian Male Anthropometric Dimensions for Human Digital
Models [9].
Variables (Sitting) 5th
mm 50th
mm
95th
mm
Input
Method
Sitting Height 812 844 893 Manual
Eye Height, Sitting 710 738 799 Manual
Hip Breadth, Sitting 272 331 405 Manual
Shoulder-Elbow
Length
306.311 340.167 386.54 Automatic
Foot Breadth 83 94 106 Manual
Variables (Standing)
Stature 1537 1648 1781 Manual
Axilla Height
1129.39
4
1222.92 1332.583 Automatic
Waist Height 894 970 1053 Manual
Chest-Height,
Standing
1088 1180 1282 Manual
Crotch-Height,
Standing
675 765 849 Manual
Acromion-Radial
Length
281 312 356 Manual
Radial-Stylion
Length
207 243 289 Manual
Sleeve out seam 484.823 547.383 629.404 Automatic
Chest Breadth 259 298 356 Manual
Waist Breadth 231 259 317 Manual
Hip Breadth,
Standing
272 331 397 Manual
Intermittent repeat the tasks less than or equal to four times in one minute. Static and
Repeated option in posture repeats the task greater than four times in one minute. In the same
posture option, we can select Arms Supported/Person leaning; Arms are working across Mid-
line and check Balance. Each should select according to the situation of the analysis. In the

parameters, 'Load' is filled to specify the load of the object manipulated by the person. The
score box shows the final score. Score range of each body part is in Fig 3(b). The risk factors
such as, which are the number of movements, static muscle workforce, working posture and
time, worked without a break is assessed in RULA analysis. Score 1 to 2 is color-coded in
green indicates the posture is acceptable.
(a) RULA Score Sheet (b) RULA Score Range
Figure 3 RULA Score Card & Range
Score 3 to 4 (Yellow) indicates further investigation or some minor design changes. Score
5 to 6 (Red) suggests immediate action by design change. The job of a design engineer is to
make modifications and bring the score within acceptable range 1 to 2 or (Green) [5, 15]. In
the paper, selects left and right sides of the manikin with posture as ’intermittent’ and ’arms
supported’ for analysis.
2.5. Preparation of Human Digital Model for Analysis
HDM for RULA analysis requires dimensions of human size. Human size varies with
ethnicity, gender and age group.[16, 17]. Anthropometric data is available for HDM in
CATIA for American, Canadian, French, Japanese and Korean. If the absence of data in
software, a Manikin can be made by entering available data. The manikin posture is made
sitting if the analysis is for sitting posture. Sitting posture for Manikin is by selecting the
option in the product. Figure 4(a)& 4(b) shows ways to apply HDM with Indian Male
Anthropometric dimensions of 5th
, 50th
, 95th
Percentile for having the size of Indian Manikin
[4, 15, 9, 18]. Each Manikin dimension can change in the Software or can set to automatic by
the software by considering other dimensions. Table 1. shows the 5th,50th and 95th Percentile
Indian Male Anthropometric Dimensions for three types of Human Digital Models. Posture
also can change for the Manikin according to sitting posture as shown in Fig 4(c&d). The
analysis on a motorized wheelchair, so the angle of the foot as 70 [19] as in Fig.4(c). The
angle of the leg or any other body parts can change using posture editor as shown in Fig
4(d)[4].
3. RESULT

3.1. RULA Analysis Results
RULA Analysis by placing 5th Percentile HDM on the Motorised Wheelchair: Figure 5(a)
shows the HDM with 5th per-centile anthropometric dimensions on the motorized wheelchair
with the arm supported on hand rest. The fingers are adjusted to place on the Joystick. The
analysis returned acceptable overall score 2 for the model. Only the wrist on left side Fig.5(b)
returned a score 2 for further investigation. The overall score of posture A is 2 because of the
wrist score 2
(a) Assign Dimensions-Sitting Manikin (b) Assign Dimensions-Standing Manikin
(c) Angle of Foot-70 (d) Posture Editor
Figure 4 Getting Manikin Ready for RULA Analysis
The score of posture B is 2 as it suggests improvements in Wrist, Arms and Trunk
support. RULA score on right side Fig.5(c) is same as in left except wrist has a Score of 3
which requires attention as per scorecard [5, 20, 21]. For RULA of 5th percentile, the seat to
footrest height was reduced to 283mm instead of 313mm.

(a) 5th Percentile HDM (b) RULA Score of Left Side (c) RULA Score of Right
Side
Figure 5 RULA Analysis with 5th Percentile Manikin
RULA Analysis by placing 50th Percentile HDM on the Motorised Wheelchair: The
RULA Analysis 50th percentile HDM in Fig.6 (a) scores better than that of 5th percentile.
Both left and right side of the wrist scored to improve the design as in Fig.6 (a&b). Posture A
scored 2, but posture B scored 1, which shows a person comes under 50th percentile has a
better score on the Motorised Wheelchair. Thus, Wheelchair dimensions justify for 50th
percentile HDM with acceptable score 1(Left) and 2(Right).
(a) 50th Percentile (b) RULA Score of Left Side (c) RULA Score of Right Side
RULA Analysis by placing 95th Percentile HDM on the Motorized Wheelchair: The 95th
percentile manikin as in Fig.7(a). The analysis on left side returned final score 1(Acceptable)
Fig.6(b), and right-side wrist and Forearm score of 2 which brought the final score to
2(Acceptable) Fig.6(c). The dimension of the footrest was increased to 351mm from 313mm
to avoid uncomfortable posture by raising the legs while sitting.

(a) 95th Percentile (b) RULA Score of Left Side (c) RULA Score of Right Side
4 DISCUSSION
The RULA analysis for 5th, 50th, and 95th percentile Manikins gave the acceptable final
score. For three Manikins footrest dimensions varied for a better posture. The results suggest
adjustable footrests for broader user groups. Design change in wheelchair legs for adjustable
height footrest should undergo Finite Element Analysis as it is the load carrying member. In
all analysis, the right-side wrist scored for further investigation. The right-side wrist score of
Motorised Wheelchair suggests further design changes for Ergonomic armrest and joystick.
Even though the shape of the joystick varies from the normal one, the positions of the buttons
and height are same as in standard wheelchairs available in the market. The Ergonomic
Wheelchairs for Indian users manufacturer can use the Bobby P Paul et al.
(a) Wheelchair Side View (b) Wheelchair Top View (c) Wheelchair Front
View
Figure 8 Wheelchair Dimensions

(a) Motorised Wheelchair
(b) Motorised Wheel chair Folded View (c) Foot Rest Folding
Fig. 9. Motorised Wheelchair
dimensions in Fig.8 to improve the design. Footrest dimensions vary with 5th, 50th, and
95th percentile users as in previous sections.
Each part should undergo further Finite Element analysis to determine the thickness.
While testing the wheelchair, it was observed that the footrest hits the ground while traveling
from inclined to the leveled surface. So, an innovative design of footrest on legs is developed
as shown in Fig.9(c) to avoid this problem. The footrest is fixed on the legs itself and can fold
before getting on the Wheelchair.
5 CONCLUSION
In the paper, a novel design of Foldable Motorised Wheelchair with ladder hinges is
discussed. Indian Anthropometric data for Motorised wheelchairs using Human Digital Model
is deduced. RULA Analysis is conducted to measure discomforts. An Innovative footrest is
developed to avoid footrest hitting the ground while traveling from inclined to leveled ground.
ACKNOWLEDGMENTS
The authors would like to acknowledge the help of Er. Arun K Varghese Assistant Professor,
SAINTGITS College of Engineering, Kottayam, Kerala, Mr Bhargav Sundaram, Chief
Executive Officer, Calladi Motor Works, Chennai, Mr Rabindran Isaac, Manager at Samiti for
Education, Environment, Social Health Action (SEESHA) Coimbatore, Mr Manjunath Reddy,
Mr Ashwin B.N, Mrs Geetha Ashwin, Mr Krishna Kumar for giving us all supports in the
design and development of Foldable Motorised Wheelchair for PwD & Elderly. We especially
thank Kerala Council for Science Technology and Environment (KSCSTE) for funding this

project through the scheme of TECHNOLOGY DEVELOPMENT & ADAPTATION
Program (TDAP).
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