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Invited Plenary Paper

Quantitative postural load assessment for wholebody manual tasks based on perceived discomfort

MIN K. CHUNG{*, I. LEE{ and DOHYUNG KEE§

{Division of Mechanical and Industrial Engineering, Pohang University of Science and

Technology, Hyoja San 31, Pohang 790 – 784, Korea

{Department of Safety Engineering, Hankyong National University, Ansung, Korea§Department of Industrial and Systems Engineering, Keimyung University, Daegu,

Korea

Many Korean workers are exposed to repetitive manual tasks or prolonged poor

working postures that are closely related to back pain or symptoms of

musculoskeletal disorders. Workers engage in tasks that require not only

handling of heavy materials, but also assuming prolonged or repetitive non-

neutral work postures. Poor work postures that have been frequently observed in

the workplaces of shipbuilding shops, manufacturing plants, automobileassembly lines and farms often require prolonged squatting, repetitive arm

raising and wrist flexion and simultaneous trunk flexion and lateral bending. In

most manufacturing industries, workers have to assume improper work postures

repetitively, several hundreds of times per day depending on daily production

rate. A series of psychophysical laboratory experiments were conducted to

evaluate the postural load at various joints. A postural load assessment system

was then developed based on a macro-postural classification scheme. The

classification scheme was constructed based on perceived discomfort for various

joint motions as well as previous research outcomes. On the basis of the

perceived discomfort, postural stress levels for the postures at individual joints

were also defined by a ratio scale to the standing neutral posture. Laboratory

experiments simulating automobile assembly tasks were carried out to

investigate the relationship between body-joint and whole-body discomfort.

Results showed a linear relationship between the two types of discomfort, with

the shoulder and low back postures being the dominant factor in determining the

whole body postural stresses. The proposed method was implemented into a

computer software program in order to automate the procedure of analysing

postural load and to enhance usability and practical applicability.

Keywords: Repetitive tasks; Postural load; Discomfort; Stress.

*Corresponding author. Email: [email protected]

Ergonomics, Vol. 48, No. 5, 15 April 2005, 492 – 505



1. Introduction

Among the current global workforce of 2.6 billion (over 45% of the world’s population),

approximately 30% of the workforce in developed countries and 50 – 70% in developing

countries are exposed to heavy physical workloads or ergonomically poor working

conditions. These conditions involve lifting and moving heavy items and repetitivemanual tasks (World Health Organization 1997). Such tasks often lead to musculoske-

letal disorders and serious injuries. Work-related musculoskeletal disorders (WMSDs)

have been recognized as a serious social problem because of the rising costs of wage

compensation, medical expenses, reduced productivity and lower quality of life (Ayoub

and Mital 1989, Ayoub 1992, Chaffin et al . 1999). In many developed countries, WMSDs

are the main cause of both short-term and permanent work disability, leading to

economic losses that amount to as much as 5% of the gross national product (World

Health Organization 1997). In the USA, it has been reported that as many as 2% of the

entire workforce suffers from a WMSD every year and these disorders account

disproportionately for over one-third of all worker compensation costs for medical care

and lost wages (Faucett et al . 2002).

In Korea, the prevalence of WMSDs, including low back injuries, has increased

considerably (see figure 1; Korea Occupational Safety and Health Agency 2002). When

Korea was experiencing economic problems in 1997 and 1998, the number of yearly

compensated workers for WMSDs was less than 250. That number increased to 1598 in

2001. The steep increasing trend is expected to continue for several years, since the

compensation for WMSDs began in the mid 1990s. It is presumed that there are many

latent injured workers who have been exposed to the risk factors of WMSDs for a long

time. As information on WMSDs spreads in society, the social compensation costs for

WMSDs will increase significantly.

It has been known that WMSDs are caused by multi-factorial operations of variousrisk factors such as working posture, repetitive and forceful activities and static muscle

load (Kroemer 1989, Hagberg et al . 1995, Bernard 1997, Kumar 2001). Among these, the

association of poor body postures with pain or symptoms of musculoskeletal disorders

has been reported in a number of studies (van Wely 1970, Grandjean and Hu ¨ nting 1977,

Westgaard and Aara ˚ s 1984, Armstrong 1986, Putz-Anderson 1988, Armstrong et al .

1993).

Figure 1. Number of the injured of work-related musculoskeletal disorders in Korea

(Korea Occupational Safety and Health Agency 2002).

Quantitative postural load assessment 493



In many typical manufacturing settings in Korea, a majority of workers perform their

jobs by assuming prolonged or repetitive non-neutral work postures. In addition, since

there exist cross-cultural variations in postural habits (Bridger 1991, Kroemer et al . 1994,

Chung et al . 2003b), Koreans frequently assume postures that are not familiar to

Westerners, such as deep squatting, kneeling and cross-legged sitting. Figure 2 illustrates

examples of poor working postures frequently observed in Korea. Included are prolongedsquatting, repetitive arm raising and wrist flexion, simultaneous trunk flexion and lateral

bending. These postures occur in shipbuilding shops, manufacturing plants, automobile

assembly lines and farms. In most manufacturing industries, workers are required to

assume improper work postures repetitively, more than several hundred times per day

depending on the daily production rate.

For ergonomics interventions for such tasks, it is not sufficient to rely solely on

biomechanical and/or physiological approaches to assess exposure to the risks of

WMSDs, because a majority of these tasks do not require much handling of heavy

materials or dynamic motions. Instead, the methods that focus on the evaluation of

postural stresses need to be used quantitatively and objectively. These include

observational methods, instrumental or direct methods, self-reports and other

psychophysical methods (Genaidy et al . 1994, Winkel and Mathiassen 1994, Li and

Buckle 1999). Among them, the observational techniques are more widespread in

industry than other techniques. Observational methods provide relatively reliable

information about the risks of WMSDs while neither interfering with job process nor

Figure 2. Typical examples of poor working postures in Korea.

494 Min K. Chung et al.



requiring the use of equipment for recording body postures (Genaidy et al . 1994, Kilbom

1994, Winkel and Mathiassen 1994).

Several observational techniques have been reported in the ergonomics literature

(Genaidy et al . 1994, Li and Buckle 1999, Lee 2002). In many of these techniques, a

postural classification system was defined by dividing the range of motion (ROM) into a

series of ranges. Work analysts then used the classification system for recording workpostures and evaluating postural load. While many postural classification systems have

been developed to enhance the reliability of observation by adopting macro-postural

classification (Genaidy et al . 1994), few studies have presented definite criteria for the

classification of postures. Only a few postural classification schemes are equipped with

criteria for evaluating postural workload. Although some methods, such as OWAS

(Ovako Working Posture Analysis System), RULA (Rapid Upper Limb Assessment) and

REBA (Rapid Entire Body Assessment), have adopted procedures for evaluating

postural stresses (Karhu et al . 1977, McAtamney and Corlett 1993, Hignett and

McAtamney 2000), they are based on the subjective ratings of experts instead of a more

objective basis (Genaidy et al . 1994, Juul-Kristensen et al . 1997, Kee and Karwowski

2001).

In this study, a psychophysical approach was adopted in evaluating postural load and

classifying joint motions based on the level of perceived discomfort. There have been

several experimental studies to assess postural load based on the perceived discomfort for

static joint postures or motions (Putz-Anderson and Galinsky 1993, Genaidy et al . 1995 ,

Kee and Karwowski 2001). Putz-Anderson and Galinsky (1993) adopted a psycho-

physical approach to determine work durations for limiting shoulder-girdle fatigue in a

set of experiments. They showed that psychophysically determined work durations

significantly decrease as task loading variables such as repetition rate, required force, tool

weight and reach height increase. Genaidy et al . (1995) reported a ranking system for the

stressfulness of non-neutral static postures around the wrist, elbow, shoulder, neck andlower back, based on perceived discomfort. Kee and Karwowski (2001) proposed a

postural classification scheme for the upper body based on perceived joint discomfort.

These studies adopted a psychophysical approach rather than using other objective

measures such as electromyographic signals, from which it is very difficult to quantify the

stress of static postures.

This study is intended to develop a quantitative and practically useful methodology

for evaluating postural stresses based on psychophysical discomfort. An observation

method with a macro-postural classification scheme was developed based on a series of

experiments in which stresses of static postures were evaluated psychophysically. In the

experiments, perceived discomfort for various static postures at each joint wasevaluated. The perceived discomfort data were used in determining the level of postural

stresses for each classified posture in the postural classification. In addition, the

relationship between body-joint discomfort and whole-body discomfort was investi-

gated based on the results of another experiment in which the whole-body postural

discomforts for various static work postures were evaluated. Finally, the proposed

method was implemented into a computer program in order to enhance its usability

and practical applicability.

2. Psychophysical evaluation of various static postures

Three different lab experiments were conducted to measure perceived discomfort for the

upper-body (Experiment 1a), leg (Experiment 1b) and complex trunk postures




(Experiment 1c). Although the experiments were performed separately with different

subjects, the same experimental protocol was adopted. In each experiment, the subjects

were asked to maintain a given posture for a 1-min duration and then to report their

perceived discomfort for the posture.

2.1. Experimental methods

In Experiment 1a, participants were 19 male students. Means and standard deviations for

age, stature and weight were 25.4 (2.7) years, 171.9 (6.0) cm. and 67.1 (7.0) kg respectively.

Participants were required to report their perceived discomfort for varying postures of the

five upper-body joints, i.e. wrist, elbow, shoulder, neck and low back. For each joint

motion, perceived discomforts were measured at the five levels of joint angles that were

determined in terms of the percentage of range of joint motion (ROM): 0% (neutral

posture), 25%, 50%, 75% and 100% of ROM, respectively (Kee and Karwowski 2001).

In Experiment 1b, participants were 18 healthy male students. Means and standard

deviations for age, stature and weight were 3.1 (2.8) years, 174.4 (4.4) cm and 68.9 (5.2) kg

respectively. Thirty-one leg postures were tested in the experiment. The postures can be

grouped into six categories: standing; knee-flexed; one-foot; sitting; kneeling; and

unbalanced postures (Chung et al . 2003a).

In Experiment 1c, participants were 12 healthy male college students. The means and

standard deviations for age, stature and weight were 21.2 (2.1) years, 174.5 (5.1) cm and

66.9 (6.6) kg respectively. Participants evaluated 29 different ‘complex trunk postures’

that can be defined as trunk postures involving two or three trunk motions

simultaneously, such as flexion, lateral bending and rotation (Lee et al . 2003).

In evaluating perceived discomfort, the free-modulus magnitude estimation method

that is widely used in psychophysics to evaluate human sensations to a physical stimulus

was applied (Gescheider 1985). The participants numerically estimated their feelings of discomfort for a given posture without any standard stimulus and a corresponding

number or verbal anchor. Before conducting the main experiment, a pre-test was

conducted to familiarize participants with ratio judgement tasks and to screen out those

who lack the ability to perform a ratio judgement. In this study, ‘numeric estimation’ and

‘line production’ were used in the pre-test, because of their wide usage and practical ease

(Han et al . 1999).

The participant was asked to adopt the postures as instructed by the experimenters and

to maintain each posture for a 1-min duration. The postures were presented in a random

order for each subject. All subjects were allowed at least a 2-min rest period between

consecutive trials and a 15-min break every hour (Lee 2002).Since each participant usually assigns different numbers to a given stimulus in free-

modulus magnitude estimation (Gescheider 1985, Han et al . 1999), the discomfort rating

data were normalized by the maximum normalization method. The discomfort rating

scores were divided by the maximum discomfort rating data for each subject. For the

normalized data, ANOVA were performed to examine the effects of posture on perceived

discomfort. Duncan’s multiple range test was used to group the postures according to the

discomfort level at each joint (Montgomery 1991).

2.2. Upper body postures

The differences in discomfort ratings between joints were not noticeable at low-range

levels of joint motions. However, they became more obvious as the range of levels




increases. Joint motions can be grouped into four categories by discomfort ratings at

100% ROM with significant differences (a= 0.05): 1) low back extension; 2) low back

flexion and lateral bending; 3) shoulder postures, low back rotation and neck extension;

4) the other postures in the neck, wrist and elbow. This result is somewhat different from

Genaidy et al . (1995), which showed that shoulder posture has the highest level of stress.

The difference may be due to different ranges of postures used in the experiment. Genaidyet al . (1995) did not consider the subject’s full range of motion in each joint motion.

In evaluating working postures, it should be noted that although there are some

differences in the order of stressfulness of joint motions, the postural load varies

according to the associated joint motion, as shown in many other studies (Genaidy and

Karwowski 1993, Genaidy et al . 1995).

Extension posture is not a common working posture as compared to other joint

motions such as low back flexion and shoulder flexion. However, it is necessary to include

extension postures in the evaluation of working postures, since this posture is found to

cause a higher level of load than other postures. Concerning joint motions in a joint,

extension showed higher discomfort ratings than other motions such as lateral bending,

flexion and rotation in the low back, neck and wrist. However, in the shoulder there were

no significant differences among joint motions. Specifically, low back extension should be

evaluated as a high-load inducing posture.

Figure 3 shows an example of the results of Experiment 1a: mean discomfort ratings

for the flexion and extension postures in the low back. The discomfort ratings for the two

motions of the low back showed a similar trend. All ranges showed statistically different

values of discomfort rating in low back flexion and extension (a= 0.05).

2.3. Leg postures

Knee flexion was found to be the most important factor for determining the discomfortlevel of leg postures. Other compounding factors, such as imbalance and one-foot

supporting condition, also increase the discomfort level. Most severely knee-flexed

postures with or without a combination of other factors showed a level of discomfort

significantly higher than other postures. Mildly knee-flexed postures also exhibited higher

discomfort than standing and sitting postures (see figure 4). The higher discomfort level

seems to be caused mainly by the contraction of large muscle groups of the thighs to

maintain the knee-flexed postures and an asymmetric postural burden in the imbalanced

postures.

Figure 3. Mean discomfort ratings for low back postures. (a) Flexion; (b) extension.




Kneeling postures showed the highest discomfort levels among the evaluated leg

postures. Kneeling postures with fully flexed knees and kneeling on a knee showed a

higher discomfort level than mildly knee-flexed postures, and kneeling with a knee angle

of 908 showed a significantly higher discomfort level than standing and sitting postures.

This outcome may occur because kneeling is an unstable posture, with the knees mainly

supporting body weight. It is also presumed that the high discomfort level for kneeling

with fully flexed knees resulted from fully contracted muscles in the thigh and shank

regions that restricted blood flow, resulting in the participant feeling numbness in the leg

region.

Most standing postures with variable heel distances included while tiptoeing showed a

higher discomfort level than other standing postures. Unbalanced standing also showed

relatively higher discomfort levels than balanced standing postures. This result impliesthat discomfort from standing postures is affected by supporting conditions rather than

feet position. Participants rated their discomfort for tiptoeing as double that of normal

standing; an outcome that seems attributable to the difficulty of maintaining balance

during tiptoeing.

Two floor sittings with flexed or straight knees showed a higher discomfort level than

sitting on a chair. In these postures it is difficult to maintain lumbar lordosis, which

results in an increased load on the lumbar region. However, being seated on the floor with

crossed legs showed a relatively lower discomfort level compared to other floor sittings.

This result may be explained by the common sitting habits of Korean people. The

discomfort level of the posture may be greater in other populations, such as Westernersnot accustomed to such a restricted posture.

As shown in figure 4, discomfort ratings increased as the knee angle decreased and the

‘balance’ factor moved from balanced to one-foot postures, i.e. the balancing condition

became worse. There was no significant interaction effect between the two factors. This

result implies that there is no synergetic effect of increasing postural discomfort by

simultaneously assuming several leg motions, such as knee flexed and unbalanced

postures.

2.4. Complex trunk postures

Postural stress increases synergistically as the angles of trunk motions increase in complex

trunk postures in which more than two trunk motions were adopted simultaneously (see

Figure 4. Mean discomfort ratings for leg postures. (a) Knee-flexed postures; (b) the

balanced, unbalanced and one-foot postures (*no significant difference at a= 0.05;

**knee angle in degree).




figure 5). Statistically significant interaction effects were found between discomfort

ratings for trunk motions such as flexion, lateral bending and rotation (a= 0.05). The

effect of complex trunk postures on the synergistic increase of discomfort is more

manifest in severe trunk postures than in their moderate postures with smaller joint

angles. Interaction effects between trunk motions were significant only when severe

lateral bending (308) or rotation (908) were included. When only two levels of lateral

bending and rotation were considered, no significant interaction effects were found

between trunk motions.

3. Postural classification

Based on the results of the psychophysical experiments (Experiments 1a, 1b and 1c) andexisting literature, a macro-postural classification system was developed (see table 1). The

postural classification scheme consists of five body parts: arm; trunk; legs; wrist; and

neck. For each body part, postures were classified into three to six categories. These

categories consisted primarily of movements in the sagittal plane, such as flexion-

extension. This procedure enhances the applicability of the classification scheme by

improving ease of observation. For complex postures that involve more than two degrees

of freedom in the neck, trunk and legs, additional categories with motion in other planes

are provided, such as lateral bending, rotation and unbalance or awkwardness. Complex

postures can be recorded and assessed by combining the categories. For example, a

moderately bent trunk with lateral bending and rotation can be recorded as acombination of ‘moderate flexion’ and ‘lateral bending/rotation’.

For each classified posture, a discomfort score was assigned based on the ratio of

perceived discomfort for a certain posture to that for a neutral posture. The neutral

posture was presented in the preliminary classification of upper-body and leg postures.

Therefore, the discomfort score has ratio scale characteristics. The score ranges from 0.5

for sitting to 8 for a severely elevated arm.

A discomfort score for a complex posture such as a flexed and laterally bent trunk is

obtained by adding the discomfort score of the adjusting category to that of simple

postures. For example, the discomfort score for a moderately flexed and rotated trunk

can be calculated by adding the discomfort scores for moderate trunk flexion (4), lateral

bending and rotation ( + 5) and the adjusting discomfort score for the complex posture

(+1), i.e. 4 + 5 + 1=10.

Figure 5. Mean discomfort ratings for complex trunk postures. (a) Rotation and flexion

postures; (b) lateral bending and rotation postures.




This additive method is adopted based on the results of Experiments 1b and 1c. In

Experiment 1c, a synergistic increase of discomfort for complex trunk postures was

identified. Relative discomfort of a complex trunk posture to the neutral posture was

approximately the sum of relative discomfort for the included postures (Lee et al . 2003).

In Experiment 1b, no significant interaction effect was found between unbalanced leg

postures and knee flexion angle. The relative discomfort for unbalanced or awkward

Table 1. Postural classification scheme and the discomfort scores for classified postures

Body

part Category Code

Range

(8)

Discomfort

score

Arm* Neutral N (1) 0 – 45 (F), 0 –

20(E)

1

ModerateElevation

ME (2) 45 – 90 3

Severe Elevation SE (3) 90 – 135 5

Extreme

Elevation

EE (4) 4 135 8

Extension E (5) 4 20 5

Trunk Neutral N (1) 0 – 30 (F), 0 – 10

(E)

1

Moderate

Flexion

MF (2) 30 – 60 4

Severe Flexion SF (3) 60 – 90 7


Lateral Bending/Rotation** LBR (’) 4 10 (LB) 425(R) + 5 ( + 1)

Legs Standing STD (1) 0 – 30 1

Moderate knee

flexion

MKF (2) 30 – 60 2

Severe knee

flexion

SKF (3) 60 – 90 3

Squatting SQ (4) 4 90 3

Sitting ST (5) 0.5

Kneeling KNL (6) 2

Unbalance or

Awkward**

UA (’) + 1

Wrist* Neutral N (1) 0 – 25 (F, E) 1

Flexion F (2) 4 25 3Extension E (3) 4 25 3

Neck Neutral N (1) 0 – 20 (F), 0 – 25

(E)

1

Moderate

Flexion

MF (2) 20 – 45 2

Severe Flexion SF (3) 4 45 4


Lateral Bending/

Rotation**

LBR (’) 4 20 + 2 ( + 1)

*Discomfort scores for two wrists or arms are separately assessed and summed together. When two wrists

or arms are positioned in the neutral range, the discomfort score is 1.**Adjusting factors: When these postures are adopted with other joint motions simultaneously, the

discomfort score for the complex posture is obtained by adding two scores. In the neck and trunk, an

additional discomfort score of 1 is added to it when either flexion or extension is adopted simultaneously

with LBR.




postures increased approximately by 1. Therefore, the adjusting factor of discomfort by

unbalance or awkwardness was set to 1 (Chung et al . 2003a).

4. Whole body postural stress prediction

A posture is determined by a combination of body joint motions such as wrist, elbow,shoulder, neck, lower back, knee and ankle. Hence, all body joint motions affect the

whole-body postural stresses. However, how each joint motion affects the whole-body

postural stress is complex and is not yet completely understood. Therefore, many existing

posture evaluation methods adopt a qualitative procedure based mainly on expert

opinion to combine each body joint motion stress into a stress level for the whole body

posture. In this study, the relationship between body joint motions and whole body

postural stresses was established for the representative working postures of automobile

assembly tasks.

In Experiment 2, 19 healthy male subjects rated their perceived discomfort for 42

different postures that were frequently observed during automobile assembly tasks. The

mean age, stature and weight of the subjects were 22.6 ( + 1.1) years, 173.0 (+ 3.5) cm

and 64.4 (+ 4.4) kg, respectively. The experimental protocol of Experiment 2 was the

same as that adopted in Experiment 1.

In selecting the postures to be evaluated in the experiment, the postural characteristics

of automobile assembly tasks were taken into account (Kim et al . 1998). The working

postures in the automobile assembly line vary depending on the assembled part of the

automobile. When performing the tasks inside or beneath the automobile frame, workers

often elevate their arms above shoulder level and extend their neck and trunk to work

over the head. Inside the car or engine area, squatting postures are assumed with a

severely flexed neck. With regard to the operators’ trunk postures, many workers often

adopt complex postures involving more than two simple trunk postures, such as flexion,extension, lateral bending and rotation. Extension of wrist occurs frequently when using

pneumatic hand tools.

A multiple linear regression analysis was performed to investigate the relationship

between whole-body discomfort ratings and joint discomfort scores. In the multiple-

linear regression model, five independent variables (discomfort scores for shoulders,

trunk, legs, wrists and neck) and one dependent variable, whole-body discomfort rating,

were considered. The result showed that the model was statistically significant ( p5 0.01)

with the coefficient of determination (R2) of 0.71 (see table 2). Tests for the null

hypothesis, i.e. H0: the slope parameter is 0, showed that four parameters (shoulders,

trunk, legs and neck) were significantly larger than 0 ( p5 0.01), thus rejecting the nullhypothesis; whereas, the parameter for wrist is not significantly larger than 0 ( p4 0.05).

From the regression result, it is presumed that a linear relationship exists between the

whole-body discomfort ratings and the joint discomfort scores. The variance of the

whole-body discomfort rating was explained as much as 71% by adopting the multiple

linear model. The coefficient of determination of 0.71 is high enough to accept the model

as an explanation for the relationship between whole-body discomfort ratings and the

joint discomfort scores.

The estimated coefficients of the independent variables were all positive, indicating that

the whole-body discomfort rating increases as the joint discomfort scores increase. The

legs have the highest coefficient value (5.82), followed by the neck (3.03), shoulders (2.27),

trunk (1.85) and wrists (1.09). However, it should be noted that independent variables

had different ranges of the discomfort score. The maximum discomfort scores for each




joint were as follows: shoulders (16), trunk (13), legs (4), wrists (6) and neck (7).

Therefore, the estimated coefficient values should be normalized by multiplying the

maximum discomfort values of each joint for comparison. Table 3 presents the estimated

and normalized coefficients for the independent variables. The shoulders have the highest

value of normalized coefficient, followed by the trunk, legs, neck and wrists. The trunk,

legs and neck have similar coefficient values. It can be concluded from the results that theshoulder posture played the most important role in determining the whole-body postural

discomfort levels, while the wrist postures were not critical in determining the whole-body

postural discomfort level.

5. Postural load assessment system

The posture evaluation method developed in this study was implemented as a computer

software program (see figure 6). The system was designed to automate the procedures for

the analysis of the postures, except for observing the postures and recording them

according to the postural classification. The user observes and records the workingpostures using automatically paused motion pictures that are displayed on the window in

the system. The motion pictures can be recorded by a digital camcorder directly at the

worksite or transformed from the video in analogue form using an MPEG computer

system. When starting the observation, the user enters the location of the movie files,

along with some information about the work. The observer can also record postures in

other ways such as direct observation at the worksite, indirect observation through a

video on another monitor and from pictures or image files.

This system enables the user to observe working postures continuously or

intermittently. For intermittent observation, the player pauses the movie file auto-

matically so that the user can observe the working postures regularly. The user can set the

sampling interval. Using continuous observation, the user can record working postures in

an event-driven manner, controlling the play of the movie file manually.

Table 2. Estimated parameter values in the regression analysis

Variable Parameter Estimate Standard Error T p

Intercept 6.32 6.02 1.05 0.3006

Shoulders 2.30 0.42 5.48 0.0001

Trunk 1.90 0.45 4.26 0.0001

Legs 5.86 1.67 3.50 0.0012Wrists 1.05 0.70 1.49 0.1440

Neck 3.17 0.92 3.43 0.0015

Table 3. Normalized coefficients for the independent variables

Independent variables Estimated coefficient Maximum discomfort

scores

Normalized coefficients

Shoulders 2.30 16 36.79

Trunk 1.90 13 24.69

Legs 5.86 4 23.45Wrists 1.05 6 6.28

Neck 3.17 7 22.18




After the postures are recorded, the system analyses the recorded postures. The

frequencies, temporal changes and durations of postures at each joint are documented

and the predicted workload level of each recorded posture is calculated. A very useful

characteristic of the system is that the user can retrieve and view the image of the

corresponding posture as a result of the analysis. For example, the image of the

posture found to have the highest workload level can be shown by clicking the bar

representing the posture on the graph of the workload level. The user can easily

understand the results of the analysis simply by viewing the postures together. This

system can enhance the applicability of working posture analysis by safety managers

in the field.

6. Conclusions

In this study, a practical methodology for evaluating postural stresses is proposed based

on perceived discomfort. The methodology consists of two parts: (1) a macro-postural

classification scheme with body-joint discomfort scores; and (2) a prediction model for

whole-body postural stresses. A working posture can be recorded using the postural

classification scheme and the whole-body postural stress for the particular working

posture can be evaluated quantitatively using the proposed prediction model. The

prediction model was developed and investigated in particular for working postures

frequently found in automobile assembly jobs.In the macro-postural classification, each joint motion was classified according to the

perceived discomfort. The classification scheme included five body parts: wrist; shoulder;

neck; trunk; and legs. The body-joint discomfort score of each classified posture was

determined to represent the stress level of the posture relative to the neutral posture. The

discomfort scores ranged from 0.5 for sitting on a chair to 17 for severely flexed (or

extended) trunk laterally bent and rotated. It is possible to directly compare the stress

levels of the postures of different joints, because the discomfort score was designed as a

ratio scale with the same reference.

Forty-two representative working postures of automobile assembly tasks were

evaluated using the experimental protocol previously employed in evaluating body-joint

motions. Based on the results of the experiment, the relationship between body-joint

motions and whole-body postural discomfort was investigated. Postural load was

Figure 6. Computerized postural stress evaluation method.




strongly associated with the combination of non-neutral joint postures. The more joints

involved in a severely non-neutral position, the higher the level of whole-body postural

discomfort imposed. The relationship between body-joint motions and whole-body

postural stresses was examined using linear regression analysis. The analysis showed that

the linear model explained the relationship well. Using regression analysis, the shoulder

was found to be the most affecting factor for whole-body postural stresses, while the wristwas the least affecting factor. However, there should be caution over generalizing the

relationship, since it was obtained from an experiment limited to representative working

postures of automobile assembly tasks.

The proposed postural stress evaluation model was computerized to automate the

analysis of postures as conveniently as possible. The user is able analyse the postural

stresses by simply observing the postures and coding them according to the classification

system. Since the analysis results are closely associated with the images of the

corresponding postures, it is feasible for the user to understand the results and use

them to improve the work method in practical situations.

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