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production process in industrial sites. Most postural classification schemes developed are the observation
methods. These include the Posture Targeting (Corlett et al., 1979), OWAS (Karhu et al., 1977), PATH
(Buchholz et al., 1996), and RULA (McAtamney and Corlett, 1993).
Depending upon the grouping methods for joint motions involved in a classified posture, Genaidy
et al. (1994) categorized the postural classification approaches used in observational techniques into:
macropostural, micropostural, and postural-work activity classifications. The macropostural classifi-
cation groups more than one non-neutral posture around a joint into one category, while the macro-
postural classification is more detailed than the previous method. The postural -work activity
classification combines postures and work activities (Genaidy et al., 1994).
Although the existing methods have proved useful for quantification of postural stresses in field
studies, and contributed to preventing work-related MSDs, they have many disadvantages. First,
many of the observational classification schemes are not based on experimental data. Second, the exist-
ing methods have been developed for specific application purposes, and, consequently, are not generic in
many respects. Third, many methods deal with only a few representative joint motions, as they focus on
specific joint motions frequently linked to MSDs. Another problem is that only a few schemes (including
OWAS and RULA) utilize specific evaluation criteria for the classified postures, which provide infor-
mation on any corrective actions to be undertaken for reducing postural burden at work. In addition,
the evaluation criteria provided by RULA and OWAS were not based on experimental results, but rather
relied on the rankings provided by ergonomists and occupational physiotherapists using biomechanical
and muscle function criteria (McAtamney and Corlett, 1993), or the subjective rankings provided by
experienced steel workers (Karhu et al., 1977), respectively.
43.2 Objectives
To complement the restrictions of the existing methods, this chapter presents an observational
and macropostural technique for postural loading on the upper body assessment (LUBA). The
method is based on experimental data for perceived discomfort, expressed as numerical ratio scores
for a set of joint motions, including the hand, arm, neck, and back. This technique is applied to
the seated posture or standing posture with the lower limb well supported in an evenly balanced
posture.
Perceived discomforts were gathered for varying postures of five joints in the upper body (Table 43.1),
which included almost every possible joint motion occurring in the sitting and standing postures. Per-
ceived discomforts were measured at five levels of range of joint motion (ROM) in each motion: 0
(neutral), 25, 50, 75, and 100% of ROM, respectively. The magnitude estimation was adopted for measur-
ing discomfort scores. It has the advantage of providing data with the characteristics of the interval or
ratio scale that can be applied to quantitative statistical techniques.
43.3 LUBA
43.3.1 Relative Discomfort Scores by Joint Motions
Each joint motion class was assigned a numerical relative discomfort score on the basis of discomfort
value for the neutral position of elbow flexion, which was the least stressful of all the joint motions inves-
tigated. A relative discomfort score of 1.0 was assigned to the neutral position of elbow flexion, with a
higher number indicating that a given joint motion class is more stressful. The relative discomfort
score is the ratio scale that could be applied to four arithmetic rules such as addition, subtraction, mul-
tiplication, and division. In other words, the back flexion of
with the relative discomfort score of 10
has ten times the discomfort magnitude of the elbow flexion of 0 to 45
60
8
.
8
, the relative discomfort score of
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