PHYSICAL TASKS:ERGONOMICS DESIGN TO REDUCE WUEDs

ERGONOMICS DESIGN TO REDUCE WUEDs

In order to reduce the extent of work-related musculoskeletal injuries, progress in four methodologic areas is expected (NIOSH 1986):

1. Identifying accurately the biomechanical hazards

2. Developing effective health-promotion and hazard-control interventions

3. Changing management concepts and operational policies with respect to expected work per- formance

4. Devising strategies for disseminating knowledge on control technology and promoting their application through incentives

From the occupational safety and health perspective, the current state of ergonomics knowledge allows for management of musculoskeletal disorders in order to minimize human suffering, potential for disability, and the related workers’ compensation costs. Ergonomics can help to:

1. Identify working conditions under which musculoskeletal disorders might occur

2. Develop engineering design measures aimed at elimination or reduction of the known job risk factors

3. Identify the affected worker population and target it for early medical and work intervention efforts

The musculoskeletal disorders-related job risk factors, which often overlap, typically involve a combination of poorly designed work methods, workstations, and hand tools and high production demands. Furthermore, while perfect solutions are rarely available, the job redesign decisions may often require some design trade-offs (Putz-Anderson 1992). In view of the above, the ergonomic intervention should allow:

1. Performing a thorough job analysis to determine the nature of specific problems

2. Evaluating and selecting the most appropriate intervention(s)

3. Developing and applying conservative treatment (implementing the intervention), on a limited scale if possible

4. Monitoring progress

5. Adjust or refining the intervention as needed

Quantitative Models for Development of WUEDs

It is generally recognized that force, repetition, posture, recovery time, duration of exposure, static muscular work, use of the hand as a tool, and type of grasp are important factors in the causation of WUEDs (Armstrong et al. 1987; Keyserling et al. 1993). Additional job factors that may increase the risk of WUEDs, in combination with the other factors, include cold temperature, use of gloves, and use of vibrating tools. Given the above knowledge, even if limited and in need of more com- prehensive validation, it is currently possible to develop quantitative methodologies for ergonomics practitioners in order to discriminate between safe and hazardous jobs in terms of workers being at increased risk of developing the WUEDs. Such models are described below.

Semiquantitative Job-Analysis Methodology for Wrist / Hand Disorders

Moore and Garg (1995) developed a semiquantitative job analysis methodology (SJAM) for identi- fying industrial jobs associated with distal upper-extremity (wrist / hand) disorders. An existing body of knowledge and theory of the physiology, biomechanics, and epidemiology of distal upper-extremity disorders was used for that purpose. The proposed methodology involves the measurement or esti- mation of six task variables:

1. Intensity of exertion

2. Duration of exertion per cycle

3. Efforts per minute

4. Wrist posture

5. Speed of exertion

6. Duration of task per day

An ordinal rating is assigned for each of the variables according to the exposure data. The pro- posed strain index is the product of these six multipliers assigned to each of the variables.

The strain index methodology aims to discriminate between jobs that expose workers to risk factors (task variables) that cause WUEDs and jobs that do not. However, the strain index is not designed to identify jobs associated with an increased risk of any single specific disorder. It is anticipated that jobs identified as in the high-risk category by the strain index will exhibit higher levels of WUEDs among workers who currently perform or historically performed those jobs that are believed to be hazardous. Large-scale studies are needed to validate and update the proposed methodology. The strain index has the following limitations in terms of its application:

1. There are some disorders of the distal upper extremity that should not be predicted by the strain index, such as hand–arm vibration syndrome (HAVS) and hypothenar hammer syndrome.

2. The strain index has not been developed to predict increased risk for distal upper-extremity disorders to uncertain etiology or relationship to work. Examples include ganglion cysts, os- teoarthritis, avascular necrosis of carpal bones, and ulnar nerve entrapment at the elbow.

3. The strain index has not been developed to predict disorders outside of the distal upper ex- tremity, such as disorders of the shoulder, shoulder girdle, neck, or back.

The following major principles have been derived from the physiological model of localized muscle fatigue:

1. The primary task variables are intensity of exertion, duration of exertion, and duration of recovery.

2. Intensity of exertion refers to the force required to perform a task one time. It is characterized as a percentage of maximal strength.

3. Duration of exertion describes how long an exertion is applied. The sum of duration of exertion and duration of recovery is the cycle time of one exertional cycle.

4. Wrist posture, type of grasp, and speed of work are considered via their effects of maximal strength.

5. The relationship between strain on the body (endurance time) and intensity of exertion is nonlinear.

The following are the major principles derived from the epidemiological literature:

1. The primary task variable associated with an increased prevalence or incidence of distal upper- extremity disorders are intensity of exertion (force), repetition rate, and percentage of recovery time per cycle.

2. Intensity of exertion was the most important task variable in two of the three studies explicitly mentioned. The majority (or all) of the morbidity was related to disorders of the muscle– tendon unit. The third study, which considered only CTS, found that repetition was more important than forcefulness (Silverstein et al. 1987).

3. Wrist posture may not be an independent risk factor. It may contribute to an increased incidence of distal upper-extremity disorders when combined with intensity of exertion.

4. The roles of other task variables have not been clearly established epidemiologically; therefore, one has to rely on biomechanical and physiological principles to explain their relationship to upper-extremity disorders, if any.

Moore and Garg (1994) compared exposure factors for jobs associated with WUEDs to jobs without prevalence of such disorders. They found that the intensity of exertion, estimated as a per- centage of maximal strength and adjusted for wrist posture and speed of work, was the major dis- criminating factor. The relationship between the incidence rate for distal upper-extremity disorder and the job risk factors was defined as follows:

The proposed concept of the strain index is a semiquantitative job analysis methodology that results in a numerical score that is believed to correlate with the risk of developing distal upper- extremity disorders. The SI score represents the product of six multipliers that correspond to six task variables. These variables:

Intensity of exertion, the most critical variable of SI, is an estimate of the force requirements of a task and is defined as the percentage of maximum strength required to perform the task once. As such, the intensity of exertion is related to physiological stress (percentage of maximal strength) and biomechanical stresses (tensile load) on the muscle–tendon units of the distal upper extremity. The intensity of exertion is estimated by an observer using verbal descriptors and assigned corresponding rating values (1, 2, 3, 4, or 5). The multiplier values are defined based on the rating score raised to a power of 1.6 in order to reflect the nonlinear nature of the relationship between intensity of exertion and manifestations of strain according to the psychophysical theory. The multipliers for other task variables are modifiers to the intensity of exertion multiplier.

Duration of exertion is defined as the percentage of time an exertion is applied per cycle. The terms cycle and cycle time refer to the exertional cycle and average exertional cycle time, respectively. Duration of recovery per cycle is equal to the exertional cycle time minus the duration of exertion per cycle. The duration of exertion is the average duration of exertion per exertional cycle (calculated by dividing all durations of a series of exertions by the number of observed exertions). The percentage

duration of exertion is calculated by dividing the average duration of exertion per cycle by the average exertional cycle time, then multiplying the result by 100. (See equation below.) The calculated per- centage duration of exertion is compared to the ranges and assigned the appropriate rating. The corresponding multipliers are identified using Table 23.

Efforts per minute is the number of exertions per minute (i.e., repetitiveness) and is synonymous with frequency. Efforts per minute are measured by counting the number of exertions that occur during a representative observation period (as described for determining the average exertional cycle time). The measured results are compared to the ranges shown in Table 23 and given the correspond- ing ratings. The multipliers are defined in Table 24.

Posture refers to the anatomical position of the wrist or hand relative to neutral position and is rated qualitatively using verbal anchors. As shown in Table 23, posture has four relevant ratings. Postures that are ‘‘very good’’ or ‘‘good’’ are essentially neutral and have multipliers of 1.0. Hand or wrist postures progressively deviate beyond the neutral range to extremes, graded as ‘‘fair,’’ ‘‘bad,’’ and ‘‘very bad.’’

Speed of work estimates perceived pace of the task or job and is subjectively estimated by a job analyst or ergonomics team. Once a verbal anchor is selected, a rating is assigned.

Duration of task per day is defined as a total time that a task is performed per day. As such, this variable reflects the beneficial effects of task diversity such as job rotation and the adverse effects of prolonged activity such as overtime. Duration of task per day is measured in hours and assigned a rating according to Table 23.

Application of the strain index involves five steps:

1. Collecting data

2. Assigning rating values

3. Determining multipliers

4. Calculating the SI score

5. Interpreting the results

The values of intensity of exertion, hand–wrist posture, and speed of work are estimated using the verbal descriptors in Table 23. The values of percentage duration of exertion per cycle, efforts per minute, and duration per day are based on measurements and counts. Theses values are then compared to the appropriate column in Table 24 and assigned a rating. The calculations of SI are shown in Table 25.

Psychophysical Models: The Maximum Acceptable Wrist Torque Snook et al. (1995) used the psychophysical approach to determine the maximum acceptable forces for various types and frequencies for repetitive wrist motion, grips, and repetition rates that would not result in significant changes in wrist strength, tactile sensitivity, or number of symptoms reported by the female subjects. Three levels of wrist motion were used:

1. Flexion motion with a power grip

2. Flexion motion with a pinch grip

3. Extension motion with a power grip

The dependent variables were maximum acceptable wrist torque, maximum isometric wrist strength, tactile sensitivity, and symptoms. The maximum acceptable wrist torque (MAWT) was defined as the number of Newton meters of resistance set in the brake by the participants (averaged and recorded every minute). The data for maximum acceptable wrist torques for the two-days-per- week exposure were used to estimate the maximum acceptable torques for different repetitions of wrist flexion (power grip) and different percentages of the population. This was done by using the adjusted means and coefficients of variation from the two-days-per-week exposure. The original torque values were converted into forces by dividing each torque by the average length of the handle lever (0.081 m).

The estimated values for the maximum acceptable forces for female wrist flexion (power grip) are shown in Table 26. Similarily, the estimated maximum acceptable forces were developed for wrist flexion (pinch grip, see Table 27) and wrist extension (power grip, see Table 28). The torques were converted into forces by dividing by 0.081 m for the power grip and 0.123m for the pinch grip. Snook et al. (1995) note that the estimated values of the maximum acceptable wrist torque do not apply to any other tasks and wrist positions than those that were used in the study.