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Observer, manual single-frame video, and automated computer vision measures of the Hand Activity Level (HAL) were compared. HAL can be measured three ways: (1) observer rating (HAL O ), (2) calculated from single-frame multimedia video task analysis for measuring frequency (F) and duty cycle (D) (HAL F ), or (3) from automated computer vision (HAL C ). This study analysed videos collected from three prospective cohort studies to ascertain HAL O , HAL F , and HAL C for 419 industrial videos. Although the differences for the three methods were relatively small on average (<1), they were statistically significant ( p < .001). A difference between the HAL C and HAL F ratings within ±1 point on the HAL scale was the most consistent, where more than two thirds (68%) of all the cases were within that range and had a linear regression through the mean coefficient of 1.03 ( R 2 The ACGIH Hand Activity Level (HAL) was obtained for 419 industrial tasks using three methods: observation, calculated using single-frame video analysis and computer vision. The computer vision methodology produced results that were comparable to single-frame video analysis.Practitioner summary: The ACGIH Hand Activity Level (HAL) was obtained for 419 industrial tasks using three methods: observation, calculated using single-frame video analysis and computer vision. The computer vision methodology produced results that were comparable to single-frame video analysis.

The primary objectives of this study were to describe and analyze the hand force exertion patterns of experienced nursing home nurses and nursing students during dynamic medicine cart pushing tasks in Initial, Sustained, Turning, and Stopping motion phases. A 2 × 2 × 2 factorial experiment was conducted with 22 participants to estimate the effects of lane congestion, precision cart control, and floor surface on horizontal hand forces. Root mean squared (RMS) lane deviation patterns were also described to provide an indicator of cart handling difficulty across the different study conditions. Descriptive statistics revealed that nurses exerted greater mean hand force (10%) and made more (12%) lane deviation than students and that the highest two-hand forces of 147N were measured in the Turning phase on carpet. Strong correlations between work experience group, body mass, and BMI required that force data for nurses and students be collapsed in analytical models where no group differences existed. Predicted pushing forces on carpeted floor surface were significantly greater than on tile in Initial (14N), Sustained (14N) and Turning (18N), except in stopping where pulling forces were 37N lower. High lane congestion predicted significant peak force increases of 4N and 7N in Sustained and Turning, respectively, but decreased by 20N in Initial. High precision control led to significant decreases in two-hand forces that ranged from 4 to 20N across motion phases. Complex interactions among the experimental factors suggest that work environment (lane congestion and floor surface) and work demands (precision control) should be included in the evaluation of pushing tasks and considered prior to making renovations to nursing home environments., (Copyright © 2012. Published by Elsevier Ltd.)

Applications of a new model for predicting power threaded-fastener-driving tool operator response and capacity to react against impulsive torque reaction forces are explored for use in tool selection and ergonomic workplace design. The model is based on a mechanical analog of the human operator, with parameters dependent on work location (horizontal and vertical distances); work orientation (horizontal and vertical); and tool shape (in-line, pistol grip, and right angle); and is stratified by gender. This model enables prediction of group means and variances of handle displacement and force for a given tool configuration. Response percentiles can be ascertained for specific tool operations. For example, a sample pistol grip nutrunner used on a horizontal surface at 30 cm in front of the ankles and 140 cm above the floor results in a predicted mean handle reaction displacement of 39.0 (SD=28.1) mm for males. Consequently 63%of the male users exceed a 30 mm handle displacement limit. When a right angle tool of similar torque output is used instead, the model predicted that only 4.6%of the male tool users exceed a 30 mm handle displacement. A method is described for interpolating individual subject model parameters at any given work location using linear combinations in relation to the range of modeled factors. Additional examples pertinent to ergonomic workstation design and tool selection are provided to demonstrate how the model can be used to aid tool selection and workstation design.

The human operator is modelled as a single-degree-of-freedom dynamic mechanical system for predicting the response to impulsive torque reaction forces produced by rotating spindle power hand tools such as nutrunners or screwdrivers. The model uses mass, spring and damping elements to represent the standing operator supporting the tool in the hand. It was hypothesized that these mechanical elements are affected by work location and vary among individuals. These elements were ascertained by measuring the resulting frequency and amplitude of a freely oscillating defined mechanical system when externally loaded using maximal effort to oppose its motion. Twenty-five subjects (13 female, 12 male) participated in the full factorial experiment that measured the effects of gender, vertical and horizontal work location for various tool shapes (in-line, pistol, right angle), and orientations (horizontal and vertical). The mean operator stiffness decreased from 1721 to 1195 N/m when the horizontal work location increased from 30 to 90 cm in front of the ankles for a pistol-grip handle used on a vertical surface. Males had greater mass moment of inertia of (0.0099 kg m2) than females (0.0072 kg m2) for an in-line handle used on a horizontal surface. Internal validation by independently measuring apparatus torque found that the model satisfactorily explained the measured operator dynamics with an average error of 2.86%. Group variance reflects the range of operator capacities to react against power hand tool generated forces for the sample group and therefore it may also be useful for understanding the range of capacities among a group of operators performing similar tasks.

This study uses a previously developed single-degree-of-freedom mechanical model to predict the power hand tool operator handle kinematic response to impulsive reaction forces (Lin, 2001). The model considers the human operator as a lumped parameter passive mechanical system, consisting of stiffness, mass moment of inertia, and viscous damping elements. Six power nutrunners were operated by 9 volunteers (3 men, 6 women) in the laboratory, and corresponding handle kinematics were compared against model predictions. A full-factorial experiment considered torque buildup time and work location. Normalized forearm flexor EMG was measured to quantify muscle exertions and used to proportionally adjust the stiffness parameter. The measured handle displacement for actual tool operation strongly correlated to the model predictions (R = .98) for all handle configurations. The overall model prediction error was 3% for predicting tool handle responses to impulsive reaction forces for various tool and workstation parameters. This model should make it possible for designers to identify conditions that minimize the torque reaction experienced by power hand tool operators.

The purpose of this experiment was to quantify the natural angle between the hand and a handle, and to investigate three design factors: handle rotation, handle tilt and between-handle width on the natural angle as well as resultant wrist radial/ulnar deviation (‘RUD’) for pushing tasks. Photographs taken of the right upper limb of 31 participants (14 women and 17 men) performing maximal seated push exertions on different handles were analysed. Natural hand/handle angle and RUD were assessed. It was found that all of the three design factors significantly affected natural handle angle and wrist RUD, but participant gender did not. The natural angle between the hand and the cylindrical handle was 65 ± 7°. Wrist deviation was reduced for handles that were rotated 0° (horizontal) and at the narrow width (31 cm). Handles that were tilted forward 15° reduced radial deviation consistently (12–13°) across handle conditions. Practitioner summary:Manual materials handling (MMH) tasks involving pushing have been related to increased risk of musculoskeletal injury. This study shows that handle orientation influences hand and wrist posture during pushing, and suggests that the design of push handles on carts and other MMH aids can be improved by adjusting their orientation to fit the natural interface between the hand and handle. [ABSTRACT FROM PUBLISHER]

Repetitive use of hand-held power tools is associated with work-related upper extremity musculoskeletal disorders. Using a pneumatic nutrunner, 21 men completed twelve 360 repetitive fastener-driving sessions on three joints (hard, soft and control) at slow and fast pace, and two different work:rest patterns. Handgrip force and perceived exertions were collected throughout each session. For the control joint, the mean grip force exerted was 39.6% of maximum voluntary exertion (MVE) whereas during hard and soft joint sessions it was 48.9% MVE and 56.9% MVE, respectively. Throughout each session, the grip force decreased, more while operating soft and hard joints as compared with the control joint (regression slope: −0.022 and −0.023, compared with −0.007 N/drive, respectively), suggesting considerable upper extremity muscular effort by participants during torque buildup. Fast work pace resulted in higher average grip forces by participants but a greater decrease in the force as the session progressed. Providing rest breaks reduced perceived exertions. The findings gain additional knowledge for assembly task design to possibly reduce the hand/arm injury risks for the operator. Practitioner Summary: Powered hand tools are widely used in assembly and manufacturing industries. However, the nature of their repetitive use on human operator biomechanical and perceptual responses is not fully understood. This study examined work-related risk factors such as joint torque, pace and work:rest ratios on powered hand tool performance. [ABSTRACT FROM AUTHOR]

The study considers the dynamic nature of the human power handtool operator as a single degree-of-freedom mechanical torsional system. The hand and arm are, therefore, represented as a single mass, spring and damper. The values of these mechanical elements are dependent on the posture used and operator. The apparatus used to quantify these elements measured the free vibration frequency and amplitude decay of a known system due to the external loading of the hand and arm. Twenty-five subjects participated in the investigation. A full factorial experiment tested the effects on the three passive elements in the model when operators exerted maximum effort for gender, horizontal distance (30, 60, 90 cm), and vertical distance (55, 93, 142 190 cm) from the ankles to the handle. The results show that the spring element stiffness and mass moment of inertia changed by 20.6 and 44.5% respectively with vertical location (p [sup <] 0.01), and 23.6 and 41.2% respectively with horizontal location (p [sup <] 0.01). Mass moment of inertia and viscous damping for males were 31.1 and 38.5% respectively greater than for females (p [sup <] 0.01). Tool handle displacement and hand force during torque buildup can, therefore, be predicted based on this model for different tool and workplace parameters. The biomechanical model was validated by recalling five subjects and having them operate a power handtool for varying horizontal distances (30, 60, 90 cm), vertical distances (55, 93, 142 cm), and two torque build-up times (70, 200 ms). Tool reaction displacement was measured using a 3D-motion analysis system. The predictions were closely correlated with these measurements (R = 0.88), although the model underpredicted the response by 27%. This was anticipated since it was unlikely that operators used maximal exertions for operating the tools. [ABSTRACT FROM AUTHOR]