Effectiveness of workplace interventions in the prevention of upper extremity musculoskeletal disorders and symptoms: an update of the evidence.

The burden of disabling musculoskeletal pain and injuries (musculoskeletal disorders, MSDs) arising from work-related causes in many workplaces remains substantial. There is little consensus on the most appropriate interventions for MSDs. Our objective was to update a systematic review of workplace-based interventions for preventing and managing upper extremity MSD (UEMSD). We followed a systematic review process developed by the Institute for Work & Health and an adapted best evidence synthesis. 6 electronic databases were searched (January 2008 until April 2013 inclusive) yielding 9909 non-duplicate references. 26 high-quality and medium-quality studies relevant to our research question were combined with 35 from the original review to synthesise the evidence on 30 different intervention categories. There was strong evidence for one intervention category, resistance training, leading to the recommendation: Implementing a workplace-based resistance training exercise programme can help prevent and manage UEMSD and symptoms. The synthesis also revealed moderate evidence for stretching programmes, mouse use feedback and forearm supports in preventing UEMSD or symptoms. There was also moderate evidence for no benefit for EMG biofeedback, job stress management training, and office workstation adjustment for UEMSD and symptoms. Messages are proposed for both these and other intervention categories.

The effects of workplace stressors on muscle activity in the neck-shoulder and forearm muscles during computer work: a systematic review and meta-analysis.

Workplace stressors have been indicated to play a role in the development of neck and upper extremity pain possibly through an increase of sustained (low-level) muscle activity. The aim of this review was to study the effects of workplace stressors on muscle activity in the neck-shoulder and forearm muscles. An additional aim was to find out whether the muscles of the neck-shoulder and the forearm are affected differently by different types of workplace stressors. A systematic literature search was conducted on studies investigating the relation between simulated or realistic workplace stressors and neck-shoulder and forearm muscle activity. For studies meeting the inclusion criteria, a risk of bias assessment was performed and data were extracted for synthesis. Results were pooled when possible and otherwise described. Twenty-eight articles met the inclusion criteria, reporting data of 25 different studies. Except for one field study, all included studies were laboratory studies. Data of 19 articles could be included in the meta-analysis and revealed a statistically significant, medium increase in neck-shoulder and forearm muscle activity as a result of workplace stressors. In subgroup analyses, we found an equal effect of different stressor types (i.e. cognitive/emotional stress, work pace, and precision) on muscle activity in both body regions. In conclusion, simulated workplace stressors result in an increase in neck-shoulder and forearm muscle activity. No indications were found that different types of stressors affect these body regions differently. These conclusions are fully based on laboratory studies, since field studies on this topic are currently lacking.

Observed differences in upper extremity forces, muscle efforts, postures, velocities and accelerations across computer activities in a field study of office workers.

This study, a part of the PRedicting Occupational biomechanics in OFfice workers (PROOF) study, investigated whether there are differences in field-measured forces, muscle efforts, postures, velocities and accelerations across computer activities. These parameters were measured continuously for 120 office workers performing their own work for two hours each. There were differences in nearly all forces, muscle efforts, postures, velocities and accelerations across keyboard, mouse and idle activities. Keyboard activities showed a 50% increase in the median right trapezius muscle effort when compared to mouse activities. Median shoulder rotation changed from 25 degrees internal rotation during keyboard use to 15 degrees external rotation during mouse use. Only keyboard use was associated with median ulnar deviations greater than 5 degrees. Idle activities led to the greatest variability observed in all muscle efforts and postures measured. In future studies, measurements of computer activities could be used to provide information on the physical exposures experienced during computer use. Practitioner Summary: Computer users may develop musculoskeletal disorders due to their force, muscle effort, posture and wrist velocity and acceleration exposures during computer use. We report that many physical exposures are different across computer activities. This information may be used to estimate physical exposures based on patterns of computer activities over time.

Validation of a wearable system for 3D ambulatory L5/S1 moment assessment during manual lifting using instrumented shoes and an inertial sensor suit.

This study aimed to evaluate the accuracy of 3D L5/S1 moment estimates from an ambulatory measurement system consisting of a wearable inertial motion capture system (IMC) and instrumented force shoes (FSs), during manual lifting. Reference L5/S1 moments were calculated using an inverse dynamics bottom-up laboratory model (buLABmodel), based on data from a measurement system comprising optical motion capture (OMC) and force plates (FPs). System performance of (1) a bottom-up ambulatory model (buAMBmodel) using lower-body kinematic IMC and FS data, and (2) a top-down ambulatory model (tdAMBmodel) using upper-body kinematic IMC data and hand forces (HFs) were compared. HFs were estimated using full-body kinematic IMC data and FS forces. Eight males and eight females lifted a 10-kg box from different initial vertical/horizontal positions using either a free or an asymmetric lifting style. As a measure of system performance, root-mean-square (RMS) errors were calculated between the reference (buLABmodel) and ambulatory (tdAMBmodel &buAMBmodel) moments. The results showed two times smaller errors for the tdAMBmodel (averaged RMS errors < 20 Nm or 10% of peak extension moment) than for the buAMBmodel (average RMS errors < 40 Nm or 20% of peak extension moment). In conclusion, for ambulatory L5/S1 moment assessment with an IMC + FS system, using a top-down inverse dynamics approach with estimated hand forces is to be preferred over a bottom-up approach.

Work pattern causes bias in self-reported activity duration: a randomised study of mechanisms and implications for exposure assessment and epidemiology.

BACKGROUND: Self-reported activity duration is used to estimate cumulative exposures in epidemiological research. OBJECTIVE: The effects of work pattern, self-reported task dullness (a measure of cognitive task demand), and heart rate ratio and perceived physical exertion (measures of physical task demands) on error in task duration estimation were investigated. METHODS: 24 participants (23-54 years old, 12 males) were randomly assigned to execute three tasks in either a continuous (three periods of 40 continuous minutes, one for each task) or a discontinuous work pattern (40 min tasks each divided into four periods of 4, 8, 12 and 16 min). Heart rate was measured during tasks. After completing the 2 h work session, subjects reported the perceived duration, dullness and physical exertion for each of the three tasks. Multivariate models were fitted to analyse errors and their absolute value to assess the accuracy in task duration estimation and the mediating role of task demands on the observed results. RESULTS: Participants overestimated the time spent shelving boxes (up to 38%) and filing journals (up to 9%), and underestimated the time typing articles (up to -22%). Over- and underestimates and absolute errors were greater in the discontinuous work pattern group. Only the self-reported task dullness mediated the differences in task duration estimation accuracy between work patterns. CONCLUSIONS: Task-related factors can affect self-reported activity duration. Exposure assessment strategies requiring workers to allocate work time to different tasks could result in biased measures of association depending on the demands of the tasks during which the exposure of interest occurs.

Effect of walking surface, late-cueing, physiological characteristics of aging, and gait parameters on turn style preference in healthy, older adults.

Turning while walking is a crucial component of locomotion, often performed on irregular surfaces with little planning time. Turns can be difficult for some older adults due to physiological age-related changes. Two different turning strategies have been identified in the literature. During step turns, which are biomechanically stable, the body rotates about the outside limb, while for spin turns, generally performed with closer foot-to-foot distance, the inside limb is the main pivot point. Turning strategy preferences of older adults under challenging conditions remains unclear. The aim of this study was to determine how turning strategy preference in healthy older adults is modulated by surface features, cueing time, physiological characteristics of aging, and gait parameters. Seventeen healthy older adults (71.5 ±â€¯4.2 years) performed 90° turns for two surfaces (flat, uneven) and two cue conditions (pre-planned, late-cue). Gait parameters were identified from kinematic data. Measures of lower-limb strength, balance, and reaction-time were also recorded. Generalized linear (logistic) regression mixed-effects models examined the effect of (1) surface and cuing, (2) physiological characteristics of ageing, and (3) gait parameters on turn strategy preference. Step turns were preferred when the condition was pre-planned (p < 0.001) (model 1) and when the gait parameters of stride regularity and maximum acceleration decreased (p = 0.010 and p = 0.039, respectively) (model 3). Differences in turn strategy selection under dynamic conditions ought to be evaluated in future fall-risk research and rehabilitation utilizing real-world activity monitoring.

Machine learning algorithms can classify outdoor terrain types during running using accelerometry data.

BACKGROUND: Running is a popular physical activity that benefits health; however, running surface characteristics may influence loading impact and injury risk. Machine learning algorithms could automatically identify running surface from wearable motion sensors to quantify running exposures, and perhaps loading and injury risk for a runner. RESEARCH QUESTION: (1) How accurately can machine learning algorithms identify surface type from three-dimensional accelerometer sensors? (2) Does the sensor count (single or two-sensor setup) affect model accuracy? METHODS: Twenty-nine healthy adults (23.3 ±â€¯3.6 years, 1.8 ±â€¯0.1 m, and 63.6 ±â€¯8.5 kg) participated in this study. Participants ran on three different surfaces (concrete, synthetic, woodchip) while fit with two three-dimensional accelerometers (lower-back and right tibia). Summary features (n = 208) were extracted from the accelerometer signals. Feature-based Gradient Boosting (GB) and signal-based deep learning Convolutional Neural Network (CNN) models were developed. Models were trained on 90% of the data and tested on the remaining 10%. The process was repeated five times, with data randomly shuffled between train-test splits, to quantify model performance variability. RESULTS: All models and configurations achieved greater than 90% average accuracy. The highest performing models were the two-sensor GB and tibia-sensor CNN (average accuracy of 97.0 ±â€¯0.7 and 96.1 ±â€¯2.6%, respectively). SIGNIFICANCE: Machine learning algorithms trained on running data from a single- or dual-sensor accelerometer setup can accurately distinguish between surfaces types. Automatic identification of surfaces encountered during running activities could help runners and coaches better monitor training load, improve performance, and reduce injury rates.

Machine learning algorithms based on signals from a single wearable inertial sensor can detect surface- and age-related differences in walking.

The aim of this study was to investigate if a machine learning algorithm utilizing triaxial accelerometer, gyroscope, and magnetometer data from an inertial motion unit (IMU) could detect surface- and age-related differences in walking. Seventeen older (71.5 ±â€¯4.2 years) and eighteen young (27.0 ±â€¯4.7 years) healthy adults walked over flat and uneven brick surfaces wearing an inertial measurement unit (IMU) over the L5 vertebra. IMU data were binned into smaller data segments using 4-s sliding windows with 1-s step lengths. Ninety percent of the data were used as training inputs and the remaining ten percent were saved for testing. A deep learning network with long short-term memory units was used for training (fully supervised), prediction, and implementation. Four models were trained using the following inputs: all nine channels from every sensor in the IMU (fully trained model), accelerometer signals alone, gyroscope signals alone, and magnetometer signals alone. The fully trained models for surface and age outperformed all other models (area under the receiver operator curve, AUC = 0.97 and 0.96, respectively; p ≤ .045). The fully trained models for surface and age had high accuracy (96.3, 94.7%), precision (96.4, 95.2%), recall (96.3, 94.7%), and f1-score (96.3, 94.6%). These results demonstrate that processing the signals of a single IMU device with machine-learning algorithms enables the detection of surface conditions and age-group status from an individual's walking behavior which, with further learning, may be utilized to facilitate identifying and intervening on fall risk.

Gait adaptations of older adults on an uneven brick surface can be predicted by age-related physiological changes in strength.

BACKGROUND: Outdoor falls in community-dwelling older adults are often triggered by uneven pedestrian walkways. It remains unclear how older adults adapt to uneven surfaces typically encountered in the outdoor built-environment and whether these adaptations are associated to age-related physiological changes. RESEARCH QUESTION: The aims of this study were to (1) compare gait parameters over uneven and flat brick walkways, (2) evaluate the differences between older and young adults for these two surfaces, and (3) assess if physiological characteristics could predict adaptations in older adults. METHODS: Balance, strength, reaction-time, full-body marker positions, and acceleration signals from a trunk-mounted inertial measurement unit were collected in seventeen older (71.5 ±â€¯4.2 years) and eighteen young (27.0 ±â€¯4.7 years) healthy adults to compute lower-limb joint kinematics, spatio-temporal parameters, dynamic stability, and accelerometry-derived metrics (symmetry, consistency, and smoothness). RESULTS: Both groups increased hip flexion at foot-strike, while decreasing ankle dorsiflexion, margin of stability, symmetry, and consistency on the uneven, compared to flat, surface. Older, compared to young, adults showed a larger increase in knee flexion at foot-strike and a larger decrease in smoothness on the uneven surface. Only young adults decreased hip abduction on the uneven surface. Strength, not balance nor reaction-time, was the main predictor of hip abduction in older adults on both surfaces. SIGNIFICANCE: While older adults may be especially vulnerable, uneven surfaces negatively impact gait, irrespective of age, and could represent a risk to all pedestrians.

Continuous ambulatory hand force monitoring during manual materials handling using instrumented force shoes and an inertial motion capture suit.

Hand forces (HFs) are commonly measured during biomechanical assessment of manual materials handling; however, it is often a challenge to directly measure HFs in field studies. Therefore, in a previous study we proposed a HF estimation method based on ground reaction forces (GRFs) and body segment accelerations and tested it with laboratory equipment: GFRs were measured with force plates (FPs) and segment accelerations were measured using optical motion capture (OMC). In the current study, we evaluated the HF estimation method based on an ambulatory measurement system, consisting of inertial motion capture (IMC) and instrumented force shoes (FSs). Sixteen participants lifted and carried a 10-kg crate from ground level while 3D full-body kinematics were measured using OMC and IMC, and 3D GRFs were measured using FPs and FSs. We estimated 3D hand force vectors based on: (1) FP+OMC, (2) FP+IMC and (3) FS+IMC. We calculated the root-mean-square differences (RMSDs) between the estimated HFs to reference HFs calculated based on crate kinematics and the GRFs of a FP that the crate was lifted from. Averaged over subjects and across 3D force directions, the HF RMSD ranged between 10-15N when using the laboratory equipment (FP + OMC), 11-18N when using the IMC instead of OMC data (FP+IMC), and 17-21N when using the FSs in combination with IMC (FS + IMC). This error is regarded acceptable for the assessment of spinal loading during manual lifting, as it would results in less than 5% error in peak moment estimates.

Aging may negatively impact movement smoothness during stair negotiation.

Stairs represent a barrier to safe locomotion for some older adults, potentially leading to the adoption of a cautious gait strategy that may lack fluidity. This strategy may be characterized as unsmooth; however, stair negotiation smoothness has yet to be quantified. The aims of this study were to assess age- and task-related differences in head and body center of mass (COM) acceleration patterns and smoothness during stair negotiation and to determine if smoothness was associated with the timed "Up and Go" (TUG) test of functional movement. Motion data from nineteen older and twenty young adults performing stair ascent, stair descent, and overground straight walking trials were analyzed and used to compute smoothness based on the log-normalized dimensionless jerk (LDJ) and the velocity spectral arc length (SPARC) metrics. The associations between TUG and smoothness measures were evaluated using Pearson's correlation coefficient (r). Stair tasks increased head and body COM acceleration pattern differences across groups, compared to walking (p < 0.05). LDJ smoothness for the head and body COM decreased in older adults during stair descent, compared to young adults (p ≤ 0.015) and worsened with increasing TUG for all tasks (-0.60 ≤ r ≤ -0.43). SPARC smoothness of the head and body COM increased in older adults, regardless of task (p < 0.001), while correlations showed improved SPARC smoothness with increasing TUG for some tasks (0.33 ≤ r ≤ 0.40). The LDJ outperforms SPARC in identifying age-related stair negotiation adaptations and is associated with performance on a clinical test of gait.

Estimating 3D L5/S1 moments and ground reaction forces during trunk bending using a full-body ambulatory inertial motion capture system.

Inertial motion capture (IMC) systems have become increasingly popular for ambulatory movement analysis. However, few studies have attempted to use these measurement techniques to estimate kinetic variables, such as joint moments and ground reaction forces (GRFs). Therefore, we investigated the performance of a full-body ambulatory IMC system in estimating 3D L5/S1 moments and GRFs during symmetric, asymmetric and fast trunk bending, performed by nine male participants. Using an ambulatory IMC system (Xsens/MVN), L5/S1 moments were estimated based on the upper-body segment kinematics using a top-down inverse dynamics analysis, and GRFs were estimated based on full-body segment accelerations. As a reference, a laboratory measurement system was utilized: GRFs were measured with Kistler force plates (FPs), and L5/S1 moments were calculated using a bottom-up inverse dynamics model based on FP data and lower-body kinematics measured with an optical motion capture system (OMC). Correspondence between the OMC+FP and IMC systems was quantified by calculating root-mean-square errors (RMSerrors) of moment/force time series and the interclass correlation (ICC) of the absolute peak moments/forces. Averaged over subjects, L5/S1 moment RMSerrors remained below 10Nm (about 5% of the peak extension moment) and 3D GRF RMSerrors remained below 20N (about 2% of the peak vertical force). ICCs were high for the peak L5/S1 extension moment (0.971) and vertical GRF (0.998). Due to lower amplitudes, smaller ICCs were found for the peak asymmetric L5/S1 moments (0.690-0.781) and horizontal GRFs (0.559-0.948). In conclusion, close correspondence was found between the ambulatory IMC-based and laboratory-based estimates of back load.

Ergonomics and human factors in endoscopic surgery: a comparison of manual vs telerobotic simulation systems.

BACKGROUND: Minimally invasive surgical techniques expose surgeons to a variety of occupational hazards that may promote musculoskeletal disorders. Telerobotic systems for minimally invasive surgery may help to reduce these stressors. The objective of this study was to compare manual and telerobotic endoscopic surgery in terms of postural and mental stress. METHODS: Thirteen participants with no experience as primary surgeons in endoscopic surgery performed a set of simulated surgical tasks using two different techniques--a telerobotic master--slave system and a manual endoscopic surgery system. The tasks consisted of passing a soft spherical object through a series of parallel rings, suturing along a line 5-cm long, running a 32-in ribbon, and cannulation. The Job Strain Index (JSI) and Rapid Upper Limb Assessment (RULA) were used to quantify upper extremity exposure to postural and force risk factors. Task duration was quantified in seconds. A questionnaire provided measures of the participants' intuitiveness and mental stress. RESULTS: The JSI and RULA scores for all four tasks were significantly lower for the telerobotic technique than for the manual one. Task duration was significantly longer for telerobotic than for manual tasks. Participants reported that the telerobotic technique was as intuitive as, and no more stressful than, the manual technique. CONCLUSIONS: Given identical tasks, the time to completion is longer using the telerobotic technique than its manual counterpart. For the given simulated tasks in the laboratory setting, the better scores for the upper extremity postural analysis indicate that telerobotic surgery provides a more comfortable environment for the surgeon without any additional mental stress.

In vivo finger flexor tendon force while tapping on a keyswitch.

Force may be a risk factor for musculoskeletal disorders of the upper extremity associated with typing and keying. However, the internal finger flexor tendon forces and their relationship to fingertip forces during rapid tapping on a keyswitch have not yet been measured in vivo. During the open carpal tunnel release surgery of five human subjects, a tendon-force transducer was inserted on the flexor digitorum superficialis of the long finger. During surgery, subjects tapped with the long finger on a computer keyswitch, instrumented with a keycap load cell. The average tendon maximum forces during a keystroke ranged from 8.3 to 16.6 N (mean = 12.9 N, SD = 3.3 N) for the subjects, four to seven times larger than the maximum forces observed at the fingertip. Tendon forces estimated from an isometric tendon-force model were only one to two times larger than tip force, significantly less than the observed tendon forces (p = 0.001). The force histories of the tendon during a keystroke were not proportional to fingertip force. First, the tendon-force histories did not contain the high-frequency fingertip force components observed as the tip impacts with the end of key travel. Instead, tendon tension during a keystroke continued to increase throughout the impact. Second, following the maximum keycap force, tendon tension during a keystroke decreased more slowly than fingertip force, remaining elevated approximately twice as long as the fingertip force. The prolonged elevation of tendon forces may be the result of residual eccentric muscle contraction or passive muscle forces, or both, which are additive to increasing extensor activity during the release phase of the keystroke.

Tensions of the flexor digitorum superficialis are higher than a current model predicts.

Existing isometric force models can be used to predict tension in the finger flexor tendon, however, they assume a specific distribution of forces across the tendons of the fingers. These assumptions have not been validated or explored by experimental methods. To determine if the force distributions repeatably follow one pattern the in vivo tension of the flexor digitorum superficialis (FDS) tendon of the long finger was measured in nine patients undergoing open carpal tunnel release surgery. Following the release, a tendon force transducer (Dennerlein et al. 1997 J. Biomechanics 30(4), 395-397) was mounted onto the FDS of the long finger. Tension in the tendon, contact force at the fingertip, and finger posture were recorded while the patient gradually increased the force applied by the fingertip from 0 to 10 N and then monotonically reduced it to 0 N. The average ratio of the tendon tension to the fingertip contact force ranged from 1.7 to 5.8 (mean = 3.3, s.d. = 1.4) for the nine subjects. These ratios are larger than ratios predicted by current isometric tendon force models (mean = 1.2, s. d. = 0.4). Subjects who used a pulp pinch posture (hyper-extended distal interphalangeal joint (DIP)) showed a significantly (p = 0.02) larger ratio (mean = 4.4, s.d. = 1.5) than the five subjects who flexed the DIP joint in a tip pinch posture (mean = 2.4, s.d. = 0.6). A new DIP constraint model, which selects different force distribution based on DIP joint posture, predicts force ratios that correlate well with the measured ratios (r2 = 0.85).

A low profile human tendon force transducer: the influence of tendon thickness on calibration.

An in vitro calibration method for human tendon force transducers using tendon thickness to predict the calibration factor has been previously proposed (An et al., 1990, J. Biomechanics 23, 1269-1271). However, changes in the calibration factor due to changing tendon geometry during repeated tendon loading are unknown. A new, low-profile transducer design that measures tendon thickness in the transducer, in situ, is developed. An empirical model estimating the transducer's calibration factor is developed using data from in vitro tension testing of 12 fresh frozen human finger flexor tendons. Each tendon is preseated with ten loading cycles before data collection. Using tendon thickness, the model predicts the measured calibration factor to within 0-15% (average 6%). During repeated loading of an in vitro tendon, the calibration factor changes 15% over the first ten cycles (0-50 N) due to the observed changing tendon thickness. After the first ten loading cycles the variability of the calibration factor is reduced to less than 1% for the next three loading cycles. Hence this new, modified in vitro calibration procedure with tendon preseating reduces the cycle-to-cycle variability caused by the associated change in the tendon thickness.

Impact of organizational policies and practices on workplace injuries in a hospital setting.

OBJECTIVE: This study aimed to assess relationships between perceptions of organizational practices and policies (OPP), social support, and injury rates among workers in hospital units. METHODS: A total of 1230 hospital workers provided survey data on OPP, job flexibility, and social support. Demographic data and unit injury rates were collected from the hospitals' administrative databases. RESULTS: Injury rates were lower in units where workers reported higher OPP scores and high social support. These relationships were mainly observed among registered nurses. Registered nurses perceived coworker support and OPP as less satisfactory than patient care associates (PCAs). Nevertheless, because of the low number of PCAs at each unit, results for the PCAs are preliminary and should be further researched in future studies with larger sample sizes. CONCLUSIONS: Employers aiming to reduce injuries in hospitals could focus on good OPP and supportive work environment.

Developing a framework for assessing muscle effort and postures during computer work in the field: the effect of computer activities on neck/shoulder muscle effort and postures.

The present study, a part of the PROOF (PRedicting Occupational biomechanics in OFfice workers) study, aimed to determine whether trapezius muscle effort was different across computer activities in a field study of computer workers, and also investigated whether head and shoulder postures were different across computer activities. One hundred twenty participants were measured continuously for two hours each while performing their own computer work. Keyboard activities were associated with the highest intensity of left and right trapezius muscle efforts, and mouse activities were associated with the smallest variability in left and right trapezius muscle efforts. Corresponding trends in head and shoulder postures included that the greatest head flexion and left and right shoulder internal rotation was observed during keyboard activities, and that the smallest variability in head flexion, head lateral tilt, and right shoulder internal rotation was observed during mouse activities. Identifying which muscle efforts and postures are different across computer activities is the first essential step for developing prediction rules for muscle efforts and postures, which can be used to link muscle efforts and postures to musculoskeletal symptoms in epidemiological studies.

Effect of horizontal position of the computer keyboard on upper extremity posture and muscular load during computer work.

The distance of the keyboard from the edge of a work surface has been associated with hand and arm pain; however, the variation in postural and muscular effects with the horizontal position have not been explicitly explored in previous studies. It was hypothesized that the wrist approaches more of a neutral posture as the keyboard distance from the edge of table increases. In a laboratory setting, 20 adults completed computer tasks using four workstation configurations: with the keyboard at the edge of the work surface (NEAR), 8 cm from the edge and 15 cm from the edge, the latter condition also with a pad that raised the work surface proximal to the keyboard (FWP). Electrogoniometers and an electromagnetic motion analysis system measured wrist and upper arm postures and surface electromyography measured muscle activity of two forearm and two shoulder muscles. Wrist ulnar deviation decreased by 50% (4 degrees ) as the keyboard position moved away from the user. Without a pad, wrist extension increased by 20% (4 degrees ) as the keyboard moved away but when the pad was added, wrist extension did not differ from that in the NEAR configuration. Median values of wrist extensor muscle activity decreased by 4% maximum voluntary contraction for the farthest position with a pad (FWP). The upper arm followed suit: flexion increased while abduction and internal rotation decreased as the keyboard was positioned further away from the edge of the table. In order to achieve neutral postures of the upper extremity, the keyboard position in the horizontal plane has an important role and needs to be considered within the context of workstation designs and interventions.

Haptic force-feedback devices for the office computer: performance and musculoskeletal loading issues.

Pointing devices, essential input tools for the graphical user interface (GUI) of desktop computers, require precise motor control and dexterity to use. Haptic force-feedback devices provide the human operator with tactile cues, adding the sense of touch to existing visual and auditory interfaces. However, the performance enhancements, comfort, and possible musculoskeletal loading of using a force-feedback device in an office environment are unknown. Hypothesizing that the time to perform a task and the self-reported pain and discomfort of the task improve with the addition of force feedback, 26 people ranging in age from 22 to 44 years performed a point-and-click task 540 times with and without an attractive force field surrounding the desired target. The point-and-click movements were approximately 25% faster with the addition of force feedback (paired t-tests, p < 0.001). Perceived user discomfort and pain, as measured through a questionnaire, were also smaller with the addition of force feedback (p < 0.001). However, this difference decreased as additional distracting force fields were added to the task environment, simulating a more realistic work situation. These results suggest that for a given task, use of a force-feedback device improves performance, and potentially reduces musculoskeletal loading during mouse use. Actual or potential applications of this research include human-computer interface design, specifically that of the pointing device extensively used for the graphical user interface.