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Musculoskeletal disorders (MSDs) are prevalent among airline baggage handlers due to manual materials handling. In this study, the Nordic musculoskeletal questionnaire (NMQ), the revised National Institute for Occupational Safety and Health (NIOSH) lifting equation, and the University of Michigan 3D Static Strength Prediction Program™ (3DSSPP) were used to analyze MSDs among baggage handlers.The NMQ was filled out by 209 baggage handlers and 46 arbitrarily selected baggage handlers were evaluated using the NIOSH method and 3DSSPP.The obtained results showed that the most common MSDs occurred in the lower back region. The next risky regions included knees, neck, and upper back, respectively. The NIOSH results confirmed that the subjects lifted loads heavier than the permitted limit and their lifting postures were inappropriate. The results of the 3DSSPP also indicated that compression forces exceeded the NIOSH limit in these awkward postures.Relying on this study, holding compulsory ergonomic lifting training courses could be proposed for workers and regulations adjusting an upper limit for maximum baggage weight must be also enacted in order to improve occupational health and prevent the prevalence of increasing MSDs.

The way central nervous system manages the excess degrees of freedom to solve kinetic redundancy of musculoskeletal system remains an open question. In this study, we utilise the concept of synergy formation as a simplifying control strategy to find the muscle recruitment based on summation of identified muscle synergies to balance the biomechanical demands (biaxial external torque) during an isometric shoulder task. A numerical optimisation-based shoulder model was used to obtain muscle activation levels when a biaxial external isometric torque is imposed at the shoulder glenohumeral joint. In the numerical simulations, 12 different shoulder torque vectors in the transverse plane are considered. For each selected direction for the torque vector, the resulting muscle activation data are calculated. The predicted muscle activation data are used for grouping muscles in some fixed element synergies by the non-negative matrix factorisation method. Next, torque produced by these synergies are computed and projected in the 2D torque space to investigate the magnitude and direction of torques that each muscle synergy generated. The results confirmed our expectation that few dominant synergies are sufficient to reconstruct the torque vectors and each muscle contributed to more than one synergy. Decomposition of the concatenated data, combining the activation and external torque, provided functional muscle synergies that produced torques in the four principal directions. Four muscle synergies were able to account for more than 95% of variation of the original data.

A novel optimisation algorithm is developed to predict coactivity of abdominal muscles while accounting for both trunk stability via the lowest buckling load (P(cr)) and tissue loading via the axial compression (F(c)). A nonlinear multi-joint kinematics-driven model of the spine along with the response surface methodology are used to establish empirical expressions for P(cr) and F(c) as functions of abdominal muscle coactivities and external load magnitude during lifting in upright standing posture. A two-component objective function involving F(c) and P(cr) is defined. Due to opposite demands, abdominal coactivities that simultaneously maximise P(cr) and minimise F(c) cannot exist. Optimal solutions are thus identified while striking a compromise between requirements on trunk stability and risk of injury. The oblique muscles are found most efficient as compared with the rectus abdominus. Results indicate that higher abdominal coactivities should be avoided during heavier lifting tasks as they reduce stability margin while increasing spinal loads.

To translate and validate the Persian version of the Arthritis Measurement Scales 2-Short Form (AIMS2-SF) in patients with osteoarthritis (OA) of the knee.The translation and cultural adaptation of the original questionnaire was carried out in accordance with published guidelines. One hundred and fourteen consecutive Persian-speaking patients with OA of the knee were participated in this study. The Short Form Health Survey (SF-36) and visual analogue scales (VAS) for pain and joint stiffness were used to test convergent validity of the Persian AIMS2-SF. In addition, 35 randomly selected patients were asked to complete the questionnaire 3 days later for the second time.The Persian AIMS2-SF showed statistically significant good convergent validity, as assessed with the relevant subscales of the Persian SF-36 and VAS for pain and joint stiffness. Cronbach's alpha coefficient for the Persian AIMS2-SF components ranged from 0.68 to 0.80. The Persian AIMS2-SF components showed good to excellent test-retest reliability with intraclass correlation coefficient ranged from 0.72 to 0.83 (p0.01).The Persian version of the AIMS2-SF is a reliable and valid instrument to measure functional disability and health-related quality of life in patients with OA of the knee in Iran. It is simple and easy to use and now can be applied in clinical settings and future outcome studies in Iran.

The relative vulnerability of spinal motion segments to different loading combinations remains unknown. The meta-analysis described here using the results of a validated L2-L3 nonlinear viscoelastic finite element model was designed to investigate the critical loading and its effect on the internal mechanics of the human lumbar spine. A Box-Behnken experimental design was used to design the magnitude of seven independent variables associated with loads, rotations and velocity of motion. Subsequently, an optimization method was used to find the primary and secondary variables that influence spine mechanical output related to facet forces, disc pressure, ligament forces, annulus matrix compressive/shear stresses and anulus fibers strain. The mechanical responses with respect to the two most-relevant variables were then regressed linearly using the response surface quadratic model. Axial force and sagittal rotation were identified as the most-relevant variables for mechanical responses. The procedure developed can be used to find the critical loading for finite element models with multi input variables. The derived meta-models can be used to predict the risk associated with various loading parameters and in setting safer load limits.

In any quantitative gait or occupational biomechanics investigation, the quantification of the different kinematic, kinetic, and electromyographic parameters is essential towards assessment of functional capacity and development of a biomechanical profile of the task demands. In the current study, the authors presented a methodology for using inferential statistics to evaluate the effect of lift characteristics on phase-dependent and phase-independent variability in performance. Using a database of kinematic and kinetic profiles obtained from a manual lifting study, the phase-dependent effects of lift characteristics: box mass (load), mode (technique of lift), and speed (frequency of lift) were investigated through the use of analysis of variance (ANOVA) techniques, which recognize the vectorial constitution of the profiles. In addition, the Karhunen-Loeve Expansion (KLE) feature extraction method was used for representing the lifting patterns of measured joint angular position, velocity, acceleration, and net muscular torque profiles obtained from a 2-D biomechanical lifting model in order to study the phase-independent effects. In comparison to traditional descriptive statistical analyses currently used in various occupational biomechanics experimental investigations, this method allows the significant information content of the time varying signal to be captured, enhancing the sensitivity of subsequent hypothesis testing procedures. The application of this technique to MMH investigations allows identification of the lift characteristics that dominate the variability of task demands, hence aiding in the design and assessment of ergonomic solutions.

This article explores the relationship between repetition/typing speed and force in keyboarding. Based on analysis of data collected on the job from professional keyboard operators and experimental laboratory data, the following observations are presented: (1) Individuals typing at preferred speeds tend not to exhibit a relationship between typing speed and average peak force; (2) across individuals typing at preferred speeds, there is no relationship between typing speed and force; (3) when an individual's typing speed is affected by external influences, typing force tends to increase or decrease with similar changes in typing speed.

The lifting stress calculator (LSC) is a user-friendly device based upon a two-dimensional model of static lifting; it recommends the optimum method of lifting given the anthropometry and clinical symptoms, and the physical characteristics of the load. This study illustrates the fact that there is no one simple, safe and proper lifting technique and that each lifting task warrants an individualized evaluation. The use of the LSC in the areas of rehabilitation, training and workplace design is advocated.