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Objectives. This study examines the role of different machine learning (ML) algorithms to determine which socio-demographic factors and hand–forearm anthropometric dimensions can be used to accurately predict hand function. Methods. The cross-sectional study was conducted with 7119 healthy Iranian participants (3525 males and 3594 females) aged 10–89 years. Seventeen hand–forearm anthropometric dimensions were measured by JEGS digital caliper and a measuring tape. Tip-to-tip, key and three-jaw chuck pinches were measured using a calibrated pinch gauge. Subsequently, 21 features pertinent to socio-demographic factors and hand–forearm anthropometric dimensions were used for classification. Furthermore, 12 well-known classifiers were implemented and evaluated to predict pinches. Results. Among the 21 features considered in this study, hand length, stature, age, thumb length and index finger length were found to be the most relevant and effective components for each of the three pinch predictions. The k-nearest neighbor, adaptive boosting (AdaBoost) and random forest classifiers achieved the highest classification accuracy of 96.75, 86.49 and 84.66% to predict three pinches, respectively. Conclusions. Predicting pinch strength and determining the predictive hand–forearm anthropometric and socio-demographic characteristics using ML may pave the way to designing an enhanced tool handle and reduce common musculoskeletal disorders of the hand. [ABSTRACT FROM AUTHOR]

Objectives. This study examines which of the heart rate variability (HRV) and morphologic variability (MV) metrics may have the highest accuracy in different stress detection during real-world driving. Methods. The cross-sectional study was carried out among 93 intercity mini-bus male drivers aged 22–67 years. The Trillium 5000 Holter Recorder and GARMIN Virb Elite camera were used to determine heart rate and vehicle speed measurements along the path, respectively. We considered the HRV and MV metrics of electrocardiogram (ECG) signals including the mean RR interval (mRR), mean heart rate (mHR), normalized low-frequency spectrum (nLF), normalized high-frequency spectrum (nHF), normalized very low-frequency spectrum (nVLF), difference of normalized low-frequency spectrum and normalized high-frequency spectrum (dLFHF), and sympathovagal balance index (SVI). Results. The analysis showed that the HRV metrics mHR, mRR, nVLF, nLF, nHF, dLFHF and SVI are effective in mental stress detection while driving as compared to rest time. We obtained a high accuracy of stress detection for MV metrics as compared to the traditional HRV analysis, of approximately 92%. Conclusions. Our findings indicate that driver stress could be detected with an accuracy of 92% using MV metrics as an accurate physiological index of the driver's state. [ABSTRACT FROM AUTHOR]

Objectives. The decision-making trial and evaluation laboratory (DEMATEL) technique integrated with the analytic network process (ANP) is used for determination and prioritization of cause–effect relationships among factors affecting construction falls. Methods. Considering the 135 fall accidents collected between 2013 and 2018 from 15 residential construction projects, 70 factors and sub-factors affecting the occurrence of construction falls were determined based on safety experts' opinions. Questionnaires based on the former and the latter were then distributed among 10 occupational health and safety specialists to determine the effectiveness of the factors. The interactions and important degree of each factor are specified, using the DEMATEL–ANP approach. Results. Findings showed that organizational factors and their sub-factors have the greatest impact on construction falls and were considered as causal variables (D – R > 0), while individual and environmental factors were considered as the effect variables (D – R < 0). The results of prioritization using the ANP method showed that the work platform altitude, psychological/occupational stresses and interactions were ranked as the first through third priorities affecting the falls, respectively. Conclusions. It is necessary to implement a systematic strategy to reduce the unsafe conditions in construction projects and to pay more attention to organizational factors. [ABSTRACT FROM AUTHOR]

Background: Low back pain (LBP) is known as one of the most common workrelated musculoskeletal disorders. Spinal cumulative loads (CLs) during manual material handling (MMH) tasks are the main risk factors for LBP. However, there is no valid and reliable quantitative lifting analysis tool available for quantifying CLs among Iranian workers performing MMH tasks. Objective: This study aimed to investigate the validity and inter-rater reliability of a posture-matching load assessment tool (PLAT) for estimating the L5-S1 static cumulative compression (CC) and shear (CS) loads based on predictive regression equations. Material and Methods: This experimental study was conducted among six participants performing four lifting tasks, each comprised of five trials during which their posture was recorded via a motion capture (Vicon) and simultaneously a threecamera system located at three different angles (0°, 45°, and 90°) to the sagittal plane. Results: There were no significant differences between the two CLs estimated by PLAT from the three-camera system and the gold-standard Vicon. In addition, ten raters estimated CLs of the tasks using PLAT in three sessions. The calculated intra-class correlation coefficients for the estimated CLs within each task revealed excellent interrater reliability (> 0.75), except for CS in the first and third tasks, which were good (0.6 to 0.75). Conclusion: The proposed posture-matching approach provides a valid and reliable ergonomic assessment tool suitable for assessing spinal CLs during various lifting activities. [ABSTRACT FROM AUTHOR]

This article presents a virtual prototyping study of a semi-active lower limb prosthesis to improve the functionality of an amputee during prosthesis–environment interaction for level ground walking. Articulated ankle–foot prosthesis and a single-axis semi-active prosthetic knee with active and passive operating modes were considered. Data for level ground walking were collected using a photogrammetric method in order to develop a base-line simulation model and with the hip kinematics input to verify the proposed design. The simulated results show that the semi-active lower limb prosthesis is able to move efficiently in passive mode, and the activation time of the knee actuator can be reduced by approximately 50%. Therefore, this semi-active system has the potential to reduce the energy consumption of the actuators required during level ground walking and requires less compensation from the amputee due to lower deviation of the vertical excursion of body centre of mass. [ABSTRACT FROM AUTHOR]

Understanding the kinematics of the spine provides paramount knowledge for many aspects of the clinical analysis of back pain. More specifically, visualisation of the instantaneous centre of rotation (ICR) enables clinicians to quantify joint laxity in the segments, avoiding a dependence on more inconclusive measurements based on the range of motion and excessive translations, which vary in every individual. Alternatively, it provides motion preserving designers with an insight into where a physiological ICR of a motion preserving prosthesis can be situated in order to restore proper load distribution across the passive and active elements of the lumbar region. Prior to the use of an unconstrained dynamic musculoskeletal model system, based on multi-body models capable of transient analysis, to estimate segmental loads, the model must be kinematically evaluated for all possible sensitivity due to ligament properties and the initial locus of intervertebral disc (IVD). A previously calibrated osseoligamentous model of lumbar spine was used to evaluate the changes in ICR under variation of the ligament stiffness and initial locus of IVD, when subjected to pure moments from 0 to 15 Nm. The ICR was quantified based on the closed solution of unit quaternion that improves accuracy and prevents coordinate singularities, which is often observed in Euler-based methods and least squares principles. The calculation of the ICR during flexion/extension revealed complexity and intrinsic nonlinearity between flexion and extension. This study revealed that, to accommodate a good agreement betweenin vitrodata and the multi-body model predictions, in flexion more laxity is required than in extension. The results showed that the ICR location is concentrated in the posterior region of the disc, in agreement with previous experimental studies. However, the current multi-body model demonstrates a sensitivity to the initial definition of the ICR, which should be recognised as a limitation of the method. Nevertheless, the current simulations suggest that, due to the constantly evolving path of the ICR across the IVD during flexion–extension, a movable ICR is a necessary condition in multi-body modelling of the spine, in the context of whole body simulation, to accurately capture segmental kinematics and kinetics. [ABSTRACT FROM AUTHOR]

The human spinal segment is an inherently complex structure, a combination of flexible and semi-rigid articulating elements stabilised by seven principal ligaments. An understanding of how mechanical loading is shared among these passive elements of the segment is required to estimate tissue failure stresses. A 3D rigid body model of the complete lumbar spine has been developed to facilitate the prediction of load sharing across the passive elements. In contrast to previous multibody models, this model includes a non-linear, six degrees of freedom intervertebral disc, facet bony articulations and all spinal ligaments. Predictions of segmental kinematics and facet joint forces, in response to pure moment loading (flexion-extension), were compared to published in vitro data. On inclusion of detailed representation of the disc and facets, the multibody model fully captures the non-linear flexibility response of the spinal segment, i.e. coupled motions and a mobile instantaneous centre of rotation. Predicted facet joint forces corresponded well with reported values. For the loading case considered, the model predicted that the ligaments are the main stabilising elements within the physiological motion range; however, the disc resists a greater proportion of the applied load as the spine is fully flexed. In extension, the facets and capsular ligaments provide the principal resistance. Overall patterns of load distribution to the spinal ligaments are in agreement with previous predictions; however, the current model highlights the important role of the intraspinous ligament in flexion and the potentially high risk of failure. Several important refinements to the multibody modelling of the passive elements of the spine have been described, and such an enhanced passive model can be easily integrated into a full musculoskeletal model for the prediction of spinal loading for a variety of daily activities. [ABSTRACT FROM AUTHOR]

A response by Alireza Abouhossein and colleagues to a letter to the editor regarding their article "A multi-body modelling approach to determine load sharing between the passive elements of the lumbar spine" in the 2010 issue is presented.