Vibration transmission is essential in the design of comfortable vehicle seats but knowledge is lacking on 3D trunk and head motion and the role of seat back and posture. We hypothesized that head motion is reduced when participants’ upper back is unsupported, as this stimulates active postural control. We developed an experimental methodology to evaluate 3D vibration transmission from compliant seats to the human body. Wide-band (0.1–12 Hz) motion stimuli were applied in fore-aft, lateral and vertical direction to evaluate the translational and rotational body response in pelvis, trunk and head. A standard car seat was equipped with a configurable and compliant back support to test 3 support heights and 3 sitting postures (erect, slouched, and preferred) where we also tested head down looking at a smartphone. Seat back support height and sitting posture substantially affected vibration transmission and affected low frequency responses in particular for body segment rotation. According to our hypothesis a low support height proved beneficial in reducing head motion. Relevance to industry: Our methodology effectively evaluates 3D wide-band vibration transmission from compliant seats to the human body. The lowest back support height reduced head motion but was perceived as least comfortable. This calls for seat designs which support but do not so much constrain the upper back. The head down posture enlarged head motion, pleading for computer system integration allowing heads up postures in future automated cars. The biomechanical data will serve to validate human models supporting the design of comfortable (automated) vehicles.

In future automated vehicles we will often engage in non-driving tasks and will not watch the road. This will affect postural stabilization and may elicit discomfort or even motion sickness in dynamic driving. Future vehicles will accommodate this with properly designed seats and interiors, whereas comfortable vehicle motion will be achieved with smooth driving styles and well-designed (active) suspensions. To support research and development in dynamic comfort, this paper presents the validation of a multi-segment full-body human model, including visuo-vestibular and muscle spindle feedback, for postural stabilization. Dynamic driving is evaluated using a “sickening drive”, including a 0.2 Hz 4 m/s² slalom. Vibration transmission is evaluated with compliant automotive seats, applying 3D platform motion and evaluating 3D translation and rotation of pelvis, trunk and head. The model matches human motion in dynamic driving and reproduces fore–aft, lateral and vertical oscillations. Visuo-vestibular and muscle spindle feedback are shown to be essential, in particular, for head–neck stabilization. Active leg muscle control at the hips and knees is shown to be essential to stabilize the trunk in the high-amplitude slalom condition but not with low-amplitude horizontal vibrations. However, active leg muscle control can strongly affect 4–6 Hz vertical vibration transmission. Compared to the vibration tests, the dynamic driving tests show enlarged postural control gains to minimize trunk and head roll and pitch and to align head yaw with driving direction. Human modelling can enable the insights required to achieve breakthrough comfort enhancements, while enabling efficient developments for a wide range of driving conditions, body sizes and other factors. Hence, modelling human postural control can accelerate the innovation of seats and vehicle motion-control strategies for (automated) vehicles.

To improve our understanding on the neuromechanics of finger movements, a comprehensive musculoskeletal model is needed. The aim of this study was to build a musculoskeletal model of the hand and wrist, based on one consistent data set of the relevant anatomical parameters. We built and tested a model including the hand and wrist segments, as well as the muscles of the forearm and hand in OpenSim. In total, the model comprises 19 segments (with the carpal bones modeled as one segment) with 23 degrees of freedom and 43 muscles. All required anatomical input data, including bone masses and inertias, joint axis positions and orientations as well as muscle morphological parameters (i.e. PCSA, mass, optimal fiber length and tendon length) were obtained from one cadaver of which the data set was recently published. Model validity was investigated by first comparing computed muscle moment arms at the index finger metacarpophalangeal (MCP) joint and wrist joint to published reference values. Secondly, the muscle forces during pinching were computed using static optimization and compared to previously measured intraoperative reference values. Computed and measured moment arms of muscles at both index MCP and wrist showed high correlation coefficients (r = 0.88 averaged across all muscles) and modest root mean square deviation (RMSD = 23% averaged across all muscles). Computed extrinsic flexor forces of the index finger during index pinch task were within one standard deviation of previously measured in-vivo tendon forces. These results provide an indication of model validity for use in estimating muscle forces during static tasks.

Aging has consequences for hand motor control, among others affecting finger force enslaving during static pressing tasks. The aim of this study was to assess whether the extent of finger force enslaving changes with aging during a task that involves both static and dynamic phases. Ten right-handed young (22–30 years) and ten elderly subjects (67–79 years) were instructed to first exert a constant force (static phase) and then flex their index finger while counteracting constant resistance forces orthogonal to their fingertips (dynamic phase). The other fingers (non-instructed) were held in extension. EMG activities of the flexor digitorum superficialis (FDS) and extensor digitorum (ED) muscles in the regions corresponding to the index, middle and ring fingers together with their forces and position of index finger were measured. In both elderly and young, forces exerted by the non-instructed fingers increased (around 0.6 N for both young and elderly) during isotonic flexion of the index finger, but with a different delay of on average 100 ± 72 ms in elderly and 334 ± 101 ms in young subjects. Results also suggest different responses in activity of FDS and ED muscle regions of the non-instructed fingers to index finger flexion between elderly and young subjects. The enslaving effect was significantly higher in elderly than in young subjects both in the static (12% more) and dynamic (14% more) phases. These differences in enslaving can at least partly be explained by changes in neuromuscular control.