Riender Happee

The control of shoulder muscles during goal directed movements, an inverse dynamic analysis.

Fast goal directed arm movements in the sagittal plane were analyzed with a three-dimensional shoulder model with 95 muscle elements. Dynamics of the muscle elements were described by a third-order nonlinear muscle model. Muscle forces and activation were estimated using the method of inverse muscular dynamics, an optimization scheme which uses only very limited computational power. Most model results were similar to the EMG but some differences between model results and EMG were found in muscles where the EMG activity was subject dependent. For the movement studied, the thoracoscapular muscles were shown to deliver about 40% of the energy required for the acceleration of the arm during anteflexion and about 22% during retroflexion. Activity of thoracoscapular muscles was also required to ensure contact between the thorax and the scapula which is important for the mechanical stability of the shoulder. The rotator cuff muscles were found to deliver about 19% of the energy required for the acceleration of the arm during anteflexion and about 8% during retroflexion.

Inverse dynamic optimization including muscular dynamics, a new simulation method applied to goal directed movements

This paper presents a new method for estimating muscular force and activation from experimental kinematic data. The method combines conventional inverse dynamics with optimization utilizing a dynamic muscle model. The method uses only very limited computational power, which makes it a useful tool especially for complex systems like the shoulder or the locomotor system. The net torques/forces are calculated by using conventional inverse dynamics. A solution of the load sharing problem is determined by minimization of the weighted sum of squared muscle forces. The load sharing problem is solved with a dynamic constraint reflecting physiological muscle properties. This constraint takes into account the nonlinear dynamics of the contractile element (CE) and the series elastic element (SE), active state dynamics and neural excitation dynamics. This physiological constraint is determined with an inverse muscle model. With this model, muscular states and neural inputs are also estimated. The method of inverse dynamics requires position, velocity and acceleration signals as input. A method to prepare such signals from noisy measured data is presented.

Automated driving: human-factors issues and design solutions

The goal of this paper is to outline human-factors issues associated with automated driving, with a focus on car following. First, we review the challenges of having automated driving systems from a human-factors perspective. Next, we identify human-machine interaction needs for automated vehicles and propose some available solutions. Finally, we propose design requirements for Cooperative Adaptive Cruise Control.

Identifying intrinsic and reflexive contributions to low-back stabilization

Motor control deficits have been suggested as potential cause and/or effect of a-specific chronic low-back pain and its recurrent behavior. Therefore, the goal of this study is to identify motor control in low-back stabilization by simultaneously quantifying the intrinsic and reflexive contributions. Upper body sway was evoked using continuous force perturbations at the trunk, while subjects performed a resist or relax task. Frequency response functions (FRFs) and coherences of the admittance (kinematics) and reflexes (sEMG) were obtained. In comparison with the relax task, the resist task resulted in a 61% decrease in admittance and a 73% increase in reflex gain below 1.1Hz. Intrinsic and reflexive contributions were captured by a physiologically-based, neuromuscular model, including proprioceptive feedback from muscle spindles (position and velocity) and Golgi tendon organs (force). This model described on average 90% of the variance in kinematics and 39% of the variance in sEMG, while resulting parameter values were consistent over subjects.

A review of visual driver models for system identification purposes

The aim of this study was to find a realistic control-theoretic visual driver model for curve driving that does not only show simular performance as actual drivers but also applies the same inputs and uses the same information. The model structure must enable system identification and parameter estimation of the model parameters. A large number of existing and adapted models have been evaluated and simulated, and when possible, frequency response functions have been identified using two system identification methods. A significant part of the paper is devoted to review these models. The evaluation shows that two-point models comply best with all system identification requirements while still governing realistic driving behavior. It is recommended to investigate further the positioning and perception part of the two-point models using eye-tracking in driving experiments with real human drivers.

Road-Departure Prevention in an Emergency Obstacle Avoidance Situation

This paper presents a driving simulator experiment, which evaluates a road-departure prevention (RDP) system in an emergency situation. Two levels of automation are evaluated: 1) haptic feedback (HF) where the RDP provides advisory steering torque such that the human and the machine carry out the maneuver cooperatively, and 2) drive by wire (DBW) where the RDP automatically corrects the front-wheels angle, overriding the steering-wheel input provided by the human. Thirty participants are instructed to avoid a pylon-confined area while keeping the vehicle on the road. The results show that HF has a significant impact on the measured steering wheel torque, but no significant effect on steering-wheel angle or vehicle path. DBW prevents road departure and tends to reduce self-reported workload, but leads to inadvertent human-initiated steering resulting in pylon collisions. It is concluded that a low level of automation, in the form of HF, does not prevent road departures in an emergency situation. A high level of automation, on the other hand, is effective in preventing road departures. However, more research may have to be done on the human response while driving with systems that alter the relationship between steering-wheel angle and front-wheels angle.

Why selective publication of statistically significant results can be effective

Concerns exist within the medical and psychological sciences that many published research findings are not replicable. Guidelines accordingly recommend that the file drawer effect should be eliminated and that statistical significance should not be a criterion in the decision to submit and publish scientific results. By means of a simulation study, we show that selectively publishing effects that differ significantly from the cumulative meta-analytic effect evokes the Proteus phenomenon of poorly replicable and alternating findings. However, the simulation also shows that the selective publication approach yields a scientific record that is content rich as compared to publishing everything, in the sense that fewer publications are needed for obtaining an accurate meta-analytic estimation of the true effect. We conclude that, under the assumption of self-correcting science, the file drawer effect can be beneficial for the scientific collective.

Steering Force Feedback for Human–Machine-Interface Automotive Experiments

Driving-simulator fidelity is usually defined by the quality of its visual and motion cueing system. However, the quality of its haptic cues is also very important and is determined by both hardware and control properties. Most experiments with haptic steering systems employ commercially available systems and do not address the systems fidelity. The goal of this paper is to offer guidelines for the development of hardware, performance evaluation, and system control in order to engineer realistic haptic cues on the steering wheel. A relatively low-cost solution for hardware is deployed, consisting of a velocity-controlled three-phase brushless servomotor, of which its high-bandwidth control allows for a realistic representation of forces. A method is presented to overcome electromagnetic interference produced by the industrial servomotor and the controller through careful amplification and filtering. To test the system, different inertia-spring-damper systems were simulated and evaluated in time and frequency domain. In conclusion, the designed system allowed reproduction of a large range of steering-wheel dynamics and forces. As a result, the developed system constitutes an efficient haptic device for human-machine-interface automotive experiments.

Muscle parameters for musculoskeletal modelling of the human neck

BACKGROUND To study normal or pathological neuromuscular control, a musculoskeletal model of the neck has great potential but a complete and consistent anatomical dataset which comprises the muscle geometry parameters to construct such a model is not yet available. METHODS A dissection experiment was performed on the left side of one 50th percentile male embalmed specimen. Geometrical data including muscle attachment sites were digitized using an Optotrak measurement system and laser diffraction was used to determine muscle sarcomere lengths. Bony landmarks were recorded and joint centres of rotation between different vertebrae were estimated using literature data. FINDINGS A total of 34 muscle parts of the neck were divided in 129 elements per body side. Muscle attachment sites, mass, physiological cross sectional area, fibre length, tendon length and optimal fibre length for each element are supplied as digital annexes to the paper. Results are coherent with other studies and new data are provided for several smaller muscles not reported elsewhere. INTERPRETATION Implementation of this dataset into a neck model is likely to improve the estimation of muscle forces and thus increase the model validity; this makes future neck models more suitable for the use as clinical tools.

Frequency response of vestibular reflexes in neck, back and lower limb muscles

Vestibular pathways form short-latency disynaptic connections with neck motoneurons, whereas they form longer-latency disynaptic and polysynaptic connections with lower limb motoneurons. We quantified frequency responses of vestibular reflexes in neck, back, and lower limb muscles to explain between-muscle differences. Two hypotheses were evaluated: 1) that muscle-specific motor-unit properties influence the bandwidth of vestibular reflexes; and 2) that frequency responses of vestibular reflexes differ between neck, back, and lower limb muscles because of neural filtering. Subjects were exposed to electrical vestibular stimuli over bandwidths of 0-25 and 0-75 Hz while recording activity in sternocleidomastoid, splenius capitis, erector spinae, soleus, and medial gastrocnemius muscles. Coherence between stimulus and muscle activity revealed markedly larger vestibular reflex bandwidths in neck muscles (0-70 Hz) than back (0-15 Hz) or lower limb muscles (0-20 Hz). In addition, vestibular reflexes in back and lower limb muscles undergo low-pass filtering compared with neck-muscle responses, which span a broader dynamic range. These results suggest that the wider bandwidth of head-neck biomechanics requires a vestibular influence on neck-muscle activation across a larger dynamic range than lower limb muscles. A computational model of vestibular afferents and a motoneuron pool indicates that motor-unit properties are not primary contributors to the bandwidth filtering of vestibular reflexes in different muscles. Instead, our experimental findings suggest that pathway-dependent neural filtering, not captured in our model, contributes to these muscle-specific responses. Furthermore, gain-phase discontinuities in the neck-muscle vestibular reflexes provide evidence of destructive interaction between different reflex components, likely via indirect vestibular-motor pathways.