Suzanne Nooij

Research scientist

I work as a research scientist in the Motion Perception and Simulation research group, and my main interest is self-motion perception and spatial orientation. In other words: how do we perceive our body motion through the environment, based on all the information coming from our senses? My first line of research focusses on the integration of rotational and linear motions. I investigate how these interact and whether this process is influenced by cognitive factors.

The second line of research focusses on motion sickness. In both an actual vehicle and a simulator motion sickness can occur, and there are still many different theories on its cause and prevention. By investigating under which circumstances motion sickness occurs in our simulators, I hope to better understand why this incapacitating condition arises.

Background

I received an MSc. degree in Human Movement Sciences in 2002 (cum laude;  Vrije Universiteit Amsterdam), and subsequently started my PhD research at the TNO Human Factors institute in Soesterberg, The Netherlands. It concerned a project on vestibular adaptation and motion sickness in astronauts, during which I was fascinated by the inevitable effect of gravity on human functioning in general, and on spatial orientation in particular. After completing the project in 2008, I worked for four years as a research scientist for the Royal Netherlands Airforce and Desdemona BV using the advanced Desdemona motion simulator for research on spatial disorientation in flight. Since 2013 I am affiliated to the Max Planck Institute for Biological Cybernetics, where I have the opportunity to investigate spatial orientation, motion perception and motion sickness on a more fundamental level.

Selected publications

• Vection is the main contributor to motion sickness induced by visual yaw rotation: Implications for conflict and eye movement theories PLoS ONE (2017)

• Perception of rotation, path, and heading in circular trajectories Experimental Brain Research (2016)
• Sensitivity to lateral force is affected by concurrent yaw rotation during curve driving DSC 2015 Europe: Driving Simulation Conference & Exhibition (2015)

Visually induced motion sickness

We are all familiar with the train illusion: the feeling that your train is departing when, in fact, you see the train at the neighboring platform leave the station. This powerful illusion shows us that motion of the visual field can give a compelling sense of self-motion in stationary observers, a phenomenon that is exploited in many fixed-base motion simulators. A negative side effect is that prolonged exposure to visually induced self-motion, also named vection, can give rise to motion sickness. In this project we look at motion perception and motion sickness when the entire visual surround is rotated around the observer’s vertical (yaw) axis. This specific situation is interesting, because it allows us to disentangle different theories on motion sickness, that all propose different causal factors. By adopting an integrative approach to this problem, and obtaining continuous measures of motion sickness, perceived self-motion, eye, and head movements, we aim at a better understanding of factors contributing to visually induced motion sickness [1].

Motion perception in curves

Already much is known about the contribution of the vestibular system to the perception of self-motion during pure translations or pure rotations in the horizontal plane. In this project we investigated motion perception under combined translation and rotation, as is the case when going around a curve. Current models of human motion perception describe how the vestibular signals from semicircular canals and otoliths are processed to derive an estimate of the perceived body tilt, translation and rotation. The overall perceived motion through the environment is then obtained by summing all components. In this project we took the predictions from such a motion perception model as a starting point and investigated whether the reported motion percept is in line with the model predictions. In particular, we measured perceived heading (one’s orientation with respect to the motion path), for which the model predicts a bias. The perceived heading would be very different from the physical one when no visual information is present. This is because the motion also will induce some tilt, which affects the perceived motion path. In a psychophysical experiment we tested this model prediction, and found that the perceived heading is quite veridical [2]. This suggests that the current models are not yet sufficient to capture the perception process during combined motions.

Overview of results. Physical heading (red) required to perceive one's orientation as aligned with the curve. This is different from the model prediction.

Motion sensitivity in driving simulation

In driving simulation sustained lateral forces (occuring for instance during curve driving) are simulated by roll tilt of the simulator while presenting a correct visual image indicating no tilt ("tilt coordination"). To make this “trick” work, the tilt should be slow, staying below the perceptual threshold. In this project we determined how this threshold behaves under different experimental conditions: when in pure darkness, when concurrent sway is present, when the roll is suppressed by visual information, and during an active driving task. In line with other studies, the results show that the threshold increases when other motion components (i.e., sway) are present. Also active driving affected the threshold, but this seemed to depend on the level of immersion [3]. This knowledge can be exploited in the tuning of the allowed tilt rate in the simulator motion drive algorithm.

Perception based vehicle simulation

In vehicle simulation we present a driver or pilot with a combination of inertial and visual cues, in order to make the perceived motion of the simulator the same as that of the actual vehicle. Normally a set of filters is used to transform the motion of the vehicle into simulator motion, which take only limited knowledge of human perception into account. In this project we developed and tested a novel approach to control the simulator that 1) utilized models on human self motion perception and sensitivity, and 2) optimized the simulator motion (without using filters) to create the intended percept. The approach was validated in a study where participants compared the perceptual validity of several driving maneuvers, comparing the traditional to the novel framework [4]. This validation showed that with the novel approach perceptual validity was enhanced while making optimal use of the entire simulator workspace.

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