Joost C. F. de Winter

Objective classification of residents based on their psychomotor laparoscopic skills

BackgroundFrom the clinical point of view, it is important to recognize residents’ level of expertise with regard to basic psychomotor skills. For that reason, surgeons and surgical organizations (e.g., Acreditation Council for Graduate Medical Education, ACGME) are calling for assessment tools that credential residents as technically competent. Currently, no method is universally accepted or recommended for classifying residents as “experienced,” “intermediates,” or “novices” according to their technical abilities. This study introduces a classification method for recognizing residents’ level of experience in laparoscopic surgery based on psychomotor laparoscopic skills alone.MethodsFor this study, 10 experienced residents (>100 laparoscopic procedures performed), 10 intermediates (10–100 procedures performed), and 11 novices (no experience) performed four tasks in a box trainer. The movements of the laparoscopic instruments were recorded with the TrEndo tracking system and analyzed using six motion analysis parameters (MAPs). The MAPs of all participants were submitted to principal component analysis (PCA), a data reduction technique. The scores of the first principal components were used to perform linear discriminant analysis (LDA), a classification method. Performance of the LDA was examined using a leave-one-out cross-validation.ResultsOf 31 participants, 23 were classified correctly with the proposed method, with 7 categorized as experienced, 7 as intermediates, and 9 as novices.ConclusionsThe proposed method provides a means to classify residents objectively as experienced, intermediate, or novice surgeons according to their basic laparoscopic skills. Due to the simplicity and generalizability of the introduced classification method, it is easy to implement in existing trainers.

Why the Fitts list has persisted throughout the history of function allocation

Function allocation is a core activity of the human–machine systems discipline. Sixty years ago, Paul Fitts marked the outset of function allocation research with an 11-statements list. Since then numerous function allocation methods have been proposed, but strikingly the seminal Fitts list spans the entire history of this domain and continues to be cited today. In this paper, we intend to explain why the Fitts list is such a pervasive factor in function allocation research, despite having received extensive criticism. We invoke philosophy of science, and we show that the Fitts list fulfils six important criteria for appraising scientific theories: plausibility, explanatory adequacy, interpretability, simplicity, descriptive adequacy, and generalisability. Furthermore, we show that the Fitts report identified issues which decades later became known as the ironies of automation. We conclude that the Fitts list is an adequate approximation that captures the most important regularity of automation, and that the Fitts report represents an unprecedented intellectual achievement that has succeeded in its pioneering objective.

The Effect of Concurrent Bandwidth Feedback on Learning the Lane-Keeping Task in a Driving Simulator

Objective: The aim of this study was to investigate whether concurrent bandwidth feedback improves learning of the lane-keeping task in a driving simulator. Background: Previous research suggests that bandwidth feedback improves learning and that off-target feedback is superior to on-target feedback. This study aimed to extend these findings for the lane-keeping task. Method: Participants without a driver’s license drove five 8-min lane-keeping sessions in a driver training simulator: three practice sessions, an immediate retention session, and a delayed retention session 1 day later. There were four experimental groups (n = 15 per group): (a) on-target, receiving seat vibrations when the center of the car was within 0.5 m of the lane center; (b) off-target, receiving seat vibrations when the center of the car was more than 0.5 m away from the lane center; (c) control, receiving no vibrations; and (d) realistic, receiving seat vibrations depending on engine speed. During retention, all groups were provided with the realistic vibrations. Results: During practice, on-target and off-target groups had better lane-keeping performance than the nonaugmented groups, but this difference diminished in the retention phase. Furthermore, during late practice and retention, the off-target group outperformed the on-target group. The off-target group had a higher rate of steering reversal and higher steering entropy than the nonaugmented groups, whereas no clear group differences were found regarding mean speed, mental workload, or self-reported measures. Conclusion: Off-target feedback is superior to on-target feedback for learning the lane-keeping task. Application: This research provides knowledge to researchers and designers of training systems about the value of feedback in simulator-based training of vehicular control.

Obstacle avoidance, visual detection performance, and eye-scanning behavior of glaucoma patients in a driving simulator: a preliminary study.

The objective of this study was to evaluate differences in driving performance, visual detection performance, and eye-scanning behavior between glaucoma patients and control participants without glaucoma. Glaucoma patients (n = 23) and control participants (n = 12) completed four 5-min driving sessions in a simulator. The participants were instructed to maintain the car in the right lane of a two-lane highway while their speed was automatically maintained at 100 km/h. Additional tasks per session were: Session 1: none, Session 2: verbalization of projected letters, Session 3: avoidance of static obstacles, and Session 4: combined letter verbalization and avoidance of static obstacles. Eye-scanning behavior was recorded with an eye-tracker. Results showed no statistically significant differences between patients and control participants for lane keeping, obstacle avoidance, and eye-scanning behavior. Steering activity, number of missed letters, and letter reaction time were significantly higher for glaucoma patients than for control participants. In conclusion, glaucoma patients were able to avoid objects and maintain a nominal lane keeping performance, but applied more steering input than control participants, and were more likely than control participants to miss peripherally projected stimuli. The eye-tracking results suggest that glaucoma patients did not use extra visual search to compensate for their visual field loss. Limitations of the study, such as small sample size, are discussed.

Vibrotactile Displays: A Survey With a View on Highly Automated Driving

The task of car driving is automated to an ever greater extent. In the foreseeable future, drivers will no longer be required to touch the steering wheel and pedals and could engage in non-driving tasks such as working or resting. Vibrotactile displays have the potential to grab the attention of the driver when the automation reaches its functional limits and the driver has to take over control. The aim of the present literature survey is to outline the key physiological and psychophysical aspects of vibrotactile sensation and to provide recommendations and relevant research questions regarding the use of vibrotactile displays for taking over control from an automated vehicle. Results showed that a distinction can be made between four dimensions for coding vibrotactile information (amplitude, frequency, timing, and location), each of which can be static or dynamic. There is a consensus that frequency and amplitude are less suitable for coding information than location and timing. Vibrotactile stimuli have been shown to be effective as simple warnings. However, vibrations can evoke annoyance, and providing vibrations in close spatial-temporal proximity might cause a lack of comprehension of the signal. We describe the sequential stages of a take-over process and argue that vibrotactile displays are a promising candidate for redirecting the attention of a distracted driver. Furthermore, vibrotactile displays hold potential for supporting cognitive processing and action selection while resuming control of an automated vehicle. Finally, we argue that multimodal feedback should be used to assist the driver in the take-over process.

The Effect of Haptic Support Systems on Driver Performance: A Literature Survey

A large number of haptic driver support systems have been described in the scientific literature. However, there is little consensus regarding the design, evaluation methods, and effectiveness of these systems. This literature survey aimed to investigate: (1) what haptic systems (in terms of function, haptic signal, channel, and supported task) have been experimentally tested, (2) how these haptic systems have been evaluated, and (3) their reported effects on driver performance and behaviour. We reviewed empirical research in which participants had to drive a vehicle in a real or simulated environment, were able to control the heading and/or speed of the vehicle, and a haptic signal was provided to them. The results indicated that a clear distinction can be made between warning systems (using vibrations) and guidance systems (using continuous forces). Studies typically used reaction time measures for evaluating warning systems and vehicle-centred performance measures for evaluating guidance systems. In general, haptic warning systems reduced the reaction time of a driver compared to no warnings, although these systems may cause annoyance. Guidance systems generally improved the performance of drivers compared to non-aided driving, but these systems may suffer from after-effects. Longitudinal research is needed to investigate the transfer and retention of effects caused by haptic support systems.

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.

Common Factor Analysis versus Principal Component Analysis: A Comparison of Loadings by Means of Simulations

Common factor analysis (CFA) and principal component analysis (PCA) are widely used multivariate techniques. Using simulations, we compared CFA with PCA loadings for distortions of a perfect cluster configuration. Results showed that nonzero PCA loadings were higher and more stable than nonzero CFA loadings. Compared to CFA loadings, PCA loadings correlated weakly with the true factor loadings for underextraction, overextraction, and heterogeneous loadings within factors. The pattern of differences between CFA and PCA was consistent across sample sizes, levels of loadings, principal axis factoring versus maximum likelihood factor analysis, and blind versus target rotation.

Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data.

The Pearson product–moment correlation coefficient (rp) and the Spearman rank correlation coefficient (rs) are widely used in psychological research. We compare rp and rs on 3 criteria: variability, bias with respect to the population value, and robustness to an outlier. Using simulations across low (N = 5) to high (N = 1,000) sample sizes we show that, for normally distributed variables, rp and rs have similar expected values but rs is more variable, especially when the correlation is strong. However, when the variables have high kurtosis, rp is more variable than rs. Next, we conducted a sampling study of a psychometric dataset featuring symmetrically distributed data with light tails, and of 2 Likert-type survey datasets, 1 with light-tailed and the other with heavy-tailed distributions. Consistent with the simulations, rp had lower variability than rs in the psychometric dataset. In the survey datasets with heavy-tailed variables in particular, rs had lower variability than rp, and often corresponded more accurately to the population Pearson correlation coefficient (Rp) than rp did. The simulations and the sampling studies showed that variability in terms of standard deviations can be reduced by about 20% by choosing rs instead of rp. In comparison, increasing the sample size by a factor of 2 results in a 41% reduction of the standard deviations of rs and rp. In conclusion, rp is suitable for light-tailed distributions, whereas rs is preferable when variables feature heavy-tailed distributions or when outliers are present, as is often the case in psychological research.