measuring-the-switch-cost-of-smartphone-use-while-walking

Measuring the Switch Cost of Smartphone Use While Walking

This paper presents a study protocol to measure the task-switching cost of using a smartphone while walking. This method involves having participants walk ...

HEC Montréal

This research sets out to estimate the effects of vehicle incompatibility on the risk of death or major injury to drivers involved in two-vehicle collisions. Based on data for 2,999,395 drivers, logistic regression was used to model the risk of driver death or major injury (defined has being hospitalized). Our analyses show that pickup trucks, minivans and sport utility vehicles (SUVs) are more aggressive than cars for the driver of the other vehicle and more protective for their own drivers. The effect of the pickups is more pronounced in terms of aggressivity. The point estimates are comparable to those in the Toy and Hammitt study [Toy, E.L., Hammitt, J.K., 2003. Safety impacts of SUVs, minivans, and pickup trucks in two-vehicle crashes. Risk Analysis 23, 641-650], but, in contrast to that study, we are now able to establish that a greater number of these effects are statistically significant with a larger sample size. Like vehicle mass and type, other characteristics of drivers and the circumstances of the collision influence the driver's condition after impact. Male drivers, older drivers, drivers who are not wearing safety belts, collisions occurring in a higher speed zone and head-on collisions significantly increase the risk of death. Except for the driver's sex, all of these categories are also associated with an increased risk of death or of being hospitalized after being involved in a two-vehicle collision. For this risk, a significant increase is associated with female drivers.

Safety impacts due to the incompatibility of SUVs, minivans, and pickup trucks in two-vehicle collisions.

Passive Brain-Computer interfaces (pBCIs) are a human-computer communication tool where the computer can detect from neurophysiological signals the current mental or emotional state of the user. The system can then adjust itself to guide the user toward a desired state. One challenge facing developers of pBCIs is that the system's parameters are generally set at the onset of the interaction and remain stable throughout, not adapting to potential changes over time such as fatigue. The goal of this paper is to investigate the improvement of pBCIs with settings adjusted according to the information provided by a second neurophysiological signal. With the use of a second signal, making the system a hybrid pBCI, those parameters can be continuously adjusted with dynamic thresholding to respond to variations such as fatigue or learning. In this experiment, we hypothesize that the adaptive system with dynamic thresholding will improve perceived game experience and objective game performance compared to two other conditions: an adaptive system with single primary signal biocybernetic loop and a control non-adaptive game. A within-subject experiment was conducted with 16 participants using three versions of the game Tetris. Each participant plays 15 min of Tetris under three experimental conditions. The control condition is the traditional game of Tetris with a progressive increase in speed. The second condition is a cognitive load only biocybernetic loop with the parameters presented in Ewing et al. (2016). The third condition is our proposed biocybernetic loop using dynamic threshold selection. Electroencephalography was used as the primary signal and automatic facial expression analysis as the secondary signal. Our results show that, contrary to our expectations, the adaptive systems did not improve the participants' experience as participants had more negative affect from the BCI conditions than in the control condition. We endeavored to develop a system that improved upon the authentic version of the Tetris game, however, our proposed adaptive system neither improved players' perceived experience, nor their objective performance. Nevertheless, this experience can inform developers of hybrid passive BCIs on a novel way to employ various neurophysiological features simultaneously.

Dynamic Threshold Selection for a Biocybernetic Loop in an Adaptive Video Game Context.

Texting while walking has been highlighted as a dangerous behavior that leads to impaired judgment and accidents. This impairment could be due to task switching which involves activation of the present task and the inhibition of the previous task. However, the relative contributions of these processes and their brain activity have not yet been studied. We addressed this gap by asking participants to discriminate the orientation of an oncoming human shape in a virtual environment while they were: i) walking on a treadmill, or ii) texting while walking on a treadmill. Participants' performance (i.e., correctly identifying if a walker would pass them to their left or right) and electroencephalography (EEG) data was collected. Unsurprisingly, we found that participants performed better while they were only walking than when texting while walking. However, we also found that the diminished performance is differently related to task set inhibition and task set activation in the two conditions. The alpha oscillations, which can be used as an index of task inhibition, have a significantly different relation to performance in the two conditions, the relation being negative when subjects are texting. This may indicate that the more inhibition is needed, the more the performance is affected by texting. To our knowledge, this is the first study to investigate the brain signature of task switching in texting while walking. This finding is the first step in identifying the source of impaired judgment in texting pedestrians and in finding viable solutions to reduce the risks.

Texting while walking: An expensive switch cost.

The goal of this study was to determine if using a standing desk would affect the productivity of workers, based on the type of work they perform.

Does Reducing Sedentarity With Standing Desks Hinder Cognitive Performance?

Random forests for homogeneous and non-homogeneous Poisson processes with excess zeros.

We report results of a study that utilizes a BCI to drive an interactive interface countermeasure that allows users to self-regulate sustained attention while performing an ecologically valid, long-duration business logistics task. An engagement index derived from EEG signals was used to drive the BCI while fNIRS measured hemodynamic activity for the duration of the task. Participants ( = 30) were split into three groups (1) no countermeasures (NOCM), (2) continuous countermeasures (CCM), and (3) event synchronized, level-dependent countermeasures (ECM). We hypothesized that the ability to self-regulate sustained attention through a neurofeedback mechanism would result in greater task engagement, decreased error rate and improved task performance. Data were analyzed by wavelet coherence analysis, statistical analysis, performance metrics and self-assessed cognitive workload via RAW-TLX. We found that when the BCI was used to deliver continuous interface countermeasures (CCM), task performance was moderately enhanced in terms of total 14,785 (σ = 423) and estimated missed sales 7.46% (σ = 1.76) when compared to the NOCM 14,529 (σ = 510), 9.79% (σ = 2.75), and the ECM 14,180 (σ = 875), 9.62% (σ = 4.91) groups. An "actions per minute" (APM) metric was used to determine interface interaction activity which showed that overall the CCM and ECM groups had a higher APM of 3.460 ( = 0.140) and 3.317 ( = 0.139) respectively when compared with the NOCM group 2.65 ( = 0.097). Statistical analysis showed a significant difference between ECM - NOCM and CCM - NOCM ( < 0.001) groups, but no significant difference between the ECM - CCM groups. Analysis of the RAW-TLX scores showed that the CCM group had lowest total score 7.27 (σ = 3.1) when compared with the ECM 9.7 (σ = 3.3) and NOCM 9.2 (σ = 3.4) groups. No statistical difference was found between the RAW-TLX or the subscales, except for self-perceived performance ( < 0.028) comparing the CCM and ECM groups. The results suggest that providing a means to self-regulate sustained attention has the potential to keep operators engaged over long periods, and moderately increase on-task performance while decreasing on-task error.

Toward a Hybrid Passive BCI for the Modulation of Sustained Attention Using EEG and fNIRS.

Distracted walking is an ever-increasing problem. Studies have already shown that using a smartphone while walking impairs attention and increases the risk of accidents. This study seeks to determine if smartphone-addiction proneness magnifies the risks of using a smartphone while walking. In an experimental design, participants, while walking on a treadmill and engaged in a smartphone task, were required to switch tasks by responding to an external stimulus, i.e., determining the direction of movement of a point-light walker. Participants were chosen to cover a range of smartphone-addiction proneness. Four smartphone-use conditions were simulated: a control condition with no smartphone-use, an individual conversation condition, a gaming condition, and a group conversation condition. Our results show that using a smartphone while walking decreases accuracy and increases the number of missed stimuli. Moreover, participants with higher smartphone-addiction proneness scores were also prone to missing more stimuli, and this effect was found regardless of experimental condition. The effect of the smartphone task on accuracy and the number of missed stimuli was mediated by the emotional arousal caused by the smartphone task. Smartphone-addiction proneness was positively correlated with a declared frequency of smartphone use while walking. Furthermore, of all the smartphone tasks, the gaming condition was found to be the most distracting.

Marc Fredette

HEC Montréal

Measuring the Switch Cost of Smartphone Use While Walking