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There is a wide range of different driving simulator systems, which vary greatly in terms of cost as well as system characteristics. Higher fidelity simulators are often assumed to produce more valid results. While there are many studies that have compared simulator driving to real-world driving, to date there has been no large study comparing different simulator systems to each other and to real-world driving. Aiming at closing this gap, the present research offers an extensive comparison of six different driving simulators with the results of a previous real-world study. In terms of absolute validity, most of the simulators provided good results for distance to a vehicle in front and standard deviation of the lateral position, whereas the results for driving speed were inconsistent. Simulator fidelity appears to positively affect distance perception, although differences between higher fidelity simulators were generally small, and no real-world comparison data were available here. With respect to simulator sickness, a clear advantage of using a high fidelity simulator was found, while the effect size depended on the use case. In summary, the results suggest that different simulators are suitable for different use cases to different degrees, and the differences between simulators are not always related to higher simulator fidelity. The presented study can serve as a basis for understanding simulator requirements associated with different use cases. • Comparative validation study with N = 267 subjects. • Six driving simulators and five scenarios, including real-world comparison data. • Less simulator sickness in high-fidelity driving simulators. • No clear relationship of simulator fidelity and valid driving behavior. [ABSTRACT FROM AUTHOR]

Background: Patients are recommended not to drive for at least the first 24 h after endoscopy with propofol sedation. However, the evidence underlying these recommendations is scarce. We hypothesized that after endoscopic procedures performed under propofol sedation, the subject's driving ability was restored in less than 24 h. Methods: We prospectively enrolled thirty patients between 20 and 70 years possessing a legitimate driver's license scheduled for endoscopy at our hospital. The sample chosen was a convenience sample. Gastroscopy or colonoscopy was performed with propofol sedation. Before and after endoscopy, the investigator drove the subjects to the laboratory to assess their driving skills using a driving simulation system, which employs 3 driving scenarios designed by professional transportation researchers. The blood propofol concentration was estimated before endoscopy, and 2 and 4 h after endoscopy. The primary outcome was the time required for subjects to recover their driving ability after propofol sedation. The secondary outcome was the blood propofol concentration before and after endoscopic procedures under propofol anesthesia. Results: Thirty volunteers participated in the study and 18 of them completed all the interventions. In the low-risk S-curve scene, the mean acceleration, lane deviation, and number of deviations from the path at baseline (0.016 cm/s2, 42.50 cm, and 0.83, respectively) were significantly less than that at post-2 h (0.029 cm/s2, P = 0.001; 53.80 cm, P = 0.014; 2.06, P = 0.022). In the moderate-(overtaking) and high-risk (emergency collision avoidance) scenes, the tested parameters at baseline and post-2 h were statistically comparable. In the low-, moderate-, and high-risk scenes the tested parameters at baseline and post-4 h were statistically comparable. The total range of propofol was 120-280 mg.The mean blood concentration of propofol at post-2 h was 0.81 ± 0.40 µg/mL, and at post-4 h was below the limit of detection. Conclusion: After endoscopy performed under propofol sedation, subjects' driving abilities were completely restored at 4 h when tested on a simulator. [ABSTRACT FROM AUTHOR]

This article evaluates the driver's reaction times in a driving simulator environment. The research focused mainly on young drivers under the age of 26, who cause many accidents. Each participating driver provided basic information later used for mathematical-statistical analysis. The main advantage of driving simulators is limitless usage. It is possible to simulate situations that would be unacceptable in real road traffic. Therefore, this study is also able to examine drunk driving. The main goal of the article is to evaluate if gender, practice, or alcohol significantly affected the reaction time of 30 drivers. We also focused on drinking before driving for a smaller number of the drivers; ten of them performed driving under the influence of alcohol. For these mathematical-statistical purposes, we used a one-sample t-test, a paired-samples t-test, an independent-sample t-test, and a correlation analysis together with the assessment of its statistical significance. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study is to investigate how anticipatory driving is influenced by distraction. Background: The anticipation of future events in traffic can allow potential gains in recognition and response times. Anticipatory actions (i.e., control actions in preparation for potential traffic changes) have been found to be more prevalent among experienced drivers in simulator studies when driving was the sole task. Despite the prevalence of visual-manual distractions and their negative effects on road safety, their influence on anticipatory driving has not yet been investigated beyond hazard anticipation. Methods: A simulator experiment was conducted with 16 experienced and 16 novice drivers. Half of the participants were provided with a self-paced visual-manual secondary task presented on a dashboard display. Results: More anticipatory actions were observed among experienced drivers; experienced drivers also exhibited more efficient visual scanning behaviors as indicated by higher glance rates toward and percent times looking at cues that facilitate the anticipation of upcoming events. Regardless of experience, those with the secondary task displayed reduced anticipatory actions and paid less attention toward anticipatory cues. However, experienced drivers had lower odds of exhibiting long glances toward the secondary task compared to novices. Further, the inclusion of glance duration on anticipatory cues increased the accuracy of a model predicting anticipatory actions based on on-road glance durations. Conclusion: The results provide additional evidence to existing literature supporting the role of driving experience and distraction engagement in anticipatory driving. Application: These findings can guide the design of in-vehicle systems and guide training programs to support anticipatory driving. [ABSTRACT FROM AUTHOR]

Highlights • Lateral specific force scaling has a time-varying effect during curve driving simulation. • The lateral specific force can be scaled down further during the curve onset than during the remainder of the curve. • The lateral specific force can be scaled down by 30% during a curve's sustained part. • The lateral specific force can be scaled up by at least 30% during a curve's sustained part. Abstract In motion simulation, motion input scaling is often applied to deal with the limited motion envelopes of motion simulators. In this research, the time-varying effects of scaling the lateral specific force up or down during passive curve driving in a car driving simulation are investigated through a simulator experiment. It is concluded that lateral specific force scaling has a time-varying effect on the perceived fidelity of a curve-driving simulation. In particular, motion scaling during a curve entry is found to be less detrimental than motion scaling during a curve's sustained part and during the curve exit. [ABSTRACT FROM AUTHOR]

Driving is an integral aspect of many modern societies, and motor vehicle safety is an important public health issue. With advances in sensor technology, more and more driving data are being collected by researchers, insurers, and automobile companies, which has increased the need and opportunities for statisticians to be involved in driving research. This report discusses several practical and statistical challenges in driver-level studies, including the process of defining meaningful driving metrics, issues related to "Big Data" aspects of driving research, and the principle of reproducible research. [ABSTRACT FROM AUTHOR]

Highlights • Driving simulators are search tools which allow the study of driver behavior in various driving scenarios, quickly, safely and economically. • This work comprised the experiment in the simulator to measure the perception of signaling within the virtual environment. Abstract Road accidents are a major societal issue for every country. The purpose of this paper is to assess and to analyze how drivers perceive traffic signals within a simulated environment direction, supported the use of an eye tracking system. Driving simulators are search tools which allow the study of driver behavior in various driving scenarios, quickly, safely and economically. This manuscript comprised the experiment in the driver simulator to measure the perception of signaling within the virtual environment in Brazil. In the experiment, 21 drivers went on a stretch of 10 km of a federal highway with 31 traffic signals, to measure the distance perception, number of fixations and the observation time signaling, as well as the variation in velocity after perception. The perception signaling within the virtual environment was similar to that reported in the literature for roads studies: on average the drivers perceived three signals, the observation time was 360 ms, the distance perception was 100 m and only the perception of velocity limits was relevant in driver behavior. [ABSTRACT FROM AUTHOR]

Abstract: Previous electroencephalography studies on anger suggest that greater left than right frontal cortical activity is associated with approach motivation of anger. Our previous study showed that greater left‐superior frontal activation of electroencephalography was associated with subjective anger during a traffic jam simulation that forced participants to maintain a slower speed than expected in elderly adults, but not in young adults. We subsequently observed similar left‐superior frontal brain activity using near‐infrared spectroscopy (NIRS) in elderly adults in the same driving situation. Using NIRS, the present study demonstrated that the elderly, but not young adults, exhibited left‐superior brain activity in the front‐dorsolateral area when they were forced to stop four times at a red traffic light in a driving simulator. Driving through the same intersections with green lights did not elicit brain activation in either age group. After four red lights, but not after four green lights, a yellow light induced left‐superior brain activity in elderly adults. This asymmetric brain activity is associated with Trail Making Test score, which reflects executive functioning. These results are discussed with regard to the inhibitory potential of aged adults. [ABSTRACT FROM AUTHOR]

In this paper, a sonification algorithm for developing the off-road models for driving simulators, is proposed. The aim of this algorithm is to overcome difficulties of heuristics identification which are best suited to a particular off-road profile built by measurements. The sonification algorithm is based on the stochastic polynomial chaos analysis suitable in solving equations with random input data. The fluctuations are generated by incomplete measurements leading to inhomogeneities of the cross-sectional curves of off-roads before and after deformation, the unstable contact between the tire and the road and the unreal distribution of contact and friction forces in the unknown contact domains. The approach is exercised on two particular problems and results compare favorably to existing analytical and numerical solutions. The sonification technique represents a useful multiscale analysis able to build a low-cost virtual reality environment with increased degrees of realism for driving simulators and higher user flexibility. [ABSTRACT FROM AUTHOR]

This article first develops an integrated traffic-driving-networking simulator (ITDNS) intended for the design and evaluation of cyber transportation systems (CTS) and connected vehicle (CV) applications. The ITDNS allows a human driver to control a subject vehicle, in a virtual environment, that is capable of communicating with other vehicles and the infrastructure with CTS messages. The challenges associated with the integration of the three simulators, and how those challenges were overcome, are discussed. As an application example, an eco-signal system, which recommends the approach speed for vehicles approaching the intersection so as to minimize fuel consumption and emissions, was implemented in the ITDNS. Test drivers were then asked to virtually drive through a signalized corridor twice, one time with the eco-signal system in place and another without the system. Thanks to the human-in-the-loop component of ITDNS, the research was able to evaluate the likely benefits of the eco-signal system, while accounting for the response of human drivers to the recommended speed profiles. Moreover, the study compared the energy consumption and emission production rates of human-controlled vehicles’ approach trajectories to the rates associated with “idealistic” trajectories that may be attainable via vehicle automation. With respect to ITDNS, the study demonstrates the unique advantages of the simulator and the broad range of applications it can address. Regarding the eco-signal application example, preliminary results demonstrate the potential of the concept to result in tangible reductions of around 9% for energy consumption, 18% for carbon monoxide, and 25% for nitrogen oxides emissions. Moreover, the application eliminated hard accelerations and decelerations maneuvers, and thus may have an additional positive safety impact. [ABSTRACT FROM AUTHOR]

We examined the crash avoidance behaviors of older and middle-aged drivers in reaction to six simulated challenging road events using two different driving simulator platforms. Thirty-five healthy adults aged 21–36 years old ( M = 28.9 ± 3.96) and 35 healthy adults aged 65–83 years old ( M = 72.1 ± 4.34) were tested using a mid-level simulator, and 27 adults aged 21–38 years old ( M = 28.6 ± 6.63) and 27 healthy adults aged 65–83 years old ( M = 72.7 ± 5.39) were tested on a low-cost desktop simulator. Participants completed a set of six challenging events varying in terms of the maneuvers required, avoiding space given, directional avoidance cues, and time pressure. Results indicated that older drivers showed higher crash risk when events required multiple synchronized reactions. In situations that required simultaneous use of steering and braking, older adults tended to crash significantly more frequently. As for middle-aged drivers, their crashes were attributable to faster driving speed. The same age-related driving patterns were observed across simulator platforms. Our findings support the hypothesis that older adults tend to react serially while engaging in cognitively challenging road maneuvers. [ABSTRACT FROM AUTHOR]

In driving simulation, a scenario includes definitions of the road environment, the traffic situation, simulated vehicles’ interactions with the participant’s vehicle and measurements that need to be collected. The scenarios need to be designed in such a way that the research questions to be studied can be answered, which commonly imply exposing the participant for a couple of predefined specific situations that has to be both realistic and repeatable. This article presents an integrated algorithm based on Dynamic Actor Preparation and Automated Action Planning to control autonomous simulated vehicles in the simulation in order to generate predefined situations. This algorithm is thus able to plan driving actions for autonomous vehicles based on specific tasks with relevant contextual information as well as handling longitudinal transportation of simulated vehicles based on the contextual information in an automated manner. The conducted experiment shows that the algorithm is able to guarantee repeatability under autonomous traffic flow. The presented algorithm can benefit not only the driving simulation community, but also relevant areas, such as autonomous vehicle and in-vehicle device design by providing them with an algorithm for target pursue and driving task accomplishment, which can be used to design a human-vehicle cooperation system in the coming era of autonomous driving. [ABSTRACT FROM AUTHOR]

Modeling scenarios on driving simulators is a complex and difficult task for end-users because they do not have the skills necessary to program the scenarios. In this paper, we present a user-centered architecture in which we have split the scenario modeling interface into 3 sub-interfaces (Template Builder, Experiment Builder, Experiment Interface) based on the user skill. The concept is tested with a panel of end-users, with fair results in terms of performance and subjective judgment. [ABSTRACT FROM AUTHOR]

Highlights: [•] Understanding simulator capability and comparing options is important. [•] For that reason a driving simulator classification method arises. [•] In this research study, a classification method for driving simulators is aimed. [•] In the proposed method, the driving simulator general characteristics were considered. [•] The criteria were adapted from helicopter flight simulation training device standards. [Copyright &y& Elsevier]

Simulators offer an alternative medium to investigate issues with driving and to conduct vehicle control and situation awareness tests. To ensure transferability of research findings, drivers' behaviour and reactions within vehicle simulators should be comparable to those observed on real roads. However, various questions relating to simulator validity have been raised, often focused on physical dimensions of fidelity (does the simulator look and feel like the real-world?), rather than psycho-physiological properties (does it replicate the relevant emotional and cognitive factors?). To address whether drivers in simulators behave and emotionally express themselves in response to perceived hazards as would be expected in the real-world, 24 drivers - 12 in a low fidelity and 12 in medium-fidelity simulator - drove on a rural road and encountered an emergency braking event (a vehicle pulling out from a parked position) towards the end of the drive. Drivers' subjective responses were measured through an Emotion Questionnaire, nonverbal expressions (facial, vocal, gestures and postural movements) of emotion response and physiological measures of Heart-Rate (HR), Respiration-Rate (RR) and Breathing-Wave Amplitude (BWA). Drivers' subjective responses to the emotion items showed higher ratings on the negative emotions of anger, fear, disgust, sadness and surprise during the emergency braking event (the hazard phase) compared to the non-hazard phase. Similar results were shown for drivers' HR, RR and BWA measures. Furthermore, drivers exhibited realistic reactions and emotional gestures e.g. withdrawal of the head back towards the vehicle head restraint, and tensing of arms as if bracing for an impact. Facial expressions revealed a continuity of negative and adaptive emotional expressions. Results also showed comparability across measures taken from both simulators and the literature for equivalent on-road situations. [ABSTRACT FROM AUTHOR]

Abstract: Background: Cannabis and alcohol are the most popular drugs amongst recreational users, and most prevalent in injured and deceased drivers. Clarification of the interactive effects of these drugs upon driving behaviour is critical for reducing drug-related road deaths. Objectives: The current study had two objectives, to examine the effects of cannabis and alcohol on driving performance, and identify if any differences between the effects of cannabis and alcohol on driving performance exist between regular cannabis users and non-regular cannabis users. Methods: The project involved 80 participants (49 male, 31 female) who were abstinent recreational users of alcohol and marijuana. They participated in six experimental sessions that involved the consumption of cannabis cigarettes containing no THC, 1.8% THC or 3% THC together with the consumption of alcohol to obtain either 0% BAC, 0.03% BAC or 0.05% BAC. The six sessions were double-blind, counter-balanced, placebo-controlled and medically supervised. Forty participants were allocated to the cannabis with low alcohol (0.03% BAC) group, and 40 participants were allocated to the cannabis with high alcohol (0.05% BAC) group. Driving simulator performance was assessed at 20min post-drug administration and blood samples were taken before and after driving. Results: Driving simulator performance was more impaired in the THC and alcohol combined conditions. Consistent with past research, the level of THC detected in blood is higher when THC is consumed with alcohol, than when cannabis is consumed alone, and regular cannabis users returned higher levels of THC in plasma than non-regular users. Generally, regular cannabis users displayed more driving errors than non-regular cannabis users. [Copyright &y& Elsevier]

Visualization of highway traffic environments in virtual reality plays a key role on fidelity of simulation and validity of driving behaviors in driving simulator studies. This paper describes a procedure to replicate a signalized intersection with many complex features into a driving simulator's 3-D databases through building a graphical visual database, constructing a road motion database, and creating simulated traffic. The validity of the visualization was assessed via the comparison of the drivers' speeds in the simulator and the speed data at the real intersection. It was found that both speed data follow normal distributions and have equal means for each intersection approach; however, that the speeds measured in the driving simulator have a larger variability than those measured in the field. The users' subjective evaluation results indicated that 92% subjects could recognize the simulated intersection in the driving simulator experiment. Therefore, the strategy of geo-specific environment modeling would be useful for studying driving behaviors in virtual environments. [ABSTRACT FROM AUTHOR]

Abstract: Autonomous vehicles can be used to create realistic simulations of surrounding vehicles in driving simulators. However, the use of autonomous vehicles makes it difficult to ensure reproducibility between subjects. In this paper, an effort is made to solve the problem by combining autonomous vehicles and controlled events. A controlled event can be compared to a theatre play. The aim is to achieve the same initial play conditions for each subject, which can be problematic since the traffic situation around the subject will be dependent upon each subject’s actions while driving in autonomous traffic. This paper presents an algorithm that achieves the transition from autonomous traffic to a predefined start condition for a play. The algorithm has been tested in the Swedish National Road and Transport Research Institute (VTI) driving simulator III with promising results. In most of the cases we examined the algorithm could reconstruct the specified start condition and conduct the transition from autonomous to controlled mode in a inconspicuous way. Some problems were observed regarding moving unwanted vehicles away from the closest area around the simulator vehicle, and this part of the algorithm has to be enhanced. The experiment also showed that the subjects drove faster in the presence of controlled everyday life traffic normally used in the VTI driving simulator than in autonomous traffic. [Copyright &y& Elsevier]

The paper presents the general design of a driving simulator and a brief overview of selected concepts in its construction. Three types of simulators have been discussed: simple for training purposes, mid-level and world-class simulators. Exemplary applications in testing behaviour of the driver during normal driving conditions have been listed and in preaccidental situations. A possibility has been mentioned to use driving simulators during basic training and supplementary training of drivers, especially in the context of recommendations of the European Directive 2003/59/EC, which allows the use of top-of-the-range simulator simulators in the initial qualification and periodical training. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To determine the effects of obstructive sleep apnea (OSA) on visual vigilance during simulated automobile driving. Methods: Twenty-five drivers with OSA and 41 comparison drivers participated in an hour-long drive in a high-fidelity driving simulator. Drivers responded to light targets flashed at seven locations across the forward horizon. Dependent measures were percent correct [hit rate (HR)] and reaction time (RT). Self-assessment of sleepiness used the Stanford Sleepiness Scale (SSS) before and after the drive and the Epworth Sleepiness Scale (ESS). Results: OSA drivers showed reduced vigilance based on lower HR than comparison drivers, especially for peripheral targets (80.7±14.8% vs. 86.7±8.8%, P=.03). OSA drivers were sleepier at the end of the drive than comparison drivers (SSS=4.2±1.2 vs. 3.6±1.2, P=.03), and increased sleepiness correlated with decreased HR only in those with OSA (r=−0.49, P=.01). Lower HR and higher post-drive SSS predicted greater numbers of driving errors in all subjects. Yet, ESS, predrive SSS, and most objective measures of disease severity failed to predict driving and vigilance performance in OSA. Conclusions: Reduced vigilance for peripheral visual targets indicates that OSA drivers have restriction of their effective field of view, which may partly explain their increased crash risk. This fatigue-related decline in attention is predicted by increased subjective sleepiness during driving. These findings may suggest a means of identifying and counseling high-risk drivers and aid in the development of in-vehicle alerting and warning devices. [Copyright &y& Elsevier]

Advanced driving simulators have a potential to be utilized to assess crash risks of driving behaviors, traffic surroundings, and highway designs. This study focused on investigating if drivers' stop/go decisions due to signal change in the simulator's virtual reality can be used to assess rear-end crash risk at the signalized intersection. A signalized intersection with as many important features (including roadway geometries, traffic control devices, intersection surroundings, and buildings) was replicated into a high-fidelity driving simulator. Using the virtual signalized intersection, a driving simulator experiment was conducted to test driver's stop/go decisions at two approaches of the intersection that respectively showed higher and lower rear-end crash risks in the crash history analysis. The experiment results showed that the variability in drivers' stop/go decisions at the higher crash-risk location is higher than that at the lower crash-risk location. Further, through modeling rear-end conflicts based on driver's stop/go probability as a function of potential time to intersection, it was found that the rear-end crash tendency at the two locations displayed by the driver's stop/go behavior in driving simulator is consistent with the finding from the trend in crash history analysis. This research supported that driver's stop/go behavior in a driving simulator can be utilized to assess rear-end crash risk at signalized intersections to seek effective engineering countermeasures to lower crash rates for the high-risk locations. [ABSTRACT FROM AUTHOR]

In this paper, we designed from scratch, realized, and characterized a six-channel EEG wearable headband for the measurement of stress-related brain activity during driving. The headband transmits data over WiFi to a laptop, and the rechargeable battery life is 10 h of continuous transmission. The characterization manifested a measurement error of 6 μ V in reading EEG channels, and the bandwidth was in the range [0.8, 44] Hz, while the resolution was 50 nV exploiting the oversampling technique. Thanks to the full metrological characterization presented in this paper, we provide important information regarding the accuracy of the sensor because, in the literature, commercial EEG sensors are used even if their accuracy is not provided in the manuals. We set up an experiment using the driving simulator available in our laboratory at the University of Udine; the experiment involved ten volunteers who had to drive in three scenarios: manual, autonomous vehicle with a "gentle" approach, and autonomous vehicle with an "aggressive" approach. The aim of the experiment was to assess how autonomous driving algorithms impact EEG brain activity. To our knowledge, this is the first study to compare different autonomous driving algorithms in terms of drivers' acceptability by means of EEG signals. The obtained results demonstrated that the estimated power of beta waves (related to stress) is higher in the manual with respect to autonomous driving algorithms, either "gentle" or "aggressive". [ABSTRACT FROM AUTHOR]

This paper details the design of two advanced driver assistance systems from concept to fully integrated solutions that are installed and tested on a driving simulator. The systems were tuned and validated using offline simulations before they were installed on the Leeds driving simulator. The simulator is equipped with a large amplitude motion base that is able to generate realistic sustained accelerations. The work forms a part of the effects of automated systems on safety project that is funded by the EPSRC. This simulator study acts a pilot study for the project. Drivers were subjected to a range of scenarios, some of which required evasive action. The two systems, adaptive cruise control and a lane keeping system, were tested in isolation, while the performance of each system and the driver were monitored. The driver was then asked to complete questionnaires on each controller. The nature of this pilot study meant that the sample size was small, but the results still demonstrate some interesting trends. The results of assisted and non-assisted driving were compared and the merits of each system were discussed. [ABSTRACT FROM AUTHOR]

Abstract: This study examined if individuals who are at increased risk for drowsy driving because of obstructive sleep apnea syndrome (OSAS), have impairments in driving performance in the moments during microsleep episodes as opposed to during periods of wakefulness. Twenty-four licensed drivers diagnosed with OSAS based on standard clinical and polysomnographic criteria, participated in an hour-long drive in a high-fidelity driving simulator with synchronous electroencephalographic (EEG) recordings for identification of microsleeps. The drivers showed significant deterioration in vehicle control during the microsleep episodes compared to driving performance in the absence of microsleeps on equivalent segments of roadway. The degree of performance decrement correlated with microsleep duration, particularly on curved roads. Results indicate that driving performance deteriorates during microsleep episodes. Detecting microsleeps in real-time and identifying how these episodes of transition between wakefulness and sleep impair driver performance is relevant to the design and implementation of countermeasures such as drowsy driver detection and alerting systems that use EEG technology. [Copyright &y& Elsevier]

Drivers with obstructive sleep apnea syndrome (OSAS) have an increased risk of motor vehicle crashes. Unfortunately, neither clinical nor polysomnographic features allow clinicians to reliably identify high-risk drivers. One potential means of identifying these drivers is with the use of driving simulators. Several investigators have shown that OSAS patients perform worse than healthy control drivers and results from our studies have demonstrated declines in driving performance during EEG-defined "microsleeps." The use of simulators, and in-vehicle detection and alerting devices may mitigate some of the suffering caused by these crashes. [ABSTRACT FROM AUTHOR]

This paper describes the design of a two channels electrodermal activity (EDA) sensor and two channels electrocardiogram (ECG) sensor. The EDA sensors acquire data on the hands and transmit them to the ECG sensor with wireless WiFi communication for increased wearability. The sensors system acquires two EDA channels to improve the removal of motion artifacts that take place if EDA is measured on individuals who need to move their hands in their activities. The ECG channels are acquired on the chest and the ECG sensor is responsible for aligning the two ECG traces with the received packets from EDA sensors; the ECG sensor sends via WiFi the aligned packets to a laptop for real time plot and data storage. The metrological characterization showed high-level performances in terms of linearity and jitter; the delays introduced by the wireless transmission from EDA to ECG sensor have been proved to be negligible for the present application. [ABSTRACT FROM AUTHOR]