Evaluation of older driver head functional range of motion using portable immersive virtual reality

Driving Difficulties and Preferences of Advanced Driver Assistance Systems by Older Drivers With Central Vision Loss

Purpose

The purpose of this study was to investigate driving difficulties and Advanced Driver Assistance Systems (ADAS) use and preferences of drivers with and without central vision loss (CVL).

Methods

Fifty-eight drivers with CVL (71 ± 13 years) and 68 without (72 ± 8 years) completed a telephone questionnaire. They rated their perceived driving difficulty and usefulness of technology support in 15 driving situations under good (daytime) and reduced visibility conditions, and reported their use experience and preferences for 12 available ADAS technologies.

Results

Drivers with CVL reported more difficulty (P = 0.002) and greater usefulness of technology support (P = 0.003) than non-CVL drivers, especially in reduced visibility conditions. Increased driving difficulty was associated with higher perceived technology usefulness (r = 0.34, P < 0.001). Dealing with blind spot road users, glare, unexpected pedestrians, and unfamiliar areas were perceived as the most difficult tasks that would benefit from technology support. Drivers with CVL used more advanced ADAS features than non-CVL drivers (P = 0.02), preferred to own the blind spot warning, pedestrian warning, and forward collision avoidance systems, and favored ADAS support that provided both information and active intervention. The perceived benefits of and willingness to own ADAS technologies were high for both groups.

Conclusions

Drivers with CVL used more advanced ADAS and perceived greater usefulness of driver assistance technology in supporting difficult driving situations, with a strong preference for collision prevention support.

Translational Relevance

This study highlights the specific technology needs and preferences of older drivers with CVL, which can inform future ADAS development, evaluation, and training tailored to this group.

Enhancing Driving Ability in Older Adults through Health Exercises and Physical Activity: A Randomized Controlled Trial

The global rise in the aging driving population has heightened concerns about traffic incidents involving this demographic. Beyond transportation, automobiles represent a vital lifeline for older adults, fostering social activities and influencing their health-related quality of life. This study explores improving and sustaining driving ability among older adults with anticipated declines through health-conscious exercises. Sixty-eight participants were randomly allocated into two groups. The exercise-oriented group (E-group) engaged in twelve 90 min health and exercise sessions over twelve weeks, while the control group (C-group) maintained their regular daily routines and did not receive any specific interventions during this period. The focal point of assessment was driving ability, as evaluated by a person using a real car on public roads without using a simulator. Driving ability and physical fitness were assessed before the intervention in both groups. Post-intervention measurements occurred twelve weeks after the initial gauging, encompassing both cohorts. Comparative analysis of pre- and post-intervention changes was executed between the two groups. The E-group demonstrated improved overall driving ability compared to the C-group. The results suggest that healthy exercise and physical activity may maintain and enhance driving ability for older adults.

Head Scanning Behavior Predicts Hazard Detection Safety Before Entering an Intersection

OBJECTIVE

We conducted a driving simulator study to investigate scanning and hazard detection before entering an intersection.

BACKGROUND

Insufficient scanning has been suggested as a factor contributing to intersection crashes. However, little is known about the relative importance of the head and eye movement components of that scanning in peripheral hazard detection.

METHODS

Eleven older (mean 67 years) and 18 younger (mean 27 years) current drivers drove in a simulator while their head and eye movements were tracked. They completed two city drives (42 intersections per drive) with motorcycle hazards appearing at 16 four-way intersections per drive.

RESULTS

Older subjects missed more hazards (10.2% vs. 5.2%). Failing to make a scan with a substantial head movement was the primary reason for missed hazards. When hazards were detected, older drivers had longer RTs (2.6s vs. 2.3s), but drove more slowly; thus, safe response rates did not differ between the two groups (older 83%; younger 82%). Safe responses were associated with larger (28.8° vs. 20.6°) and more numerous (9.4 vs. 6.6) gaze scans. Scans containing a head movement were stronger predictors of safe responses than scans containing only eye movements.

CONCLUSION

Our results highlight the importance of making large scans with a substantial head movement before entering an intersection. Eye-only scans played little role in detection and safe responses to peripheral hazards.

APPLICATION

Driver training programs should address the importance of making large scans with a substantial head movement before entering an intersection.

Head-Mounted Display for Clinical Evaluation of Neck Movement Validation with Meta Quest 2

Neck disorders have a significant impact on people because of their high incidence. The head-mounted display (HMD) systems, such as Meta Quest 2, grant access to immersive virtual reality (iRV) experiences. This study aims to validate the Meta Quest 2 HMD system as an alternative for screening neck movement in healthy people. The device provides data about the position and orientation of the head and, thus, the neck mobility around the three anatomical axes. The authors develop a VR application that solicits participants to perform six neck movements (rotation, flexion, and lateralization on both sides), which allows the collection of corresponding angles. An InertiaCube3 inertial measurement unit (IMU) is also attached to the HMD to compare the criterion to a standard. The mean absolute error (MAE), the percentage of error (%MAE), and the criterion validity and agreement are calculated. The study shows that the average absolute errors do not exceed 1° (average = 0.48 ± 0.09°). The rotational movement's average %MAE is 1.61 ± 0.82%. The head orientations obtain a correlation between 0.70 and 0.96. The Bland-Altman study reveals good agreement between the HMD and IMU systems. Overall, the study shows that the angles provided by the Meta Quest 2 HMD system are valid to calculate the rotational angles of the neck in each of the three axes. The obtained results demonstrate an acceptable error percentage and a very minimal absolute error when measuring the degrees of neck rotation; therefore, the sensor can be used for screening neck disorders in healthy people.

A Systematic Review of Virtual Reality Applications for Automated Driving: 2009–2020

While virtual reality (VR) interfaces have been researched extensively over the last decades, studies on their application in vehicles have only recently advanced. In this paper, we systematically review 12 years of VR research in the context of automated driving (AD), from 2009 to 2020. Due to the multitude of possibilities for studies with regard to VR technology, at present, the pool of findings is heterogeneous and non-transparent. We investigated N = 176 scientific papers of relevant journals and conferences with the goal to analyze the status quo of existing VR studies in AD, and to classify the related literature into application areas. We provide insights into the utilization of VR technology which is applicable at specific level of vehicle automation and for different users (drivers, passengers, pedestrians) and tasks. Results show that most studies focused on designing automotive experiences in VR, safety aspects, and vulnerable road users. Trust, simulator and motion sickness, and external human-machine interfaces (eHMIs) also marked a significant portion of the published papers, however a wide range of different parameters was investigated by researchers. Finally, we discuss a set of open challenges, and give recommendation for future research in automated driving at the VR side of the reality-virtuality continuum.

Effect of Virtual Reality Exercises on the Cognitive Status and Dual Motor Task Performance of the Aging Population

Aging is a global phenomenon affecting numerous developed and developing countries. During this process, the functional state of the body, especially the cognitive state, declines. This research investigated the impact of virtual reality exercises on the cognitive status and dual-task performance in the elderly of Tabriz city, Iran. Forty men with a mean age of 71.5 were selected and assigned to either the experimental (n = 20) or control groups (n = 20). Both groups completed the Mini-Mental State Examination for cognitive status. The pre-test was performed through the Timed Up and Go test (TUG) along with a countdown of numbers. Then, the experimental group practiced virtual driving for six weeks, while the control group received no treatment. After the treatment, both groups completed the post-test. At each stage, the test was performed as a dual motor task as well. Data were analyzed using the paired t-test and the independent sample t-test to show the intra-group and inter-group differences, respectively. The results showed a significant improvement in the cognitive status and dual-task performance of the elderly men after the six-week training period, which was also significant compared to the control group. Virtual reality driving can be used to improve the cognitive status and dual task performance of elderly men.

Can't simply roll it out: Evaluating a real-world virtual reality intervention to reduce driving under the influence

Driving under the influence (DUI) increases the risk of crashes. Emerging technologies, such as virtual reality (VR), represent potentially powerful and attractive tools for the prevention of risky behaviours, such as DUI. Therefore, they are embraced in prevention efforts with VR interventions primed to grow in popularity in near future. However, little is known about the actual effectiveness of such DUI-targeting VR interventions. To help fill the knowledge gap, this study explored the effects of one VR intervention as delivered in the real world. Using pre and post test design, including an intervention group (n = 98) and a control group (n = 39), the intervention evaluation examined young drivers’ (aged 18 to 25, no known history of DUI) intention and self-reported behaviour three months after the intervention as compared to the baseline. The results did not provide evidence for statistically significant effects of the VR intervention on self-reported DUI behaviour during the three months post intervention and DUI intention at three months post intervention. Such results might be due to the fact that the recruited participants generally self-reported little DUI behaviour, i.e. positively changing behaviour that is already positive is inherently challenging. Nevertheless, the results question the utility of funding the roll-out of arguably attractive technologies without a thorough understanding of their effectiveness in particular settings. To improve the potential for future positive outcomes of such interventions, we provide suggestions on how VR software might be further developed and, subsequently, leveraged in future research to improve the likelihood for behavioural change, e.g. by collecting, analysing and presenting objective driving performance data. Alternatively, future endeavours might focus on participants with known DUI history and examine the effects of the VR intervention for this particular higher-risk group.

Does Practicing with a Virtual Reality Driving Simulator Improve Spatial Cognition in Older Adults? A Pilot Study

Memory, cognition, executive functioning, and spatial cognition loss are prevalent in the normal aging process, but these impairments are observed more extensively in individuals with dementia, specifically Alzheimer’s disease. To improve the impaired functions, serious games targeting the lost functions are commonly developed and used in training programs. In this study, we designed a virtual reality driving simulator (VRDS) as a serious game with different difficulty levels for improving the spatial cognition; we evaluated it on 11 participants with different levels of dementia for two weeks, every day except weekends (10 sessions of practice in total) and 30 min/day. We assessed the participants’ spatial cognition before and after the intervention by an independent assessment (the VR replica of Morris Water test) and also by their performance playing the VRDS during the intervention. We also assessed the participants’ mood by a standard depression scale as well as their plausible experience of simulation sickness. The results showed significant improvement in Morris water test. The participants’ normalized correct trajectory (to find the target) was improved significantly by 44.4% at post-intervention with respect to baseline. Furthermore, on average, the participants progressed to higher (more challenging) levels of the game, and their spatial learning score increased throughout the sessions. Their mood also showed improvement with respect to baseline. Overall, the results hold promise for the designed VRDS as a mood-lifting and enhancing spatial skills serious game for older adults if it is played regularly.

Trial Registry name: Investigating the Effect of Training with a Virtual Reality Driving Simulator

URL: https://clinicaltrials.gov/ct2/show/NCT04074655

Clinical Trials.gov ID: NCT04074655

The effects of age on the contributions of head and eye movements to scanning behavior at intersections

The current study was aimed at evaluating the effects of age on the contributions of head and eye movements to scanning behavior at intersections. When approaching intersections, a wide area has to be scanned requiring large lateral head rotations as well as eye movements. Prior research suggests older drivers scan less extensively. However, due to the wide-ranging differences in methodologies and measures used in prior research, the extent to which age-related changes in eye or head movements contribute to these deficits is unclear. Eleven older (mean 67 years) and 18 younger (mean 27 years) current drivers drove in a simulator while their head and eye movements were tracked. Scans, analyzed for 15 four-way intersections in city drives, were split into two categories: eye-only (consisting only of eye movements) and head+eye (containing both head and eye movements). Older drivers made smaller head+eye scans than younger drivers (46.6° vs. 53°), as well as smaller eye-only scans (9.2° vs. 10.1°), resulting in overall smaller all- gaze scans. For head+eye scans, older drivers had both a smaller head and a smaller eye movement component. Older drivers made more eye-only scans than younger drivers (7 vs. 6) but fewer head+eye scans (2.1 vs. 2.7). This resulted in no age effects when considering all-gaze scans. Our results clarify the contributions of eye and head movements to age-related deficits in scanning at intersections, highlight the importance of analyzing both eye and head movements, and suggest the need for older driver training programs that emphasize the importance of making large scans before entering intersections.

The Effects of Age and Central Field Loss on Head Scanning and Detection at Intersections

Purpose

Using a driving simulator, we quantified the effects of age and central field loss (CFL) on head scanning when approaching an intersection and investigated the role of inadequate head scanning in detection failures.

Methods

Participants with CFL (n = 20) and with normal vision (NV; n = 29), middle-aged (36–60 years) or older (67–87 years), drove along city routes with multiple intersections while head movements were recorded. The effects of age and CFL on scanning were analyzed at 32 intersections with stop/yield signs. The relationships between age, CFL, scanning, and detection were examined at four additional intersections with a pedestrian appearing on the far left.

Results

Older NV participants made fewer total scans than middle-aged NV participants and had smaller maximum scan magnitudes. Head scanning of older CFL and NV participants did not differ, but middle-aged CFL participants made fewer head scans, had higher rates of failing to scan, and made smaller head scans than middle-aged NV participants. For the older NV and both CFL groups, detection failures were high (≥58%); head scan magnitudes were 15° smaller when the pedestrian was not detected than when it was detected.

Conclusions

Both older NV and CFL participants exhibited head scanning deficits relative to middle-aged NV participants. Unexpectedly, however, it was the middle-aged CFL group that performed least well when scanning, a finding that warrants further investigation.

Translational Relevance

Failing to head scan sufficiently far at intersections may place older drivers and drivers with vision impairment at a higher risk for causing collisions.

An Immersive Virtual Reality Platform for Assessing Spatial Navigation Memory in Predementia Screening: Feasibility and Usability Study

BACKGROUND

Traditional methods for assessing memory are expensive and have high administrative costs. Memory assessment is important for establishing cognitive impairment in cases such as detecting dementia in older adults. Virtual reality (VR) technology can assist in establishing better quality outcome in such crucial screening by supporting the well-being of individuals and offering them an engaging, cognitively challenging task that is not stressful. However, unmet user needs can compromise the validity of the outcome. Therefore, screening technology for older adults must address their specific design and usability requirements.

OBJECTIVE

This study aimed to design and evaluate the feasibility of an immersive VR platform to assess spatial navigation memory in older adults and establish its compatibility by comparing the outcome to a standard screening platform on a personal computer (PC).

METHODS

VR-CogAssess is a platform integrating an Oculus Rift head-mounted display and immersive photorealistic imagery. In a pilot study with healthy older adults (N=42; mean age 73.22 years, SD 9.26), a landmark recall test was conducted, and assessment on the VR-CogAssess was compared against a standard PC (SPC) setup.

RESULTS

Results showed that participants in VR were significantly more engaged (P=.003), achieved higher landmark recall scores (P=.004), made less navigational mistakes (P=.04), and reported a higher level of presence (P=.002) than those in SPC setup. In addition, participants in VR indicated no significantly higher stress than SPC setup (P=.87).

CONCLUSIONS

The study findings suggest immersive VR is feasible and compatible with SPC counterpart for spatial navigation memory assessment. The study provides a set of design guidelines for creating similar platforms in the future.

Driving Dilemmas: A Guide to Driving Assessment in Primary Care

Clinical assessment of fitness to drive can be a challenging part of primary care of older adults. There are no guidelines on screening for driver safety, so it falls to provider judgment on when to assess older drivers. This review offers recommendations on when to assess for driver safety based on red flag conditions, medications, acute events, and patient or family concerns. It reviews how to assess for visual, cognitive, and neuromuscular impairments and what to do as next steps for at-risk drivers once they are identified. Laws regarding driver reporting are also reviewed.

Assessing the use of immersive virtual reality, mouse and touchscreen in pointing and dragging-and-dropping tasks among young, middle-aged and older adults

This study assessed the use of an immersive virtual reality (VR), a mouse and a touchscreen for one-directional pointing, multi-directional pointing, and dragging-and-dropping tasks involving targets of smaller and larger widths by young (n = 18; 18-30 years), middle-aged (n = 18; 40-55 years) and older adults (n = 18; 65-75 years). A three-way, mixed-factorial design was used for data collection. The dependent variables were the movement time required and the error rate. Our main findings were that the participants took more time and made more errors in using the VR input interface than in using the mouse or the touchscreen. This pattern applied in all three age groups in all tasks, except for multi-directional pointing with a larger target width among the older group. Overall, older adults took longer to complete the tasks and made more errors than young or middle-aged adults. Larger target widths yielded shorter movement times and lower error rates in pointing tasks, but larger targets yielded higher rates of error in dragging-and-dropping tasks. Our study indicated that any other virtual environments that are similar to those we tested may be more suitable for displaying scenes than for manipulating objects that are small and require fine control. Although interacting with VR is relatively difficult, especially for older adults, there is still potential for older adults to adapt to that interface. Furthermore, adjusting the width of objects according to the type of manipulation required might be an effective way to promote performance.

Functional Changes and Driving Performance in Older Drivers: Assessment and Interventions

With the increasing aging of the population, the number of older drivers is rising. Driving is a significant factor for quality of life and independence concerning social and working life. On the other hand, driving is a complex task involving visual, motor, and cognitive skills that experience age-related changes even in healthy aging. In this review we summarize different age-related functional changes with relevance for driving concerning sensory, motor, and cognitive functions. Since these functions have great interindividual variability, it is necessary to apply methods that help to identify older drivers with impaired driving abilities in order to take appropriate measures. We discuss three different methods to assess driving ability, namely the assessment of (i) functions relevant for driving; (ii) driving behavior in real traffic; and (iii) behavior in a driving simulator. We present different measures to improve mobility in older drivers, including information campaigns, design of traffic and car environment, instructions, functional training, and driving training in real traffic and in a driving simulator. Finally, we give some recommendations for assessing and improving the driving abilities of older drivers with multi-modal approaches being most promising for enhancing individual and public safety.