Eye blink parameters to indicate drowsiness during naturalistic driving in participants with obstructive sleep apnea: A pilot study

Driving among individuals with chronic conditions: A systematic review of applied research using kinematic driving sensors

BACKGROUND

Kinematic driving data studies are a novel methodology relevant to health care, but prior studies have considerable variance in their methods, populations, and findings suggesting a need for critical analysis and appraisal for feasibility and methodological guidelines.

METHODS

We assessed kinematic driving studies of adults with chronic conditions for study feasibility, characteristics, and key findings, to generate recommendations for future study designs, and to identify promising directions for applications of kinematic driving data. PRISMA was used to guide the review and searches included PubMed, CINAHL, and Compendex. Of 379 abstract/titles screened, 49 full-text articles were reviewed, and 29 articles met inclusion criteria of analyzing trip-level kinematic driving data from adult drivers with chronic conditions.

RESULTS

The predominant chronic conditions studied were Alzheimer's disease and related Dementias, obstructive sleep apnea, and diabetes mellitus. Study objectives included feasibility testing of kinematic driving data collection in the context of chronic conditions, comparisons of simulation with real-world kinematic driving behavior, assessments of driving behavior effects associated with chronic conditions, and prognostication or disease classification drawn from kinematic driving data. Across the studies, there was no consensus on devices, measures, or sampling parameters; however, studies showed evidence that driving behavior could reliably differentiate between adults with chronic conditions and healthy controls.

CONCLUSIONS

Vehicle sensors can provide driver-specific measures relevant to clinical assessment and interventions. Using kinematic driving data to assess and address driving measures of individuals with multiple chronic conditions is positioned to amplify a functional outcome measure that matters to patients.

PERCLOS-based technologies for detecting drowsiness: current evidence and future directions

Drowsiness associated with sleep loss and circadian misalignment is a risk factor for accidents and human error. The percentage of time that the eyes are more than 80% closed (PERCLOS) is one of the most validated indices used for the passive detection of drowsiness, which is increased with sleep deprivation, after partial sleep restriction, at nighttime, and by other drowsiness manipulations during vigilance tests, simulated driving, and on-road driving. However, some cases have been reported wherein PERCLOS was not affected by drowsiness manipulations, such as in moderate drowsiness conditions, in older adults, and during aviation-related tasks. Additionally, although PERCLOS is one of the most sensitive indices for detecting drowsiness-related performance impairments during the psychomotor vigilance test or behavioral maintenance of wakefulness test, no single index is currently available as an optimal marker for detecting drowsiness during driving or other real-world situations. Based on the current published evidence, this narrative review suggests that future studies should focus on: (1) standardization to minimize differences in the definition of PERCLOS between studies; (2) extensive validation using a single device that utilizes PERCLOS-based technology; (3) development and validation of technologies that integrate PERCLOS with other behavioral and/or physiological indices, because PERCLOS alone may not be sufficiently sensitive for detecting drowsiness caused by factors other than falling asleep, such as inattention or distraction; and (4) further validation studies and field trials targeting sleep disorders and trials in real-world environments. Through such studies, PERCLOS-based technology may contribute to preventing drowsiness-related accidents and human error.

Usefulness of the maintenance of wakefulness test in central disorders of hypersomnolence: a scoping review

Study Objectives

To review the Maintenance of Wakefulness Test (MWT) as assessment of daytime sleepiness in the evaluation of treatment effects and driving fitness in central disorders of hypersomnolence (CDH).

Methods

We performed a scoping review of studies using the MWT in patients with CDH (i.e. narcolepsy types 1 and 2, and idiopathic hypersomnia). N = 20 articles were included, comprising 683 patients and 129 controls. MWT effect sizes were compared to the Clinical Global Impression (GCI) scale and the Epworth Sleepiness Scale (ESS). MWT sleep latency was correlated to objective driving performances. The role of motivation was evaluated by comparing MWTs of treatment studies (low motivation) to driving fitness studies (high motivation to stay awake). Healthy controls were compared to norm values.

Results

MWT and CGI were both impacted by the same treatment; however, the MWT has higher effect sizes and was more sensitive to measure these effects. The MWT correlated fairly to moderately (ρ = −0.26 to −0.56; p ≤ .05) to objective driving performance. Motivation played a major role on MWT sleep latencies (d = 0.76 to 1.43; p ≤ .001). Current norm values may not be valid, as sleep latency may be impacted by age.

Conclusions

The MWTs applicability to measure treatment effects in CDH was confirmed, but age-adjusted norm values are needed. For a more complete evaluation of EDS it should be combined with subjective measures. Its reliability for driving fitness evaluation is insufficient, and motivation plays a major role. To predict or monitor driving performance in CDH, valid and easy methods should be developed.

A Road Safety-Based Selection Methodology for Professional Drivers: Behaviour and Accident Rate Analysis

In this paper, we examine the factors affecting the behaviour of road users and the impact of these factors on professional drivers' reliability and performance. A professional driver is considered as a driver involved in the processes of driving a vehicle as a matter of his/her business or the transportation of passengers or goods by bus or lorry, with higher liability in terms of road safety and requiring a higher degree of maintained attentiveness, constant concentration, and working capacity. This article highlights the process of selecting a professional driver by focusing on the driver's individual and psychophysiological characteristics. An anonymous survey on professional drivers and a statistical analysis of the accidents caused by professional drivers was used to research the impact of fatigue on the behaviour of road users. The conducted statistical analysis demonstrates that the amount of professional driving experience most conducive to driving a vehicle safely was observed at between 29 and 33 years of experience. It was also found that a higher probability of causing an accident after rest days is related to the driver's long period of engagement at work and inadequate rest. This study demonstrates that specific requirements should be applied to the methodologies for selecting professional drivers, the research on the reliability of which aims to develop a concept that enables opting for those drivers able to properly perform hired work, causing minimal losses due to road accidents.