Home-Use Evaluation of a Wearable Collision Warning Device for Individuals With Severe Vision Impairments: A Randomized Clinical Trial.

IMPORTANCE: There is scant rigorous evidence about the real-world mobility benefit of electronic mobility aids. OBJECTIVE: To evaluate the effect of a collision warning device on the number of contacts experienced by blind and visually impaired people in their daily mobility. DESIGN, SETTING, AND PARTICIPANTS: In this double-masked randomized clinical trial, participants used a collision warning device during their daily mobility over a period of 4 weeks. A volunteer sample of 31 independently mobile individuals with severe visual impairments, including total blindness and peripheral visual field restrictions, who used a long cane or guide dog as their habitual mobility aid completed the study. The study was conducted from January 2018 to December 2019. INTERVENTIONS: The device automatically detected collision hazards using a chest-mounted video camera. It randomly switched between 2 modes: active mode (intervention condition), where it provided alerts for detected collision threats via 2 vibrotactile wristbands, and silent mode (control condition), where the device still detected collisions but did not provide any warnings to the user. Scene videos along with the collision warning information were recorded by the device. Potential collisions detected by the device were reviewed and scored, including contacts with the hazards, by 2 independent reviewers. Participants and reviewers were masked to the device operation mode. MAIN OUTCOMES AND MEASURES: Rate of contacts per 100 hazards per hour, compared between the 2 device modes within each participant. Modified intention-to-treat analysis was used. RESULTS: Of the 31 included participants, 18 (58%) were male, and the median (range) age was 61 (25-73) years. A total of 19 participants (61%) had a visual acuity (VA) of light perception or worse, and 28 (90%) reported a long cane as their habitual mobility aid. The median (interquartile range) number of contacts was lower in the active mode compared with silent mode (9.3 [6.6-14.9] vs 13.8 [6.9-24.3]; difference, 4.5; 95% CI, 1.5-10.7; P < .001). Controlling for demographic characteristics, presence of VA better than light perception, and fall history, the rate of contacts significantly reduced in the active mode compared with the silent mode (ß = 0.63; 95% CI, 0.54-0.73; P < .001). CONCLUSIONS AND RELEVANCE: In this study involving 31 visually impaired participants, the collision warnings were associated with a reduced rate of contacts with obstacles in daily mobility, indicating the potential of the device to augment habitual mobility aids. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03057496.

With Motion Perception, Good Visual Acuity May Not Be Necessary for Driving Hazard Detection.

Purpose: To investigate the roles of motion perception and visual acuity in driving hazard detection. Methods: Detection of driving hazard was tested based on video and still-frames of real-world road scenes. In the experiment using videos, 20 normally sighted participants were tested under four conditions: with or without motion interruption by interframe mask, and with or without simulated low visual acuity (20/120 on average) by using a diffusing filter. Videos were down-sampled to 2.5 Hz, to allow the addition of motion interrupting masks between the frames to maintain video durations. In addition, single still frames extracted from the videos were shown in random order to eight normally sighted participants, who judged whether the frames were during ongoing hazards, with or without the diffuser. Sensitivity index d-prime (d') was compared between unmasked motion (n = 20) and still frame conditions (n = 8). Results: In the experiment using videos, there was a significant reduction in a combined performance score (taking account of reaction time and detection rate) when the motion was disrupted (P = 0.016). The diffuser did not affect the scores (P = 0.419). The score reduction was mostly due to a decrease in the detection rate (P = 0.002), not the response time (P = 0.148). The d' of participants significantly decreased (P < 0.001) from 2.24 with unmasked videos to 0.68 with still frames. Low visual acuity also had a significant effect on the d' (P = 0.004), but the change was relatively small, from 2.03 without to 1.56 with the diffuser. Conclusions: Motion perception plays a more important role than visual acuity for detecting driving hazards. Translational Relevance: Motion perception may be a relevant criterion for fitness to drive.

Bioptic Telescope Use in Naturalistic Driving by People with Visual Impairment.

Purpose: The purpose of this study was to investigate the telescope use behaviors in natural daily driving of people with reduced visual acuity licensed to drive with a bioptic (a small spectacle-mounted telescope). Methods: A large dataset (477 hours) of naturalistic driving was collected from 19 bioptic drivers (visual acuity 20/60 to 20/160 without the telescope). To reduce the data volume, a multiloss 50-layer deep residual neural network (ResNet-50) was used to detect potential bioptic telescope use events. Then, a total of 120 hours of selected video clips were reviewed and annotated in detail. Results: The frequency of looking through their telescopes ranged from 4 to 308 times per hour (median: 27, interquartile range [IQR], 19-75), with each bioptic use lasting median 1.4 seconds (IQR, 1.2-1.8). Thus, participants spent only 1.6% (IQR, 0.7%-3.5%) driving time with their telescopes aiding their vision. Bioptic telescopes were used most often for checking the road ahead (84.8%), followed by looking at traffic lights (5.3%), and reading road signs (4.6%). Conclusions: In daily driving, the bioptic drivers mostly (>98% of driving time) drove under low visual acuity conditions. The bioptic telescope was mainly used for observing road and traffic conditions in the distance for situational awareness. Only a small portion of usage was for road sign reading. Translational Relevance: This study provides new insights into how the vision rehabilitation device-bioptic telescopes are used in daily driving. The findings may be helpful for designing bioptic driving training programs.

Hazard Detection With Monocular Bioptic Telescopes in a Driving Simulator.

Purpose: In most states, people with reduced visual acuity may legally drive with the aid of a bioptic telescope. However, concerns have been raised that the ring scotoma may impair detection of peripheral hazards. Using a driving simulator, we tested the hypothesis that the fellow eye would be able to compensate for the ring scotoma when using a monocular telescope. Methods: Sixteen bioptic users completed three drives with binocular viewing interleaved between three drives with monocular viewing. Forty pedestrians appeared and ran on the road for 1 second, including 26 within the ring scotoma, while participants were reading road signs through their own monocular telescopes. Head movements were analyzed to determine whether the pedestrian appeared before or only while using the telescope. Results: For pedestrians that appeared only during bioptic use and were likely in the area of the ring scotoma, detection rates were significantly higher in binocular (fellow eye can compensate) than monocular (fellow eye patched) viewing (69% vs. 32%; P < 0.001); this was true for both current and noncurrent drivers. For pedestrians appearing before or after bioptic use, detection rates did not differ in binocular and monocular viewing. However, detection rates were even higher and reaction times shorter when the telescope was not being used. Conclusions: Both current and noncurrent drivers'  fellow eyes were able to compensate, at least in part, for the ring scotoma. Translational Relevance: When using monocular telescopes, the fellow eye reduces the impact of the ring scotoma on hazard detection in binocular viewing.

Evaluation of the Driving Safety of Visually Impaired Bioptic Drivers Based on Critical Events in Naturalistic Driving.

Purpose: Visually impaired people may be allowed to drive if they wear bioptic telescopes. Bioptic driving safety is debatable, especially given that the telescopes are seldom used by most bioptic drivers. This preliminary study examined bioptic safety based on critical events that occurred in naturalistic daily driving. Methods: Daily driving activities were recorded using in-car video recorders in 20 bioptic drivers (median age 55, visual acuity, 20/60-160) and 19 control subjects (median age 74) for two to eight weeks. In a secondary analysis, these subjects were compared with 44 cognitively impaired drivers with normal vision (median age 75). Results: In 292 hours of driving by bioptic drivers and 169 hours by control drivers, seven bioptic drivers and three control drivers had eight and four near-collisions, respectively. Near-collision survival times were not significantly different between the two groups (hazard ratio [HR] = 1.93, P = 0.591) according to Cox hazards regression. Even without compensation for bioptic drivers' longer driving exposure, their odds ratio (OR) was not statistically significant (OR = 2.88, P = 0.18). When including cognitively impaired drivers with normal vision, cognition was a significant predictor of near collisions (HR = 3.86, P = 0.036), but vision loss was not (HR = 0.47, P = 0.317). Conclusions: This preliminary study failed to find any evidence suggesting that bioptic drivers were more prone to near-collision than healthy drivers. Vision might be a less-significant factor than cognition. Translational Relevance: Given that bioptic drivers use the telescope for less than 2% of the driving time, this study suggests that driving safety might not be substantially affected even when visual acuity is in the low vision range.

Data Acquisition, Processing, and Reduction for Home-Use Trial of a Wearable Video Camera-Based Mobility Aid.

Purpose: Evaluating mobility aids in naturalistic conditions across many days is challenging owing to the sheer amount of data and hard-to-control environments. For a wearable video camera-based collision warning device, we present the methodology for acquisition, reduction, review, and coding of video data for quantitative analyses of mobility outcomes in blind and visually impaired participants. Methods: Scene videos along with collision detection information were obtained from a chest-mounted collision warning device during daily use of the device. The recorded data were analyzed after use. Collision risk events flagged by the device were manually reviewed and coded using a detailed annotation protocol by two independent masked reviewers. Data reduction was achieved by predicting agreements between reviewers based on a machine learning algorithm. Thus, only those events for which disagreements were predicted would be reviewed by the second reviewer. Finally, the ultimate disagreements were resolved via consensus, and mobility-related outcome measures such as percentage of body contacts were obtained. Results: There were 38 hours of device use from 10 participants that were reviewed by both reviewers, with an agreement level of 0.66 for body contacts. The machine learning algorithm trained on 2714 events correctly predicted 90.5% of disagreements. For another 1943 events, the trained model successfully predicted 82% of disagreements, resulting in 81% data reduction. Conclusions: The feasibility of mobility aid evaluation based on a large volume of naturalistic data is demonstrated. Machine learning-based disagreement prediction can lead to data reduction. Translational Relevance: These methods provide a template for determining the real-world benefit of a mobility aid.

Driving Safety of Cognitively-Impaired Drivers Based on Near Collisions in Naturalistic Driving.

BACKGROUND: Controlled naturalistic driving for examining impacts of cognitive impairment on driving safety is rare. OBJECTIVE: Evaluating the safety among drivers with mild cognitive impairment based on near collision incidents using naturalistic driving, and investigating its correlation with cognitive measures. METHODS: Frequency of near collisions of 44 cognitively impaired [Age = 75.1(±6.7), MMSE = 25.5(±2.5)] and 19 control group drivers [Age = 72.5(±7.8), MMSE = 29.3(±0.8)] were obtained from two weeks of recorded driving. Survival time free of predicted collision based on a previously established near-collision to collision estimate ratio of 11 : 1, for 140 hours of driving exposure was calculated. Participants were also tested using Mini-Mental Status Examination (MMSE), Trail A, and Trail B. Spearman correlation and Cox survival analysis were conducted. RESULTS: Near collision frequency per driving hour was correlated with MMSE (r = -0.258, p = 0.041). Survival analyses showed that cognitively impaired drivers might be prone to higher probability of having collision (p = 0.056) with a hazard ratio of 5.78 (p = 0.092). When all participants were combined, there was a significant difference (p < 0.017) in all the three cognitive measures between drivers with and without predicted collision, which were not significant within patient or control group alone (p > 0.186). Cox regression analysis showed MMSE as the only significant factor (p < 0.025) for survival time of predicted collision, but not age, gender, or driving experience. CONCLUSION: The association between driving critical events and cognitive measures suggests that some drivers with mild cognitive impairment might have an elevated driving collision risk compared to control drivers. Standard clinical cognitive measures may be reasonable predictors.

Preliminary Evaluation of a Wearable Camera-based Collision Warning Device for Blind Individuals.

SIGNIFICANCE: This work describes a preliminary evaluation of a wearable collision warning device for blind individuals. The device was found to provide mobility benefit in subjects without (or deprived of) vision. This preliminary evaluation will facilitate further testing of this developmental stage device in more naturalistic conditions. PURPOSE: We developed a wearable video camera-based device that provided tridirectional collision warnings (right, center, and left) via differential feedback of two vibrotactile wristbands. We evaluated its mobility benefit in blind and normally sighted (NS) blindfolded individuals in indoor mobility courses. METHODS: Three evaluation experiments were conducted. First, the ability of the device to provide warnings for hanging objects not detected by a long cane was evaluated in eight NS and four blind subjects in an obstacle course with and without the device. Second, the accuracy of collision warning direction assignment was evaluated in 10 NS subjects as they walked toward a hanging object at random offsets and verbally reported the obstacle offset position with respect to their walking path based on the wristbands' vibrotactile feedback. Third, the mobility benefit of collision warning direction information was evaluated by 10 NS and 4 blind subjects when walking with and without differential wristband feedback. RESULTS: In experiment 1, collisions reduced significantly from a median of 11.5 without to 4 with the device (P < .001). Percent preferred walking speed reduced only slightly from 41% without to 36% with the device (P = .04). In experiment 2, the most likely reported relative obstacle positions were consistent with the actual positions. In experiment 3, subjects made more correct navigational decisions with than without the collision warning direction information (91% vs. 69%, P < .001). CONCLUSIONS: Substantial mobility benefit of the device was seen in detection of aboveground collision threats missed by a long cane and in enabling better navigational decision making based on the tridirectional collision warning information.

Detection of Risky Driving Behaviors in the Naturalistic Environment in Healthy Older Adults and Mild Alzheimer's Disease.

Analyzing naturalistic driving behavior recorded with in-car cameras is an ecologically valid method for measuring driving errors, but it is time intensive and not easily applied on a large scale. This study validated a semi-automated, computerized method using archival naturalistic driving data collected for drivers with mild Alzheimer's disease (AD; n = 44) and age-matched healthy controls (HC; n = 16). The computerized method flagged driving situations where safety concerns are most likely to occur (i.e., rapid stops, lane deviations, turns, and intersections). These driving epochs were manually reviewed and rated for error type and severity, if present. Ratings were made with a standardized scoring system adapted from DriveCam®. The top eight error types were applied as features to train a logistic model tree classifier to predict diagnostic group. The sensitivity and specificity were compared among the event-based method, on-road test, and composite ratings of two weeks of recorded driving. The logistic model derived from the event-based method had the best overall accuracy (91.7%) and sensitivity (97.7%) and high specificity (75.0%) compared to the other methods. Review of driving situations where risk is highest appears to be a sensitive data reduction method for detecting cognitive impairment associated driving behaviors and may be a more cost-effective method for analyzing large volumes of naturalistic data.