Testing and training lifeguard visual search

Lifeguards play a crucial role in drowning prevention. However, current U.K. lifeguard qualifications are limited in training and assessing visual surveillance skills, and little is known about how lifeguards successfully detect drowning swimmers. To improve our understanding of lifeguard visual search skill, and explore the potential for improving this skill through training, this thesis had the following aims: (a) to identify whether visual skills for drowning detection improve with lifeguard experience, (b) to understand why such differences occur, and (c) design and valid a visual training intervention to improve drowning detection on the basis of these results. The first two studies investigated drowning-detection skills of participants with differing levels of lifeguard experience in a dynamic search task with simulated drownings. Lifeguards were found to detect drownings faster and more often than non-lifeguards. In three follow-up studies these results were replicated with more naturalistic stimuli. Video footage from an American wave pool was extracted, which showed genuine instances of swimmer distress. Results again demonstrated lifeguard superiority in detecting the drowning targets. Eye tracking measures, recorded on both the simulated and naturalistic clips, failed to reveal any differences between lifeguards and non-lifeguards, suggesting that superior drowning detection for lifeguards did not result from better scanning strategies per se. Following this, two cognitive mechanisms that may underlie drowning-detection skill were investigated. Lifeguard and non-lifeguard performance on Multiple Object Avoidance (MOA) and Functional Field of View (FFOV) tests was assessed. Although lifeguards had better MOA task performance compared to non-lifeguards, only the lifeguards’ accuracy at detecting the central target in the FFOV task predicted performance on a subsequent drowning detection task. It was concluded that superior drowning detection was a result of better classification recognition of drowning swimmers (which was the central task in the FFOV test). Based on these findings the final experiment explored the effectiveness of an intense classification training task to improve drowning detection. An intervention was designed that required participants to differentiate between videos of isolated drowning and non-drowning swimmers. Non-lifeguards trained in this intervention showed greater improvement on a subsequent drowning-detection task compared to untrained control participants, who completed an active-control task. The results of this thesis suggest that drowning-detection skill can be reliably assessed, and that foveal processing of drowning characteristics is key to lifeguards' superior performance. Isolating and training this key sub-skill improves drowning-detection performance and offers a method for training future lifeguards

DESIGN OF A DROWNING RESCUE ALERT SYSTEM

Dating back in time, drowning has been a significant ground for death worldwide; it accounts for the third cause of unplanned death globally, with about 1.2 million cases yearly. Characteristically it affects swimmers, accident victims, children and recreational seeking individuals. Although there have been various provisions put in place from drowning in some countries, it still accounts for the primary cause of unplanned death. Eradication rather than cure has been able to minimize the number of individuals who drown generally, except in developing nations, who lack adequate educational facilities and enforcement of safety measures on the dangers of drowning, thereby making the burden of drowning to escalate. The proposed drowning rescue system aims to curb deaths from drowning by observing the rise and fall of the heart rate and blood pressure of a swimmer or non-swimmer in water and if endangered, sends signals from the wearable device attached to the wrist of the victim who maybe undergoing a neardrowning experience to the receiver or rescuer who could be a lifeguard, parent or neighbour, in order to enable the rescuer render immediate help

Deep learning and 5G and beyond for child drowning prevention in swimming pools

Drowning is a major health issue worldwide. The World Health Organization’s global report on drowning states that the highest rates of drowning deaths occur among children aged 1–4 years, followed by children aged 5–9 years. Young children can drown silently in as little as 25 s, even in the shallow end or in a baby pool. The report also identifies that the main risk factor for children drowning is the lack of or inadequate supervision. Therefore, in this paper, we propose a novel 5G and beyond child drowning prevention system based on deep learning that detects and classifies distractions of inattentive parents or caregivers and alerts them to focus on active child supervision in swimming pools. In this proposal, we have generated our own dataset, which consists of images of parents/caregivers watching the children or being distracted. The proposed model can successfully perform a seven-class classification with very high accuracies (98%, 94%, and 90% for each model, respectively). ResNet-50, compared with the other models, performs better classifications for most classes.Peer ReviewedPostprint (published version

The Visible Behaviour of Drowning Persons: A Pilot Observational Study Using Analytic Software and a Nominal Group Technique

Although drowning is a common phenomenon, the behaviour of drowning persons is poorly understood. The purpose of this study is to provide a quantitative and qualitative analysis of this behaviour. This was an observational study of drowning videos observed by 20 international experts in the field of water safety. For quantitative analysis, each video was analysed with Lince observation software by four participants. A Nominal Group Technique generated input for the qualitative analysis and the two principal investigators conducted a post-hoc analysis. A total of 87.5% of the 23 videos showed drowning in swimming pools, 50% of the drowned persons were male, and 58.3% were children or teenagers. Nineteen persons were rescued before unconsciousness and showed just the beginning of downing behaviour. Another five were rescued after unconsciousness, which allowed the observation of their drowning behaviour from the beginning to the end. Significant differences were found comparing both groups regarding the length of disappearances underwater, number, and length of resurfacing (resp. p = 0.003, 0.016, 0.005) and the interval from the beginning of the incident to the rescue (p = 0.004). All persons drowned within 2 min. The qualitative analysis showed previously suggested behaviour patterns (immediate disappearance n = 5, distress n = 6, instinctive drowning response n = 6, climbing ladder motion n = 3) but also a striking new pattern (backward water milling n = 19). This study confirms previous assumptions of drowning behaviour and provides novel evidence-based information about the large variety of visible behaviours of drowning persons. New behaviours, which mainly include high-frequency resurfacing during a struggle for less than 2 min and backward water milling, have been recognised in this study

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学位の種別:課程博士University of Tokyo(東京大学

The Visible Behaviour of Drowning Persons: A Pilot Observational Study Using Analytic Software and a Nominal Group Technique

Although drowning is a common phenomenon, the behaviour of drowning persons is poorly understood. The purpose of this study is to provide a quantitative and qualitative analysis of this behaviour. This was an observational study of drowning videos observed by 20 international experts in the field of water safety. For quantitative analysis, each video was analysed with Lince observation software by four participants. A Nominal Group Technique generated input for the qualitative analysis and the two principal investigators conducted a post-hoc analysis. A total of 87.5% of the 23 videos showed drowning in swimming pools, 50% of the drowned persons were male, and 58.3% were children or teenagers. Nineteen persons were rescued before unconsciousness and showed just the beginning of downing behaviour. Another five were rescued after unconsciousness, which allowed the observation of their drowning behaviour from the beginning to the end. Significant differences were found comparing both groups regarding the length of disappearances underwater, number, and length of resurfacing (resp. p = 0.003, 0.016, 0.005) and the interval from the beginning of the incident to the rescue (p = 0.004). All persons drowned within 2 min. The qualitative analysis showed previously suggested behaviour patterns (immediate disappearance n = 5, distress n = 6, instinctive drowning response n = 6, climbing ladder motion n = 3) but also a striking new pattern (backward water milling n = 19). This study confirms previous assumptions of drowning behaviour and provides novel evidence-based information about the large variety of visible behaviours of drowning persons. New behaviours, which mainly include high-frequency resurfacing during a struggle for less than 2 min and backward water milling, have been recognised in this study