Computer Screen Use Detection Using Smart Eyeglasses

Wahl, Florian; Kasbauer, Jakob; Amft, Oliver

doi:10.3389/fict.2017.00008

Cited by 16 publications

(9 citation statements)

References 22 publications

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“…613 Few skin-interfaced platforms monitor blue light exposure, with eyeglass-mounted color sensors being the primary form factor. 614,615 The preceding mm-NFC dosimeter platform 600 represents the only truly epidermal device for monitoring exposure to blue light. A clinical study demonstrates device efficacy by monitoring the exposure of jaundiced infants in the neo-natal intensive care unit (NICU) undergoing bili light therapy for treating hyperbilirubinemia.…”

Section: Chemical Reviewsmentioning

confidence: 99%

“…Blue light exposure is also critical in therapeutic applications such as in treatment of hyperbilirubinemia, seasonal affective disorder, or potentially as a means for decreasing systolic blood pressure and arterial stiffness . Few skin-interfaced platforms monitor blue light exposure, with eyeglass-mounted color sensors being the primary form factor. , The preceding mm-NFC dosimeter platform represents the only truly epidermal device for monitoring exposure to blue light. A clinical study demonstrates device efficacy by monitoring the exposure of jaundiced infants in the neo-natal intensive care unit (NICU) undergoing bili light therapy for treating hyperbilirubinemia.…”

Section: Bio-integrated Wearable Sensorsmentioning

confidence: 99%

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Bio-Integrated Wearable Systems: A Comprehensive Review

et al. 2019

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Bio-integrated wearable systems can measure a broad range of biophysical, biochemical, and environmental signals to provide critical insights into overall health status and to quantify human performance. Recent advances in material science, chemical analysis techniques, device designs, and assembly methods form the foundations for a uniquely differentiated type of wearable technology, characterized by noninvasive, intimate integration with the soft, curved, time-dynamic surfaces of the body. This review summarizes the latest advances in this emerging field of “bio-integrated” technologies in a comprehensive manner that connects fundamental developments in chemistry, material science, and engineering with sensing technologies that have the potential for widespread deployment and societal benefit in human health care. An introduction to the chemistries and materials for the active components of these systems contextualizes essential design considerations for sensors and associated platforms that appear in following sections. The subsequent content highlights the most advanced biosensors, classified according to their ability to capture biophysical, biochemical, and environmental information. Additional sections feature schemes for electrically powering these sensors and strategies for achieving fully integrated, wireless systems. The review concludes with an overview of key remaining challenges and a summary of opportunities where advances in materials chemistry will be critically important for continued progress.

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Section: Chemical Reviewsmentioning

confidence: 99%

Section: Bio-integrated Wearable Sensorsmentioning

confidence: 99%

Bio-Integrated Wearable Systems: A Comprehensive Review

et al. 2019

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“…Zhang et al proposed a system to detect moments of screen watching during daily life activities based on first-person videos from a wearable camera [35]. Wahl et al proposed a method for screen use detection using a color sensor in smart eyeglasses [31]. In this paper, we find out that the sole use of the color sensor can make false-positive errors and thus propose a multi-sensory fusion including an IMU and a distance measurement sensor to make Tiger more robust to various situations.…”

Section: Related Workmentioning

confidence: 99%

“…We choose a TCS34725 RGB color sensor that has red, green, blue, and clear light sensing elements. The same sensor was also used in Wahl et al's work [31] for screen use detection, where they extracted time-domain features based on the relative ratios across the color channels and used SVM for the usage detection. We further optimize the screen viewing detection in two aspects.…”

Section: Screen Viewing Detection Through Sensor Fusionmentioning

confidence: 99%

Tiger

Min

Lee

Park

et al. 2019

Proceedings of the 21st International Conference on Human-Computer Interaction With Mobile Devices and Services

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We propose Tiger, an eyewear system for helping users follow the 20-20-20 rule to alleviate the Computer Vision Syndrome symptoms. It monitors user's screen viewing activities and provides real-time feedback to help users follow the rule. For accurate screen viewing detection, we devise a light-weight multi-sensory fusion approach with three sensing modalities, color, IMU, and lidar. We also design the real-time feedback to effectively lead users to follow the rule. Our evaluation shows that Tiger accurately detects screen viewing events, and is robust to the differences in screen types, contents, and ambient light. Our user study shows positive perception of Tiger regarding its usefulness, acceptance, and real-time feedback. CCS CONCEPTS• Human-centered computing → Ubiquitous and mobile computing systems and tools;

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“…For example, due to the camera attachment and the resultant line of sight, if the participant is not sitting upright while watching TV, the camera may point away from the TV. A head mounted wearable camera could address this limitation [219].However so would the more unobtrusive options of wearable gaze camera glasses [220] and smart glasses that measure blue light emission [221]. Gaze cameras and smart glasses would also allow for better quantification of other types of screen time, as the devices' field of view is aligned with participant's eyes.…”

Section: Technologies For Collecting Broader Contextual Informationmentioning

confidence: 99%

The relationship between the home environment and children’s physical activity and sedentary behaviour at home

Sheldrick¹

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Increasing children’s physical activity (PA) and reducing their sedentary behaviour are considered important preventative measures for obesity and several other health risk factors in children. Given children spend significant time at home, an improved understanding of these behaviours in the home environment would provide invaluable insight for interventions. Therefore, the overarching aim of this thesis was to provide new insight into how the home environment is related to children’s home-based PA and sedentary behaviour. Study 1 investigated the relationship between sufficient moderate-to-vigorous physical activity (MVPA) (≥60 min·day–1) and excessive screen-time (≥2 h·day–1) with lifestyle factors in children, and found they were associated with healthy and unhealthy factors, respectively. This study highlighted the importance of meeting PA and screen-time recommendations in relation to important health-related lifestyle factors, which is of concern, as few children were shown to meet such recommendations. Identifying the correlates of children’s behaviours is an important stage in intervention development, therefore studies 2-5 focussed on improving understanding of children’s PA and sedentary behaviour at home. Study 2 demonstrated the validity and reliability of HomeSPACE-II, a novel instrument for measuring physical factors that influence children’s home-based PA and sedentary behaviour. Using HomeSPACE-II, study 3 showed that the physical home environment is related to children’s home-based PA and sedentary behaviour. Given the established influence of social and individual factors on children’s behaviour and their confounding effects in study 3, study 4 investigated the influence of social and individual factors on: (i) children’s home-based PA and sedentary behaviour, and; (ii) the home physical environment. Study 4 revealed that parental and child activity preferences and priorities, as well as parental rules were associated with children’s home-based PA and sedentary behaviour and the physical home environment. Study 5 found clusters of social and physical factors at home, which were associated with children’s home-based PA and sedentary behaviour as well as background characteristics in the expected directions.

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Computer Screen Use Detection Using Smart Eyeglasses

Cited by 16 publications

References 22 publications

Bio-Integrated Wearable Systems: A Comprehensive Review

Bio-Integrated Wearable Systems: A Comprehensive Review

Tiger

The relationship between the home environment and children’s physical activity and sedentary behaviour at home

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