On-skin displays have emerged as a seamless form factor for visualizing information. However, the non-traditional form factor of these on-skin displays and how they present notifications on the skin may raise concerns for public wear. These perceptions will impact whether a device is eventually adopted or rejected by society. Therefore, researchers must consider the societal facets of device design. In this paper, we study social perceptions towards interacting with a color-changing on-skin display. We examined third-person perspectives through a 254-person online survey. The study was conducted in the United States and Taiwan to distill cross-cultural attitudes. This structured study sheds light on designing on-skin displays reflective of cultural considerations.
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Encounters with casual acquaintances are common in our daily lives. In such situations, people are sometimes unable to find an appropriate topic for conversation, and as such, an awkward silence follows. However, we believe that this awkward encounter can be an opportunity to build a good relationship with the acquaintance through a brief conversation if an appropriate topic is discovered.
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Eyelid stickers are thin strips that temporarily create a crease when attached to the eyelid. The direct contact with the crease that increases and decreases the pressure on the eyelid sticker provides a novel opportunity for sensing blinking. We present Eslucent, an on-skin wearable capacitive sensing device that affords blink detection, building on the form factor of eyelid stickers. It consists of an art layer, conductive thread, fiber eyelid stickers, coated with conductive liquid, and applied the device onto the eyelid crease with adhesive temporary tattoo paper. Eslucent detects blinks during intentional blinking and four involuntary activities by a falling edge detection algorithm in a user study of 14 participants. The average precision was 82% and recall was 70% while achieving the precision and recall of more than 90% in intentional blinking. By embedding interactive technology into a daily beauty product, Eslucent explores a novel wearable form factor for blink detection.
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More than one million people in the US suffer from hemianopia, which blinds the vision in one half of the peripheral vision in both eyes. Hemianopic patients are often not aware of what they cannot see and frequently bump into walls, trip over objects, or walk into people on the side where the peripheral vision is diminished. We present an augmented reality based assistive technology that expands the peripheral vision of hemianopic patients at all distances. In a pilot trial, we evaluate the utility of this assistive technology for ten hemianopic patients. We measure and compare outcomes related to target identification and visual search in the participants. Improvements in target identification are noted in all participants ranging from 18% to 72%. Similarly, all the participants benefit from the assistive technology in performing a visual search task with an average increase of 24% in the number of successful searches compared to unaided trials. The proposed technology is the first instance of an electronic vision enhancement tool for hemianopic patients and is expected to maximize the residual vision and quality of life in this growing, yet largely overlooked population.
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The ubiquitous availability of wearable sensing devices has rendered large scale collection of movement data a straightforward endeavor. Yet, annotation of these data remains a challenge and as such, publicly available datasets for human activity recognition (HAR) are typically limited in size as well as in variability, which constrains HAR model training and effectiveness. We introduce masked reconstruction as a viable self-supervised pre-training objective for human activity recognition and explore its effectiveness in comparison to state-of-the-art unsupervised learning techniques. In scenarios with small labeled datasets, the pre-training results in improvements over end-to-end learning on two of the four benchmark datasets. This is promising because the pre-training objective can be integrated “as is” into state-of-the-art recognition pipelines to effectively facilitate improved model robustness, and thus, ultimately, leading to better recognition performance.
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Theatre provides a unique environment in which to obtain detailed data on social interactions in a controlled and repeatable manner. This work introduces a method for capturing and characterising the underlying emotional intent of performers in a scripted scene using in-ear accelerometers. Each scene is acted with different underlying emotional intentions using the theatrical technique of Actioning. The goal of the work is to uncover characteristics in the joint movement patterns that reveal information on the positive or negative valence of these intentions. Preliminary findings over 3×12 (Covid-19 restricted) non-actor trials suggests people are more energetic and more in-sync when using positive versus negative intentions.
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