Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Internet of Things (IoT) applications typically collect and analyse personal data that is categorised as sensitive or special category of personal data. These data are subject to a higher degree of protection under data privacy laws. Regardless of legal ...

There is increasing interest in deploying building-scale, general-purpose, and high-fidelity sensing to drive emerging smart building applications. However, the real-world deployment of such systems is challenging due to the lack of system and ...

Smartphones contain thermistors that ordinarily monitor the temperature of the device's internal components; however, these sensors are also sensitive to warm entities in contact with the device, presenting opportunities for measuring human body ...

Visual body signals are designated body poses that deliver an application-specific message. Such signals are widely used for fast message communication in sports (signaling by umpires and referees), transportation (naval officers and aircraft ...

The last few decades have witnessed an emerging trend of wearable soft sensors; however, there are important signal-processing challenges for soft sensors that still limit their practical deployment. They are error-prone when displaced, resulting in ...

Imagine a near-future smart home. Home-embedded visual AI sensors continuously monitor the resident, inferring her activities and internal states that enable higher-level services. Here, as home-embedded sensors passively monitor a free person, good ...

Forecasting physical functioning of people with Multiple Sclerosis (MS) can inform timely clinical interventions and accurate "day planning" to improve their well-being. However, people's physical functioning often remains unchecked in between ...

The plethora of sensors in our commodity devices provides a rich substrate for sensor-fused tracking. Yet, today's solutions are unable to deliver robust and high tracking accuracies across multiple agents in practical, everyday environments - a feature ...

Millimeter wave radar is a promising sensing modality for enabling pervasive and privacy-preserving human sensing. However, the lack of large-scale radar datasets limits the potential of training deep learning models to achieve generalization and ...

Estimating 3D human mesh is appealing for various application scenarios. Current mainstream solution predicts the meshes either from the image or the human reflected RF-signals. In this paper, instead of investigating which approach is better, we ...

Wide-area soil moisture sensing is a key element for smart irrigation systems. However, existing soil moisture sensing methods usually fail to achieve both satisfactory mobility and high moisture estimation accuracy. In this paper, we present the design ...

In clinical settings, most automatic recognition systems use visual or sensory data to recognize activities. These systems cannot recognize activities that rely on verbal assessment, lack visual cues, or do not use medical devices. We examined speech-...

Any two objects in contact with each other exert a force that could be simply due to gravity or mechanical contact, such as any ubiquitous object exerting weight on a platform or the contact between two bones at our knee joints. The most ideal way of ...

Thermal signals have been explored in HCI for emotion-elicitation and enhancing two-person communication, showing that temperature invokes social and emotional signals in individuals. Yet, extending these findings to group communication is missing. We ...

The physical and physiological development of infants and toddlers requires the proper amount of macronutrient intake, making it an essential problem to estimate the macronutrient in baby food. Nevertheless, existing solutions are either too expensive ...

The increasingly remote workforce resulting from the global coronavirus pandemic has caused unprecedented cybersecurity concerns to organizations. Considerable evidence has shown that one-pass authentication fails to meet security needs when the ...

End-to-end deep learning models are increasingly applied to safety-critical human activity recognition (HAR) applications, e.g., healthcare monitoring and smart home control, to reduce developer burden and increase the performance and robustness of ...

Many countries have implemented school closures due to the outbreak of the COVID-19 pandemic, which has inevitably affected children's physical and mental health. It is vital for parents to pay special attention to their children's health status during ...

With current clinical techniques, it is difficult to assess a patient's neurodegenerative disease (e.g., Alzheimer's) state accurately and frequently. The most widely used tests are qualitative or only performed intermittently, motivating the need for ...

Currently, federated learning (FL) can enable users to collaboratively train a global model while protecting the privacy of user data, which has been applied to human activity recognition (HAR) tasks. However, in real HAR scenarios, deploying an FL ...

Activity recognition using video data is widely adopted for elder care, monitoring for safety and security, and home automation. Unfortunately, using video data as the basis for activity recognition can be brittle, since models trained on video are ...

We propose FocalPoint, a direct manipulation technique in smartphone augmented reality (AR) for selecting small densely-packed objects within reach, a fundamental yet challenging task in AR due to the required accuracy and precision. FocalPoint ...

Stories are a core way human beings make meaning and sense of the world and our lived experiences, including our behaviors, desires, and goals. Narrative structures, both visual and textual, help us understand and act on information, while also evoking ...

Given the complexity of human eating behaviors, developing interactions to change the way users eat or their choice of meals is challenging. In this study, we propose an interactive system called eat2pic designed to encourage healthy eating habits such ...

Energy harvesting reduces the burden of power source maintenance and promises to make computing systems genuinely ubiquitous. Researchers have made inroads in this area, but their novel energy harvesting materials and fabrication techniques remain ...

Many patients with neurological disorders, such as Ataxia, do not have easy access to neurologists, -especially those living in remote localities and developing/underdeveloped countries. Ataxia is a degenerative disease of the nervous system that ...

Studying social interaction in real-world settings is of increasing importance to social cognitive researchers. Theatre provides an ideal opportunity to study rich face-to-face interactions in a controlled, yet natural setting. Here we collaborated with ...

Smartphones have gotten under public scrutiny due to their ostensible negative impact on users' well-being. Nonetheless, users and related work report positive aspects of smartphones, too. We investigated this discrepancy through the prism of the ...

Mood, often studied using smartphones, influences human perception, judgment, thought, and behavior. Mood measurements on smartphones face challenges concerning the selection of a proper mood measure and its transfer, or translation, into a digital ...

Blood glucose measurement is commonly used to screen for and monitor diabetes, a chronic condition characterized by the inability to effectively modulate blood glucose that can lead to heart disease, vision loss, and kidney failure. Early detection of ...