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

Human activity recognition (HAR) has emerged as a prominent research field in recent years. Current HAR models are only able to model bilateral correlations between two sensing devices for feature extraction. However, for some activities, exploiting ...

Electrodermal activity (EDA) is a physiological signal that can be used to infer humans' affective states and stress levels. EDA can nowadays be monitored using unobtrusive wearable devices, such as smartwatches, and leveraged in personal informatics ...

Small form factor limits physical input space in earable (i.e., ear-mounted wearable) devices. Off-device earable inputs in alternate mid-air and on-skin around-ear interaction spaces using uni-manual gestures can address this input space limitation. ...

Due to the fact that roughly sixty percent of the human body is essentially composed of water, the human body is inherently a conductive object, being able to, firstly, form an inherent electric field from the body to the surroundings and secondly, ...

Knowing the object grabbed by a hand can offer essential contextual information for interaction between the human and the physical world. This paper presents a novel system, ViObject, for passive object recognition that uses accelerometer and gyroscope ...

Federated Learning (FL) enables distributed training of human sensing models in a privacy-preserving manner. While promising, federated global models suffer from cross-domain accuracy degradation when the labeled source domains statistically differ from ...

While occlusal diseases - the main cause of tooth loss -- significantly impact patients' teeth and well-being, they are the most underdiagnosed dental diseases nowadays. Experiencing occlusal diseases could result in difficulties in eating, speaking, and ...

The inadequate use of finger properties has limited the input space of touch interaction. By leveraging the category of contacting fingers, finger-specific interaction is able to expand input vocabulary. However, accurate finger identification remains ...

Transportation mode detection (TMD) has been proposed as a computational technology to obtain mobility information. However, previous TMD studies mainly focused on improving detection performance and have not investigated the social implications of ...

In recent years, predicting mobile app usage has become increasingly important for areas like app recommendation, user behaviour analysis, and mobile resource management. Existing models, however, struggle with the heterogeneous nature of contextual data ...

Human activity recognition (HAR) is crucial for ubiquitous computing systems. While HAR systems are able to recognize a predefined set of activities established during the development process, they often fail to handle users' unique ways of completing ...

Smart home assistants function best when user commands are direct and well-specified---e.g., "turn on the kitchen light"---or when a hard-coded routine specifies the response. In more natural communication, however, human speech is unconstrained, often ...

Sleep posture plays a crucial role in maintaining good morpheus quality and overall health. As a result, long-term monitoring of 3D sleep postures is significant for sleep analysis and chronic disease prevention. To recognize sleep postures, traditional ...

A spinal cord injury (SCI) typically results in a sudden change to an individual's motor function. People's adoption of technology soon after a severe SCI is crucial, since they must relearn most technology interactions to adjust to their new physical ...

WiFi has gradually developed into one of the main candidate technologies for ubiquitous sensing. Based on commercial off-the-shelf (COTS) WiFi devices, this paper proposes LiquImager, which can simultaneously identify liquid and image container ...

Contactless acoustic sensing has been actively exploited in the past few years to enable a large range of applications, ranging from fine-grained vital sign monitoring to coarse-grained human tracking. However, existing acoustic sensing systems mainly ...

Egocentric non-intrusive sensing of human activities of daily living (ADL) in free-living environments represents a holy grail in ubiquitous computing. Existing approaches, such as egocentric vision and wearable motion sensors, either can be intrusive or ...

A long-term perspective toward the future enables a more comprehensive approach to decision-making, considering a variety of potential scenarios. The forecasting of mental health was anticipated to promote proactive planning, however, it faces challenges ...

Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) are both heterogeneous in their clinical presentations, manifesting with unique symptom profiles. Despite this, prior digital phenotype research has primarily focused on disorder-...

We introduce UbiPhysio, a milestone framework that delivers fine-grained action description and feedback in natural language to support people's daily functioning, fitness, and rehabilitation activities. This expert-like capability assists users in ...

Radio frequency (RF) devices such as Wi-Fi transceivers, radio frequency identification tags, and millimeter-wave radars have appeared in large numbers in daily lives. The presence and movement of humans can affect the propagation of RF signals, further, ...

Facial expression recognition (FER) is a crucial task for human-computer interaction and a multitude of multimedia applications that typically call for friendly, unobtrusive, ubiquitous, and even long-term monitoring. Achieving such a FER system meeting ...

This paper introduces MultiMesh, a multi-subject 3D human mesh construction system based on commodity WiFi. Our system can reuse commodity WiFi devices in the environment and is capable of working in non-line-of-sight (NLoS) conditions compared with the ...

Ear wearables (earables) are emerging platforms that are broadly adopted in various applications. There is an increasing demand for robust earables authentication because of the growing amount of sensitive information and the IoT devices that the earable ...

The focus of Advanced driver-assistance systems (ADAS) is extending from the vehicle and road conditions to the driver because the driver's attention is critical to driving safety. Although existing sensor and camera based methods can monitor driver ...

User authentication on smartphones needs to balance both security and convenience. Many image-based face authentication methods are vulnerable to spoofing and are plagued by privacy breaches, so models based on acoustic sensing have emerged to achieve ...

Energy-saving features (ESFs) represent a simple way to reduce the resource consumption of home appliances (HAs), yet they remain under-utilized. While prior research focused on increasing the use of ESFs through behavior change interventions, there is ...

Underwater Visible Light Communication (UVLC) is promising due to its relatively strong penetration capability in water and large frequency bandwidth. Visible Light Communication (VLC) is also considered a safer wireless communication paradigm as light ...

Reducing the environmental footprint of electronics and computing devices requires new tools that empower designers to make informed decisions about sustainability during the design process itself. This is not possible with current tools for life cycle ...

Arrhythmia is a common problem of irregular heartbeats, which may lead to serious complications such as stroke and even mortality. Due to the paroxysmal nature of arrhythmia, its long-term monitoring and early detection in daily household scenarios, ...