Related papers: CommSense: A Wearable Sensing Computational Framew…
Large language models (LLMs) are increasingly grounded in sensor data to perceive and reason about human physiology and the physical world. However, accurately interpreting heterogeneous multimodal sensor data remains a fundamental…
The rise of wearable smart devices raises unprecedented opportunities for self-improvement through ubiquitous behavior tracking and guidance. However, the design of effective wearable behavior intervention systems remains relatively…
Effective patient-provider communication is difficult to assess at scale. We examine whether large language models (LLMs) can track 20 social behaviors from clinical transcripts without fine-tuning. Across three model families and multiple…
After decades of use in dictation and, more recently, ambient documentation, speech is emerging as a primary modality for interacting with technology and AI in healthcare. Yet medical speech recognition remains difficult: systems must…
Recent growth in popularity of mobile and wearable devices has re-ignited the need for reliable and stealthy communication side-channels to enable applications such as secret/PIN sharing, co-location proofs and user authentication. Existing…
Time-series foundation models excel at tasks like forecasting across diverse data types by leveraging informative waveform representations. Wearable sensing data, however, pose unique challenges due to their variability in patterns and…
Digitally presenting physiological signals as biofeedback to users raises awareness of both body and mind. This paper describes the effectiveness of conveying a physiological signal often overlooked for communication: breathing. We present…
Integrated sensing and communication (ISAC) has been recognized as a key enabler and feature of future wireless networks. In the existing works analyzing the performances of ISAC, discrete-time systems were commonly assumed, which, however,…
Modern IoT and sensor networks generate vast amounts of data, posing significant challenges for storage, transmission, and real-time processing. Traditional approaches, such as compressive sensing and machine learning-based compression,…
Modern mobile devices are able to provide context-aware and personalized services to the users, by leveraging on their sensing capabilities to infer the activity and situation in which a person is currently involved. Current solutions for…
Research shows that dialogue, the interactive process through which participants articulate their thinking, plays a central role in constructing shared understanding, coordinating action, and shaping learning outcomes in teams. Analysing…
Collaborative perception has recently shown great potential to improve perception capabilities over single-agent perception. Existing collaborative perception methods usually consider an ideal communication environment. However, in…
Massive multiple-input multiple-output (MIMO) technology is a key enabler of modern wireless communication systems, which demand accurate downlink channel state information (CSI) for optimal performance. Although deep learning (DL) has…
People have the ability to make sensible assumptions about other people's emotional states by being sympathetic, and because of our common sense of knowledge and the ability to think visually. Over the years, much research has been done on…
Medical education faces challenges in providing scalable, consistent clinical skills training. Simulation with standardized patients (SPs) develops communication and diagnostic skills but remains resource-intensive and variable in feedback…
Round-the-clock monitoring of human behavior and emotions is required in many healthcare applications which is very expensive but can be automated using machine learning (ML) and sensor technologies. Unfortunately, the lack of…
Advances in wireless communication and signal processing facilitate integrated sensing and communication a compelling technology that intrinsically combines sensing and communication functionalities for the dual purpose exploitation of…
Semantic communication aims to transmit information most relevant to a task rather than raw data, offering significant gains in communication efficiency for applications such as telepresence, augmented reality, and remote sensing. Recent…
Wireless body area network (WBAN) is emerging in the mobile healthcare area to replace the traditional wire-connected monitoring devices. As wireless data transmission dominates power cost of sensor nodes, it is beneficial to reduce the…
Citizen Science aims to engage people in research activities on important issues related to their well-being. Smart Cities aim to provide them with services that improve the quality of their life. Both concepts have seen significant growth…