Smart and Connected Health

The prototype wristwatch here, called CommSense, offers meaningful, real-time ways to improve how doctors and nurses talk with their patients. (Photo by Sanjay Suchak, University Communications)

Engineering the Future of Personalized and Connected Healthcare

The Link Lab advances research that combines cyber-physical systems, AI, sensing, and data-driven technologies to improve health outcomes and transform the delivery of care. Our faculty develop innovative solutions that support earlier detection, personalized interventions, and continuous monitoring across a wide range of health conditions, including asthma, dementia, depression, diabetes, obesity, and cardiovascular disease. From wearable and in-body devices to intelligent environments, Link Lab researchers are creating technologies that extend care beyond clinical settings and enable healthier, more connected lives.

FEATURED RESEARCH

  • Professional headshots of Somayeh Asadi, Afsaneh Doryab, and Homa Alemzadeh displayed side by side.

    Interdisciplinary Collaboration

    Last year, Link Lab faculty convened monthly around the Lab’s four core research themes to foster collaboration. One tangible outcome of these meetings was the development of a seed grant proposal led by three faculty members: Afsaneh Doryab (SIE), Homa Alemzadeh (ECE), and Somayeh Asadi (CEE).

     

    Their interdisciplinary project, “Toward Intelligent, Privacy-Preserving Mental-Health Support Systems for Low-Connectivity Rural Communities,” reflects the collaborative spirit and impact of these efforts.

  • Four line charts compare spectrometer signals (blue) with recovered signals (orange) across wavelengths ranging from approximately 400 to 1000 nanometers. The charts are titled Glucose Signal Recovery, LDL Signal Recovery, HDL Signal Recovery, and VLDL Signal Recovery. The x-axis shows wavelength (nm) and the y-axis shows absorbance. In each chart, the recovered signal closely follows the spectrometer signal, demonstrating successful reconstruction of spectral data for glucose and different lipoprotein type

    Resilience-by-Construction Design of Medical Devices

    Link Lab faculty Amanda Watson (ECE) and Afsaneh Doryab (SIE) along with their student researchers evaluated whether an off-the-shelf wearable device with a multiwavelength optical sensor can detect nutritional molecules in the blood and recover their molecular signatures compared with a laboratory spectrophotometer. The findings demonstrate the potential of wearable biosensing technology to provide noninvasive, real-time monitoring of nutritional intake, offering a promising new approach for managing nutrition-related disorders.

     

    PUBLICATION: Characterization and Feasibility of Wearable Spectroscopic Tracking of Nutrition Biomarkers

  • College student walking on a campus sidewalk while looking at a smartphone, with other students in the background.

    Mental Health Monitoring Through Mobile Sensing

    Laura Barnes (SIE) is leveraging smartphones and wearables to monitor mental health levels (e.g. anxiety and depression) and designing AI-powered models for just-in-time interventions to reduce symptoms.

     

    PUBLICATION: Demonicsalmon: Monitoring Mental Health and Social Interactions of College Students Using Smartphones

 

Afsaneh Doryab

Amanda Watson

Benton Calhoun

Cong Shen

Daniel Otero-Leon

Daniel Quinn

Gregory Gerling

Haibo Dong

Homa Alemzadeh

Hongru Du

Laura Barnes

Lu Feng

Maite Brandt-Pearce

Matthew Bolton

Qiaochu Zhang

Rich Nguyen

Somayeh Asadi

Subigya Nepal

Xiaoxuan Yang

Ye (Sarah) Sun

Yixin Sun

Search publications by keyword, author, year, or journal to learn more about the research emerging from the Link Lab.

Publications

Faculty Spotlight Video

Person seated in a conference or classroom setting, speaking during a recorded interview while gesturing with one hand. The room contains tables, office chairs, and a large wall-mounted display screen in the background. A lower-third graphic identifies the speaker as “Daniel Otero-Leon, Professor, Systems & Information Engineering.”

Explore More Smart Health Research

LAURA BARNES

This qualitative study explored system-level factors that influence the successful implementation of AI-supported communication tools in healthcare, using the CommSense platform. Findings suggest that integrating these technologies into existing clinical workflows, engaging key stakeholders throughout implementation, and providing tailored feedback can help overcome communication challenges and improve clinician training and patient care.

PUBLICATION: Implementing artificial intelligence (AI)-supported communication tools in healthcare: System-level perspectives

Diaz, Carmen M.; Reed, Kelly L.; Barnes, Laura E.; Flickinger, Tabor; Truong, Trish; Wang, Zhiyuan; LeBaron, Virginia, DIGITAL HEALTH, 2026

SARAH SUN

This work introduces a physics-based framework for distributed sensing in soft continuum robots, demonstrating how strategically placed embedded sensors can accurately predict the motion of a soft robotic finger while reducing the need for centralized control. The theoretical approach, validated through simulations and experiments, establishes principles for sensor placement and shows that a finite number of well-positioned sensors can enable real-time trajectory prediction, with potential applications across a broad range of compliant soft robotic systems.

PUBLICATION: Distributed Sensing Enabled Embodied Intelligence for Soft Finger Manipulation

Chukwuemeka Ochieze; Zhen Liu; Ye Sun, Actuators, 2025

HOMA ALEMZADEH

Researchers developed EgoEMS, a large-scale multimodal dataset of realistic emergency medical response scenarios designed to support the development of AI assistants for Emergency Medical Services (EMS). The dataset includes more than 20 hours of simulated emergency care with extensive annotations and benchmark tasks, providing a foundation for AI systems that can assist first responders with real-time procedural guidance and decision-making.

PUBLICATION: EgoEMS: A High-Fidelity Multimodal Egocentric Dataset for Cognitive Assistance in Emergency Medical Services

Weerasinghe, Keshara; Ge, Xueren; Heick, Tessa; Wijayasingha, Lahiru Nuwan; Cortez, Anthony; Satpathy, Abhishek; Stankovic, John; Alemzadeh, Homa, Proceedings of the AAAI Conference on Artificial Intelligence, 2026 

Homa Alemzadeh Wins Test-of-Time Award

Homa Alemzadeh (Associate Professor, Electrical and Computer Engineering) received the Dependable Systems and Networks Test-of-Time Award, recognizing research that has demonstrated lasting relevance and impact over the past decade. Her award honors pioneering work in safe and secure surgical robotics.

Read Article

Smart and Connected Health News

  • UVA Launches Undergraduate Engineering Research Minor

    UVA Engineering’s new 18-credit-hour engineering research minor trains undergraduates to conduct and publish research, building skills employers and graduate schools seek.

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  • Focused Ultrasound to Transform Brain Disease Treatment

    UVA researchers are exploring how focused ultrasound could transform the treatment of brain tumors and other neurological diseases by offering new ways to deliver therapies to the brain.

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  • Multimillion NIH Award Advances UVA Women’s Health Research

    UVA Engineering researchers are collaborators on an NIH-funded, $12 million project to digitally model how hormonal differences between men and women can impact the effectiveness of some medications.

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