Smart and Connected Health
Smart and Connected Health Research
Personalized technology addressing pressing health challenges.
Treating areas such as asthma, dementia, depression, diabetes, obesity, and cardiac conditions, Link Lab’s work builds on a growing suite of enabling technologies to advance care in the hospital, extend care and awareness throughout the everyday life of the patient, and achieve a more holistic and robust understanding of conditions. Work in this area spans in-body, on-body, and in-situ sensors and actuators that detect and affect physiological, behavioral, and psychological states. Sensing and actuation, data mining, machine learning, and natural language processing are all integral parts of the solutions.
RESEARCH PROJECTS
Detecting Conflicting Health Information
An increasing number of people are relying on online and mobile health apps for health management. These sources often provide conflicting information regarding diet, lifestyle, and medication that might cause adverse side effects. We have developed PreCluDe to solve this problem of conflict detection in an interpretable and context-aware manner. READ MORE
PUBLICATIONS
PRECLUDE: CONFLICT DETECTION IN TEXTUAL HEALTH ADVICE, S. Preum, M. Mondol, M. Ma, H. Wang, and J. Stankovic, Percom, March 2017.
PRECLUDE2: PERSONALIZED AND CONTEXT-AWARE CONFLICT DETECTION IN HETEROGENEOUS HEALTH APPLICATIONS, S. Preum, M. Mondol, M. Ma, H. Wang, and J. Stankovic, Journal of Pervasive and Mobile Computing, Vol. 42, Dec. 2017, pp. 226-247.
Mental Health Monitoring Through Mobile Sensing
Mehdi Boukhechba | LAURA BARNES | BETHANY TEACHMAN
The goal of this project is to leverage sensor-rich smartphones and wearables to monitor mental health levels (e.g. anxiety and depression) and design AI-powered models for just-in-time interventions to reduce symptoms. READ MORE
PUBLICATIONS
PREDICTING SOCIAL ANXIETY FROM GLOBAL POSITIONING SYSTEM TRACES OF COLLEGE STUDENTS: FEASIBILITY STUDY, Mehdi Boukhechba, Philip Chow, Karl Fua, Bethany A Teachman, Laura E Barnes, JMIR mental health
DEMONICSALMON: MONITORING MENTAL HEALTH AND SOCIAL INTERACTIONS OF COLLEGE STUDENTS USING SMARTPHONES, Mehdi Boukhechba, Alexander R Daros, Karl Fua, Philip I Chow, Bethany A Teachman, Laura E Barnes, Smart Health Journal
FluiSense: Fluid intake monitoring for CKD patients
Mehdi Boukhechba | EMAAD ABDEL-RAHMAN | BRENDAN BOWMAN | JAMIE ZOELLNER
The goal of project is to design a platform capable of monitoring fluid intake for end stage kidney disease patients. FluiSense is a multimodal sensor framework that extracts signatures from multiple sensors on smartphones and wrist-worn watches to develop biomarkers predictive of fluid intake.
Resilience-by-Construction Design of Medical Devices
This project focuses on development of a “resilience-by-construction” design methodology for the human-in-the-loop medical CPS (e.g., artificial pancreas systems, surgical robots). We combine model- and data-driven approches for automated synthesis of context-aware safety monitors that detect accidental or malicious faults and prevent patient harm. READ MORE
PUBLICATIONS
REAL-TIME CONTEXT-AWARE DETECTION OF UNSAFE EVENTS IN ROBOT-ASSISTED SURGERY, M. S. Yasar, H. Alemzadeh, In the 50th IEEE/IFIP Int. Conf. on Dependable Systems and Networks (DSN), 2020.
TARGETED ATTACKS ON TELEOPERATED SURGICAL ROBOTS: DYNAMIC MODEL-BASED DETECTION AND MITIGATION, H. Alemzadeh, D. Chen, X. Li, T. Kesavadas, Z. T. Kalbarczyk, R. K. Iyer, Proc. 46th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2016.
Cognitive Assistant Systems for Emergency Response
HOMA ALEMZADEH | JOHN STANKOVIC | RONALD WILLIAMS
This project focuses on the development of a wearable cognitive assistant that improves situational awareness in emergency response. CognitiveEMS combines real-time sensing and computing with resilient data analytics for inferring context from heterogeneous data at an incident scene and generating just-in-time actionable feedback for responders. READ MORE
PUBLICATIONS
A BEHAVIOR TREE COGNITIVE ASSISTANT SYSTEM FOR EMERGENCY MEDICAL SERVICES, S. Shu, S. Preum, H. M. Pitchford, R. D. Williams, J. Stankovic, H. Alemzadeh In the IEEE IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.
A REVIEW OF COGNITIVE ASSISTANTS FOR HEALTHCARE: TRENDS, PROSPECTS, AND FUTURE DIRECTIONS, S. Preum, S. Munir, M. Ma, M. S. Yasar, D. J. Stone, R. Williams, H. Alemzadeh, J. Stankovic, ACM Computing Surveys, 2021.