MD2K Center of Excellence
FedEx Institute of Technology, Suite 335
365 Innovation Drive, Memphis, TN 38152
MD2K's research is part of a continuing research effort on the utility of mobile sensors in mHealth.
Active Projects
mDOT Center
The mHealth Center for Discovery, Optimization & Translation of Temporally-Precise Interventions provides the methods, tools, and infrastructure for researchers to discover, optimize and deploy temporally-precise mHealth interventions to address growing public health problems.
mProv
Provenance-based data analytics cyberinfrastructure for high-frequency mobile sensor data gives
mGuard
mGuard leverages Named Data Networking (NDN) to produce the naming scheme and trust model for typical mHealth research data, develop innovative mechanisms for the specification and automated enforcement of sophisticated access control policies, and improve NDN’s pub-sub API to support a broader range of applications.
Completed Projects
MD2K/BD2K
MD2K is part of the National Institutes of Health (NIH) Big Data to Knowledge (BD2K) initiative, designed to support advances in research, policy, and training that are needed for the effective use of Big Data in biomedical research. MD2K develops and deploys cutting edge approaches, methods, software, tools, and other resources that enables biomedical researchers to use Big Data to advance human health.
mPerf
mPerf uses mobile sensors to support productivity and employee well-being. It is an an open-source software platform that allows researchers to transform high-frequency mobile sensor data into biomarkers. mPerf uses this platform to better understand performance and support individual well-being.
mContain
mContain is a free mobile app to help track social distancing during a virus outbreak. It uses smartphone technology to detect proximity encounters (within 6 feet for several minutes) with other app users, displays the number of daily proximity encounters and crowding, and can notify other users about possible exposures to COVID-19 individuals.
Open mHealth
The goal of this project is the development, test and validation, repository and dissemination of a software infrastructure that addresses data FAIR (findable, accessible, interoperable and reusable) using data and metadata standards.
mResearch
The goal of the mResearch project is to make necessary enhancements to the MD2K infrastructure so it becomes a true community resource that computing researchers from across the country and around the world can easily use to conduct reproducible and extensible research on any aspect of the collection and analysis of high-frequency mobile sensor data.
Novel use of mHealth Data
MD2K is part of the National Institutes of Health (NIH) Big Data to Knowledge (BD2K) initiative, designed to support advances in research, policy, and training that are needed for the effective use of Big Data in biomedical research. MD2K develops and deploys cutting edge approaches, methods, software, tools, and other resources that enables biomedical researchers to use Big Data to advance human health.
Context-Awareness & Personalization
The goals of this project are to adapt computational models for detecting stress, craving, smoking, eating and geoexposures from mobile sensor data by incorporating modeling advances; determine timing for intervention and adaptation of content based on detection of the above listed biomarkers; and to facilitate intervention data collection for user students.
EasySense
The collaborative research project developed and evaluated a mobile sensor called EasySense that can provide continuous physiological monitoring without skin contact in the field environments using radio frequency (RF) probes.
SES
The goal of this project is to inform the tailoring of policies and interventions targeted at reducing the profound smoking-related disparities experienced by low socioecoomic status individuals.
Eliminating Tobacco-Related Disparities
The goal of this project is to inform the tailoring of policies and interventions targeted at reducing the profound smoking-related disparities experienced by African Americans.
Novel Use of Technologies
This project aims to examine targets of self-regulatory function among two exemplar populations for which behavior plays a critical role in health outcomes: smokers and individual who binge eat (BED).
ROBAS
The goal of this projects is to build, test, refine, and field-validate the Remote Oral Behaviors Assessment System (ROBAS) that can provide objective, individual-level and ecologically-valid data on oral hygiene behaviors.
Predicting Smoking Abstinence
The goal of this project is to enable the development and evaluation of personalized cessation interventions that can be administered in real-time on smart phones, which could prove potent in preventing relapse.
Affective Science
This project is designed to create a more detailed and comprehensive conceptual model of the role of distinct emotions in self-regulation, as well as the technical, empirical, and analytic foundation necessary to develop effective interventions for smoking cessation and other cancer risk behaviors that can target real time, real world mechanisms.
Detecting Cocaine Use
This project is designed to leverage mHealth technologies to determine the feasibility of detecting cocaine use via smartwatches.
Applying mHealth
The goal of this project is to apply mHealth to tobacco-related health disparities to enhance aspects of resiliency to aid cessation efforts.
FieldStream
FieldStream was a collaborative project funded by the National Science Foundation and involving researchers from Carnegie Mellon University, Georgia Institute of Technology, University of California at Los Angeles, University of Massachusetts at Amherst, and University of Memphis.