Transforming Health & Wellness Through Wearable AI

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// TRANSFORMING HEALTH & WELLNESS

Research Datasets

Deployments

Research software has been utilized in numerous collaborative studies in an array of categories including:

Stress Detection

Penn State University – This study utilized smartwatches and the MOODS app to explore the dynamic relationships between individuals’ personalized drivers of momentary risk and disease progression, aiming to identify targets for temporally-precise interventions.

Opioid & Pain Detection

Johns Hopkins University – This project was designed to examine the feasibility for detecting opioid use and pain flares among a population of individuals experiencing chronic pain (sickle-cell disease), for which they also regularly took opioid medications.  

Smoking Cessation

Northwestern University – This study evaluated the feasibility of a just-in-time intervention to delay or prevent smoking relapse in smokers attempting to quit.

Rice University – This study examined smoking cessation in a population of African American smokers who were attempting to quit.

University of Utah – This study examined the influence of socioeconomic status, social history, contextual and environmental influences, biobehavioral/psychosocial predispositions, and acute momentary precipitants on stress, smoking lapse, and abstinence among 300 smokers attempting to quit.

Moffitt Cancer Center – This feasibility study examined the effects of delivering mindfulness strategies via smartphones on key mechanisms underlying smoking cessation among low socioeconomic status, racially/ethnically diverse smokers.

University of Vermont – This study examined the multiple neurocognitive processes that had previously been implicated in relapse among smokers who were both successful and unsuccessful in maintaining smoking abstinence.

Congestive Heart Failure

The Ohio State University – This study was designed to evaluate the efficacy of the novel EasySense wireless, contactless system in assessing pulmonary congestion via measurements of thoracic impedance and cardiac and lung motion in patients with congestive heart failure (CHF) during hospitalization and post-discharge.

Oral Health

University of California, Los Angeles – This study developed the Remote Oral Behaviors Assessment System (ROBAS) by integrating a multimodal sensing platform (smart toothbrush and wrist sensors) with the mCerebrum software platform (physiological and EMA data logging, transmission, and activity/behavior inference system) for the testing and iterative refinement via laboratory simulators and test subjects.

Cocaine Use

Johns Hopkins University – This study was designed to extend previous work in the development of methods to automatically detect the timing of cocaine use from cardiac interbeat interval and physical activity data derived from wearable, unobtrusive mobile sensor technologies.

Behavior Change

Dartmouth College – This study examined mechanisms of self-regulatory function via both passive physiological sensing and ecological momentary assessment (EMA) both within and outside of laboratory settings.

Workplace Performance

University of Minnesota – This study utilized wearable sensors to objectively assess everyday job performance for employers.

Last updated: 6/10/24