Northwestern | Rice | Utah | Vermont | Moffitt | Ohio State | UCLA | Johns Hopkins | Dartmouth | Minnesota
All of these studies utilize both mCerebrum and Cerebral Cortex
mCerebrum (mobile) contributors: Monowar Hossain, Nusrat Nasrin, Anandatirtha Nandugudi, Nasir Ali, and Timothy Hnat
Cerebral Cortex (cloud) contributors: Nasir Ali, Anandatirtha Nandugudi, and Timothy Hnat
• AutoSense
• MotionSense
• Phone
This study examines 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.
• AutoSense
MotionSense
• Phone
This feasibility study examines the effects of delivering mindfulness strategies via smartphones on key mechanisms underlying smoking cessation among low socioeconomic status, racially/ethnically diverse smokers.
• AutoSense
• MotionSense
• Phone
This study examines the multiple neurocognitive processes that have previously been implicated in relapse among smokers who are both successful and unsuccessful in maintaining smoking abstinence.
• Microsoft Band
• EasySense
• Phone
• Omron Scale
• Omron Blood Pressure
This study is 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.
• OralB Toothbrush
• MotionSense
• Phone
This study develops 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.
• AutoSense
• MotionSense
• Phone
This study is 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.
• AutoSense
• MotionSense
• Phone
This study examines mechanisms of self-regulatory function via both passive physiological sensing and ecological momentary assessment (EMA) both within and outside of laboratory settings.