Collaborative Research: HCC: MEDIUM: Body as Intervention: Toward Closed-Loop, Embodied Behavioral Health Interventions

There has been a drastic increase in stress and anxiety in the U.S., leading to a mental health pandemic. The need for effective mental health interventions is more urgent now than ever. By monitoring users' symptoms and their context (e.g., when someone is having an anxiety attack or experiencing cravings when passing by a bar) through wearables and IoT (Internet of Things) devices, mobile health (mHealth) technologies have the potential to transform mental health care.

Despite the advanced monitoring capability, most existing mHealth interventions are digitization of traditional health interventions that do not deliver in-the-moment precision interventions in response to users' symptoms. As such, they inherit the limitations of their predecessors: the reliance on human motivation and the need for active engagement to be effective, resulting in limited adherence.

To address this problem, the investigators will develop a class of novel solutions – sensory interventions – that can be effective without disrupting the users or requiring their active engagement. Sensory interventions are real-time closed-loop systems that directly act on the users’ bodies or immediate environment in response to users behavioral or physiological signals.

Unlike existing solutions, sensory interventions combine applied engineering, signal processing, and machine learning to trigger interventions autonomously without user effort. The project will create three types of closed-loop wearable and IoT systems that use different modalities (vibration, airflow, and touch) to deliver sensory interventions in mental health contexts, such as cravings, workplace stress, and social stress.

Ultimately, this project will enable mHealth interventions to be as rich, diverse, and personalized as mHealth monitoring solutions. This project will produce open-source software, hardware designs, and datasets. Collaborations with Cornell Tech Precision Health Initiative and with the University of Chicago Medicine and their clinical and industry partners will accelerate the dissemination of research through clinical evaluations and commercialization.

Most existing mHealth behavioral health interventions, although coupled with advanced sensing systems to detect health needs, require conscious cognitive processing of information and active participation from users to be effective. This project will introduce and develop the concept of sensory interventions, a novel class of mHealth interventions that require little or no cognitive awareness to be effective.

This project will investigate sensory interventions in four stages: (i) investigate and map modalities of external (electromechanical) stimuli to actuate neurological responses that produce a neurophysiological effect (ii) design and develop devices that enable these sensory interventions within the constraints of mHealth, (iii) determine physiological signals that are associated with target behaviors and integrate sensing systems, signal processing, and machine learning with sensory interventions to achieve closed-loop systems that automatically triggers intervention, and (iv) evaluate the efficacy, usability, and acceptability of the closed-loop systems (both in-lab and in situ). Throughout this process, the investigators will evaluate and characterize how sensory interventions impact three common stress-induced mental health challenges: substance cravings, workplace stress, and social stress.

To intervene in substance cravings, the investigators will leverage heart rate biofeedback, develop a smartwatch-based system to deliver biofeedback using vibrotactors, and evaluate how such vibrotactile actuation mitigates alcohol and nicotine cravings. To intervene in workplace stress, the investigators will leverage breathing regulations, develop a fan-based system that alters the perception of airflow around the nose, and evaluate how such airflow entrains slow, guided breathing in the workplace.

To intervene in social stress, the investigators will leverage affective touch, develop an arm-worn device that activates affective touch neurons, and evaluate how affective touch helps regulate social stress. Collectively, this research will enable a new class of mHealth interventions that are responsive to users’ health context in real-time and can be effective irrespective of users cognitive capacity or availability.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.