Anxiety Detection Leveraging Mobile Passive Sensing

08/09/2020
by   Lionel Levine, et al.
0

Anxiety disorders are the most common class of psychiatric problems affecting both children and adults. However, tools to effectively monitor and manage anxiety are lacking, and comparatively limited research has been applied to addressing the unique challenges around anxiety. Leveraging passive and unobtrusive data collection from smartphones could be a viable alternative to classical methods, allowing for real-time mental health surveillance and disease management. This paper presents eWellness, an experimental mobile application designed to track a full-suite of sensor and user-log data off an individual's device in a continuous and passive manner. We report on an initial pilot study tracking ten people over the course of a month that showed a nearly 76 on the passively monitored features.

READ FULL TEXT
research
06/12/2016

SenseFlow: An Experimental Study for Tracking People

The main challenges in large-scale people tracking are the recognition o...
research
09/26/2020

Mental Health and Sensing

Mental health is a global epidemic, affecting close to half a billion pe...
research
08/09/2019

Crowdsourcing real-time viral disease and pest information. A case of nation-wide cassava disease surveillance in a developing country

In most developing countries, a huge proportion of the national food bas...
research
08/19/2019

Mobile community sensing with smallholder farmers in a developing nation; A scaled pilot for crop health monitoring

Previously, crowdsourcing experiments in surveillance of crop diseases a...
research
03/06/2021

Smart Speakers, the Next Frontier in Computational Health

The rapid dissemination and adoption of smart speakers has enabled subst...
research
04/03/2017

Wireless Health Monitoring using Passive WiFi Sensing

This paper presents a two-dimensional phase extraction system using pass...

Please sign up or login with your details

Forgot password? Click here to reset