Wearable, Environmental, and Smartphone-Based Passive Sensing for Mental Health Monitoring

Abstract

Collecting and analyzing data from sensors embedded in the context of daily life has been widely employed for the monitoring of mental health. Variations in parameters such as movement, sleep duration, heart rate, electrocardiogram, skin temperature, etc., are often associated with psychiatric disorders. Namely, accelerometer data, microphone, and call logs can be utilized to identify voice features and social activities indicative of depressive symptoms, and physiological factors such as heart rate and skin conductance can be used to detect stress and anxiety disorders. Therefore, a wide range of devices comprising a variety of sensors have been developed to capture these physiological and behavioral data and translate them into phenotypes and states related to mental health. Such systems aim to identify behaviors that are the consequence of an underlying physiological alteration, and hence, the raw sensor data are captured and converted into features that are used to define behavioral markers, often through machine learning. However, due to the complexity of passive data, these relationships are not simple and need to be well-established. Furthermore, parameters such as intrapersonal and interpersonal differences need to be considered when interpreting the data. Altogether, combining practical mobile and wearable systems with the right data analysis algorithms can provide a useful tool for the monitoring and management of mental disorders. The current review aims to comprehensively present and critically discuss all available smartphone-based, wearable, and environmental sensors for detecting such parameters in relation to the treatment and/or management of the most common mental health conditions.

What Are We Measuring When We Evaluate Digital Interventions for Improving Lifestyle? A Scoping Meta-Review

“…In experimental conditions, algorithms developed based on physiological proxies of the autonomic nervous system activity (e.g., heart rate, body temperature, skin temperature, and conductance) have demonstrated a high accuracy to detect stress (117). Moreover, smartphone-based episodic audio recordings allow analyses of voice and speech features that may be potential vocal markers of stress (118,119). Phone usage and the number of calls, texts, and interactions in online social media can be used as proxies of social contact or interaction (116,(120)(121)(122), while global positioning system (GPS)-based mobility and conversations captured by smartphone microphones were used to estimate social activity and loneliness in individuals with schizophrenia (123).…”

Lessons learned from psychosocial support and mental health surveys during the 10 years since the Great East Japan Earthquake: Establishing evidence‐based disaster psychiatry

“…As an example of utilization in the situation following COVID‐19 infection, suicide risk was analyzed from messages posted on social network services using AI 75 . The technological capabilities to develop smart health backed by the acquisition and evaluation of biometric information through digital sensing at home, are also improving 80–82 . Thus, effective induction of these advanced technologies is important for overcoming the current situation and building a new mental health and welfare system in Japan in the future.…”

Wearable Sensing Systems for Monitoring Mental Health

“…And these methods are subject to reporting unreliable results due to personal bias, possibly confounding the subsequent clinical decision making for mental health treatments [ 9 , 10 ]. In this context, there has been an increasing interest in wearable sensors that can collect in real time the biosignals associated with mental status [ 11 ]. This review gives an overview of recent developments in several types of wearable sensors, with more focus on sensor materials, that can detect cardiac, respiratory, and perspiratory activities and/or molecular secretion, which can be utilized to support mental health management.…”