Varun Mishra

• Ph.D.
• Assistant Professor at Northeastern University

Smartphones and wearable sensors offer an unprecedented ability to collect peripheral psychophysiological signals across diverse timescales, settings, populations, and modalities. However, open-source software development has yet to keep pace with rapid advancements in hardware technology and availability, creating an analytical barrier that limits...

Longitudinal passive sensing studies for health and behavior outcomes often have missing and incomplete data. Handling missing data effectively is thus a critical data processing and modeling step. Our formative interviews with researchers working in longitudinal health and behavior passive sensing revealed a recurring theme: most researchers consi...

Understanding the daily lives and routines of older adults is crucial to facilitate aging in place. Ubiquitous computing technologies like smartphones and wearables that are easy to deploy and scale, have become a popular method to collect comprehensive and longitudinal data for various demographics. Despite their popularity, several challenges per...

BACKGROUND Mental health has become a growing concern among university students. According to the Healthy Minds Study (HMS) National Report 2022-2023, 46% of students have been diagnosed with a mental disorder by a health professional, reflecting a nearly 50% increase from 2013 to 2021. While researchers have developed various technologies to help...

Researchers have long recognized the socio-technical gaps in personal tracking research, where machines can never fully model the complexity of human behavior, making it only able to produce basic rule-based outputs or "black-box" results that lack clear explanations. Real-world deployments rely on experts for this complex translation from sparse d...

Client-Service Representatives (CSRs) are vital to organizations. Frequent interactions with disgruntled clients, however, disrupt their mental well-being. To help CSRs regulate their emotions while interacting with uncivil clients, we designed Pro-Pilot, an LLM-powered assistant, and evaluated its efficacy, perception, and use. Our comparative ana...

Despite recent advances in cancer treatments that prolong patients' lives, treatment-induced cardiotoxicity remains one severe side effect. The clinical decision-making of cardiotoxicity is challenging, as non-clinical symptoms can be missed until life-threatening events occur at a later stage, and clinicians already have a high workload centered o...

Mental health has become a growing concern among university students. While medication is a common treatment, understanding how university students manage their medication for mental health symptoms in real-world practice has not been fully explored. In this study, we conducted semi-structured interviews with university students to understand the u...

Cardiotoxicity induced by cancer treatment has become a major clinical concern, affecting the long-term survival and quality of life of cancer patients. Effective clinical decision-making, including the detection of cancer treatment-induced cardiotoxicity and the monitoring of associated symptoms, remains a challenging task for clinicians. This stu...

Smartphones and wearable sensors offer an unprecedented ability to collect peripheral psychophys-iological signals across diverse timescales, settings, populations, and modalities. However, open-source software development has yet to keep pace with rapid advancements in hardware technology and availability , creating an analytical barrier that limi...

Just-In-Time Adaptive Interventions (JITAI) have the potential to provide effective support for health behavior by delivering the right type and amount of intervention at the right time. The timing of interventions is crucial to ensure that users are receptive and able to use the support provided. Previous research has explored the association of c...

Background: Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD. Objective: The aim is to examine patient enga...

BACKGROUND Multiple digital data sources can capture moment-to-moment information to advance a robust understanding of opioid use disorder (OUD) behavior, ultimately creating a digital phenotype for each patient. This information can lead to individualized interventions to improve treatment for OUD. OBJECTIVE The aim is to examine patient engageme...

Introduction Across the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses have risen precipitously in recent years. Several effective medications for OUD (MOUD) exist and have been shown to be life-saving. A large volume of research has identified a confluence of factors that predict attrition and continued substan...

[This corrects the article DOI: 10.3389/fpubh.2021.625640.].

Background and Objective: Researchers use wearable sensing data and machine learning (ML) models to predict various health and behavioral outcomes. However, sensor data from commercial wearables are prone to noise, missing, or artifacts. Even with the recent interest in deploying commercial wearables for long-term studies, there does not exist a st...

Background: The current COVID-19 coronavirus pandemic is an emergency on a global scale, with huge swathes of the population required to remain indoors for prolonged periods to tackle the virus. In this new context, individuals' health-promoting routines are under greater strain, contributing to poorer mental and physical health. Additionally, indi...

Just-In-Time Adaptive Intervention (JITAI) is an emerging technique with great potential to support health behavior by providing the right type and amount of support at the right time. A crucial aspect of JITAIs is properly timing the delivery of interventions, to ensure that a user is receptive and ready to process and use the support provided. So...

Recent developments of novel in-vehicle interventions show the potential to transform the otherwise routine and mundane task of commuting into opportunities to improve the drivers' health and well-being. Prior research has explored the effectiveness of various in-vehicle interventions and has identified moments in which drivers could be interruptib...

Recent advances in wearable sensor technologies have led to a variety of approaches for detecting physiological stress. Even with over a decade of research in the domain, there still exist many significant challenges, including a near-total lack of reproducibility across studies. Researchers often use some physiological sensors (custom-made or off-...

JITAI is an emerging technique with great potential to support health behavior by providing the right type and amount of support at the right time. A crucial aspect of JITAIs is properly timing the delivery of interventions, to ensure that a user is receptive and ready to process and use the support provided. Some prior works have explored the asso...

Recent wearable devices enable continuous and unobtrusive monitoring of human's physiological parameters, like e.g., electrodermal activity and heart rate, over long periods of time in everyday life settings. Continuous monitoring of these parameters enables the creation of systems able to predict affective states and stress with the goal of provid...

Background The Assistant to Lift your Level of activitY (Ally) app is a smartphone application that combines financial incentives with chatbot-guided interventions to encourage users to reach personalized daily step goals. Purpose To evaluate the effects of incentives, weekly planning, and daily self-monitoring prompts that were used as interventi...

Timely detection of an individual's stress level has the potential to improve stress management, thereby reducing the risk of adverse health consequences that may arise due to mismanagement of stress. Recent advances in wearable sensing have resulted in multiple approaches to detect and monitor stress with varying levels of accuracy. The most accur...

The application of digital technologies to better assess, understand, and treat substance use disorders (SUDs) is a particularly promising and vibrant area of scientific research. The National Drug Abuse Treatment Clinical Trials Network (CTN), launched in 1999 by the U.S. National Institute on Drug Abuse, has supported a growing line of research t...

Recent advancements in sensing techniques for mHealth applications have led to successful development and deployments of several mHealth intervention designs, including Just-In-Time Adaptive Interventions (JITAI). JITAIs show great potential because they aim to provide the right type and amount of support, at the right time. Timing the delivery of...

Advances in mobile, wearable and embedded sensing technology have created new opportunities for research into a variety of health conditions. This has led to the field of mobile health (mHealth), which covers a full spectrum of works, including but not limited to disease surveillance, treatment support, epidemic outbreak tracking, and chronic disea...

With the rapid growth in the number of Internet of Things (IoT) devices with wireless communication capabilities, and sensitive information collection capabilities, it is becoming increasingly necessary to ensure that these devices communicate securely with only authorized devices. A major requirement of this secure communication is to ensure that...

Listening to music has been studied as a method for combating the rapidly increasing stress levels of adolescents. Previous studies yielded inconsistent results and neglected specific factors including the time relative to the stressor and the duration of time in which participants listened to music. We conducted a survey and lab experiment to inve...

Mental health issues affect a significant portion of the world's population and can result in debilitating and life-threatening outcomes. To address this increasingly pressing healthcare challenge, there is a need to research novel approaches for early detection and prevention. Toward this, ubiquitous systems can play a central role in revealing an...

Wrist-worn devices hold great potential as a platform for mobile health (mHealth) applications because they comprise a familiar, convenient form factor and can embed sensors in proximity to the human body. Despite this potential, however, they are severely limited in battery life, storage, bandwidth, computing power, and screen size. In this paper,...

BACKGROUND Smartphones enable the implementation of just-in-time adaptive interventions (JITAIs) that tailor the delivery of health interventions over time to user- and time-varying context characteristics. Ideally, JITAIs include effective intervention components, and delivery tailoring is based on effective moderators of intervention effects. Usi...

BACKGROUND: Smartphones enable the implementation of just-in-time adaptive interventions (JITAIs) that tailor the delivery of health interventions over time to user- and time-varying context characteristics. Ideally, JITAIs include effective intervention components, and delivery tailoring is based on effective moderators of intervention effects. Us...

Timely detection of an individual's stress level has the potential to expedite and improve stress management, thereby reducing the risk of adverse health consequences that may arise due to unawareness or mismanagement of stress. Recent advances in wearable sensing have resulted in multiple approaches to detect and monitor stress with varying levels...

The advances in mobile and wearable sensing have led to a myriad of approaches for stress detection in both laboratory and free-living settings. Most of these methods, however, rely on the usage of some combination of physiological signals measured by the sensors to detect stress. While these solutions work great in a lab or a controlled environmen...

Background: Smartphones enable the implementation of just-in-time adaptive interventions (JITAIs) that tailor the delivery of health interventions over time to user- and time-varying context characteristics. Ideally, JITAIs include effective intervention components, and delivery tailoring is based on effective moderators of intervention effects. U...

No behavior has an impact on human health as great as physical activity (PA). We therefore developed Ally, a smartphone-based 6-week PA intervention. Ally seeks to exploit the ubiquity and sensing capabilities of mobile phones to adapt the provision of PA interventions to the context of the user. In this research we investigate the following resear...

In this work, we attempt to determine whether the contextual information of a participant can be used to predict whether the participant will respond to a particular Ecological Momentary Assessment (EMA) trigger. We use a publicly available dataset for our work, and find that by using basic contextual features about the participant's activity, conv...

Self-tracking consists of recording the behaviors that occur in one’s daily life. Self-tracking studies can provide researchers with passively sensed information about individual’s daily behaviors and environments and actively logged information (e.g., self-reports). This method has great promise for obtaining detailed records of behavior in natura...

In this work, we propose HuMorse, a universal home automation system for the elderly and people with disabilities of vision, speech or paralyzed limbs. Analog input using facial processing or tilt gestures is captured via smart-phone and is mapped to Morse code - dots and dashes. This Morse code sequence can be interpreted as words in a group to fo...

Environmental monitoring using external and Smartphone-interfaced wireless sensors has been widely used in the past. The roadblocks start emerging when we use on-board sensors in off-the-shelf Smartphones to estimate context aware environmental parameters like ambient temperature, humidity and atmospheric pressure. In this work, we evaluate the sen...