A5083849277- Behavioral Health and Interventions
- Mental Health Research Topics
- Innovative Human-Technology Interaction
- Digital Mental Health Interventions
- Mobile Health and mHealth Applications
- ICT in Developing Communities
- Context-Aware Activity Recognition Systems
- Physical Activity and Health
- Mobile Crowdsensing and Crowdsourcing
- Usability and User Interface Design
- Personal Information Management and User Behavior
- Human Mobility and Location-Based Analysis
- Obesity, Physical Activity, Diet
- Child Development and Digital Technology
- Digital Games and Media
- Neuroscience and Music Perception
- Innovative Approaches in Technology and Social Development
- Urban Transport and Accessibility
- Educational Games and Gamification
- Time Series Analysis and Forecasting
- Statistical Methods and Bayesian Inference
- Smart Cities and Technologies
- Personality Traits and Psychology
- Death Anxiety and Social Exclusion
- Data Visualization and Analytics
Photon Spot (United States)
2023-2024
Northeastern University
2016-2024
Samsung (India)
2015-2016
Indian Institute of Technology Guwahati
2012-2013
Ecological Momentary Assessment (EMA) is a method of in situ data collection for assessment behaviors, states, and contexts. Questions are prompted during everyday life using an individual's mobile device, thereby reducing recall bias increasing validity over other self-report methods such as retrospective recall. We describe microinteraction-based EMA ("micro" EMA, or μEMA) smartwatches, where all questions can be answered with quick glance tap -- nearly quickly checking the time on watch....
Mobile-based ecological-momentary-assessment (EMA) is an in-situ measurement methodology where electronic device prompts a person to answer questions of research interest. EMA has key limitation: interruption burden. Microinteraction-EMA(µEMA) may reduce burden without sacrificing high temporal density measurement. In µEMA, all can be answered with ‘at glance' microinteractions. prior 4-week pilot study comparing standard delivered on phone (phone-EMA) vs. µEMA smartwatch (watch-µEMA),...
Ecological momentary assessment (EMA) uses mobile technology to enable in situ self-report data collection on behaviors and states. In a typical EMA study, participants are prompted several times day answer sets of multiple-choice questions. Although the repeated nature reduces recall bias, it may induce participation burden. There is need explore complementary approaches collecting that less burdensome yet provide comprehensive information an individual's A new approach, microinteraction...
The use of intensive sampling methods, such as ecological momentary assessment (EMA), is increasingly prominent in medical research. However, inferences from data are often limited to the subject-specific mean outcome and between-subject variance (i.e., random intercept), despite capability examine within-subject scale) associations between covariates slope). MixWILD (Mixed model analysis With Intensive Longitudinal Data) statistical software that tests effects subject-level parameters...
Ecological momentary assessment (EMA) is an in situ method of gathering self-report on behaviors using mobile devices. In typical phone-based EMAs, participants are prompted repeatedly with multiple-choice questions, often causing participation burden. Alternatively, microinteraction EMA (micro-EMA or μEMA) a type where all the prompts single-question surveys that can be answered 1-tap glanceable conveniently smartwatch. Prior work suggests μEMA may permit substantially higher prompting rate...
Young adulthood (ages 18-29 years) is marked by substantial weight gain, leading to increased lifetime risks of chronic diseases. Engaging in sufficient levels physical activity and sleep, limiting sedentary time are important contributors the prevention gain. Dual-process models decision-making behavior that delineate reflective (ie, deliberative, slow) reactive automatic, fast) processes shed light on different mechanisms underlying adoption versus maintenance these energy-balance...
Content recommender systems often rely on modeling users' past behavioral data to provide personalized recommendations - a practice that works well for suggesting more of the same and media require little time investment from users, such as music tracks. However, this approach can be further optimized where user is higher, podcasts, because there broader space goals might not captured by implicit signals their behavior. Allowing users directly specify help narrow possible recommendations....
Ecological momentary assessment (EMA) is used to gather in-situ self-report on behaviors using mobile devices. Microinteraction EMA (μEMA), a type of where each survey only one single question that can be answered with glanceable microinteraction smartwatch. Prior work shows even when μEMA interrupts far more frequently than smartphone-EMA, yields higher response rates lower burden. We examined the contextual biases associated non-response prompts Based prior and smartwatch use, we...
Mobile games currently occupy a very large market share amongst mobile applications. The success of these depends on how well they appeal to their users. In this paper, four have been analyzed based playability heuristics from the literature study. results give us glimpse in creating positive user experience. Results analysis were then compared with statistics individual understand whether can be attributed judicious following heuristics.
The rise of on-demand music streaming platforms and novel recommendation algorithms have brought a transformative shift in listening, where users an effectively endless supply new to discover. This study aims understand patterns, operationalizing as releases that are everyone, from the perspective genres. Leveraging tracks, users, data Spotify, we empirically analyze patterns 282K releases. We find genres often serve functional purposes, such classical for relaxation, consumed less....
Ecological momentary assessment (EMA) is an approach to collect self-reported data repeatedly on mobile devices in natural settings. EMAs allow for temporally dense, ecologically valid collection, but frequent interruptions with lengthy surveys can burden users, impacting compliance and quality. We propose a method that reduces the length of each EMA question set measuring interrelated constructs, only modest information loss. By estimating potential gain using question-answer prediction...
People differ from each other to the extent which momentary factors, such as context, mood, and cognitions, influence health behaviors. However, statistical models date are limited in their ability test whether association between two variables (i.e., subject-level slopes) predicts a outcome. This study demonstrates novel two-stage modeling strategy that is capable of testing slopes predict outcomes. An empirical case application presented examine there differences moderate-to-vigorous...
Recent studies have shown potentially detrimental effects of the COVID-19 pandemic on physical activity (PA) in emerging adults (ages 18-29 y). However, that examined PA location choices and maintenance for this age group remain limited. The current study investigated changes across 13 months during their associations with population.
Individual empowerment is defined as an increased sense of confidence and control over one's life. Empowerment critical in low-income communities, can be facilitated through the development social, financial human capital. We present a qualitative study community program that seeks to empower neighborhood residents mobile application connects them local resources. Our findings highlight how offline socio-organizational mechanisms worked tandem create gateways for capital building-sparking...
The ILHBN is funded by the National Institutes of Health to collaboratively study interactive dynamics behavior, health, and environment using Intensive Longitudinal Data (ILD) (a) understand intervene on behavior health (b) develop new analytic methods innovate behavioral theories interventions. heterogenous designs, populations, measurement protocols adopted seven studies within created practical challenges, but also unprecedented opportunities capitalize data harmonization provide...
Human activity recognition using wearable accelerometers can enable in-situ detection of physical activities to support novel human-computer interfaces and interventions. However, developing valid algorithms that use accelerometer data detect everyday often requires large amounts training datasets, precisely labeled with the start end times interest. Acquiring annotated is challenging time-consuming. Applied games, such as human computation games (HCGs) have been used annotate images,...
Spinal cord injury (SCI) affects the mobility of 250,000 people per year worldwide. Physical activity (PA) in individuals with SCI is positively associated improved mental and physical health outcomes. Mobile technologies have been developed to motivate increase PA using tracking real-time feedback. We conducted semi-structured interviews participatory design sessions 15 manual wheelchair users eight their family members/friends investigate user impressions future that might use...
In this paper, we present a Human centered Computer Interaction design approach for conceptualization of Persuasive games relevant to Indian cultural context. Core the protocol process adopted involved semi-structured interviews with nineteen families, where parents have reported certain behaviors, which they wished change in their children positive way. On qualitative evaluation parents' responses using Fogg's behavior model as basis, it was found that "diffidence" or "shyness" is one such...
This case study shares our experiences and challenges in understanding the innate needs of typical users smartphone from various socio economic classes a rapidly growing region like India. The objective was to support design commercial ultra-low cost would appeal user experience mass. We were team HCI researchers started by devising formal method segment vast varied group order undertake field study. faced with ranging diverse expectations users, their levels technology exposure means map...
Human activity recognition using wearable accelerometers can enable in-situ detection of physical activities to support novel human-computer interfaces. Many the machine-learning-based algorithms require multi-person, multi-day, carefully annotated training data with precisely marked start and end times interest. To date, there is a dearth usable tools that researchers conveniently visualize annotate multiple days high-sampling-rate raw accelerometer data. Thus, we developed Signaligner Pro,...
<sec> <title>BACKGROUND</title> Ecological momentary assessment (EMA) uses mobile technology to enable in situ self-report data collection on behaviors and states. In a typical EMA study, participants are prompted several times day answer sets of multiple-choice questions. Although the repeated nature reduces recall bias, it may induce participation burden. There is need explore complementary approaches collecting that less burdensome yet provide comprehensive information an individual’s A...