88 citations · 298 across the 15 of their papers we have counts for
15 papers
Development and Evaluation of Three Chatbots for Postpartum Mood and Anxiety Disorders
Xuewen Yao, Miriam Mikhelson, S. Craig Watkins +3
In collaboration with Postpartum Support International (PSI), a non-profit organization dedicated to supporting caregivers with postpartum mood and anxiety disorders, we developed…
Cheating off your neighbors: Improving activity recognition through corroboration
Haoxiang Yu, Jingyi An, Evan King +2
Understanding the complexity of human activities solely through an individual's data can be challenging. However, in many situations, surrounding individuals are likely performing…
Understanding Postpartum Parents' Experiences via Two Digital Platforms
Xuewen Yao, Miriam Mikhelson, Megan Micheletti +4
Digital platforms, including online forums and helplines, have emerged as avenues of support for caregivers suffering from postpartum mental health distress. Understanding support…
Dynamic Speech Endpoint Detection with Regression Targets
Dawei Liang, Hang Su, Tarun Singh +5
Interactive voice assistants have been widely used as input interfaces in various scenarios, e.g. on smart homes devices, wearables and on AR devices. Detecting the end of a speech…
Automated detection of foreground speech with wearable sensing in everyday home environments: A transfer learning approach
Dawei Liang, Zifan Xu, Yinuo Chen +3
Acoustic sensing has proved effective as a foundation for numerous applications in health and human behavior analysis. In this work, we focus on the problem of detecting in-person…
Lifelong Adaptive Machine Learning for Sensor-based Human Activity Recognition Using Prototypical Networks
Rebecca Adaimi, Edison Thomaz
Continual learning, also known as lifelong learning, is an emerging research topic that has been attracting increasing interest in the field of machine learning. With human activit…
Transferring Voice Knowledge for Acoustic Event Detection: An Empirical Study
Dawei Liang, Yangyang Shi, Yun Wang +6
Detection of common events and scenes from audio is useful for extracting and understanding human contexts in daily life. Prior studies have shown that leveraging knowledge from a…
MagSurface: Wireless 2D Finger Tracking Leveraging Magnetic Fields
Sarnab Bhattacharya, Keum San Chun, Edison Thomaz
With the ubiquity of touchscreens, touch input modality has become a popular way of interaction. However, current touchscreen technology is limiting in its design as it restricts t…
Improving Prediction of Real-Time Loneliness and Companionship Type Using Geosocial Features of Personal Smartphone Data
Congyu Wu, Amanda N. Barczyk, R. Cameron Craddock +6
Loneliness is a widely affecting mental health symptom and can be mediated by and co-vary with patterns of social exposure. Using momentary survey and smartphone sensing data colle…
Multi-Modal Data Collection for Measuring Health, Behavior, and Living Environment of Large-Scale Participant Cohorts: Conceptual Framework and Findings from Deployments
Congyu Wu, Hagen Fritz, Zoltan Nagy +10
As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented c…
Infant Crying Detection in Real-World Environments
Xuewen Yao, Megan Micheletti, Mckensey Johnson +2
Most existing cry detection models have been tested with data collected in controlled settings. Thus, the extent to which they generalize to noisy and lived environments is unclear…
Quantifying the Chaos Level of Infants' Environment via Unsupervised Learning
Priyanka Khante, Mai Lee Chang, Domingo Martinez +2
Acoustic environments vary dramatically within the home setting. They can be a source of comfort and tranquility or chaos that can lead to less optimal cognitive development in chi…
Audio-Based Activities of Daily Living (ADL) Recognition with Large-Scale Acoustic Embeddings from Online Videos
Dawei Liang, Edison Thomaz
Over the years, activity sensing and recognition has been shown to play a key enabling role in a wide range of applications, from sustainability and human-computer interaction to h…
Leveraging Context to Support Automated Food Recognition in Restaurants
Vinay Bettadapura, Edison Thomaz, Aman Parnami +2
The pervasiveness of mobile cameras has resulted in a dramatic increase in food photos, which are pictures reflecting what people eat. In this paper, we study how taking pictures o…
Predicting Daily Activities From Egocentric Images Using Deep Learning
Daniel Castro, Steven Hickson, Vinay Bettadapura +4
We present a method to analyze images taken from a passive egocentric wearable camera along with the contextual information, such as time and day of week, to learn and predict ever…