Capturing the College Experience: A Four-Year Mobile Sensing Study of Mental Health, Resilience and Behavior of College Students during the Pandemic [0.03%]
新冠疫情下美国大学生心理、行为和复原力的四年移动感知研究报告
Subigya Nepal,Wenjun Liu,Arvind Pillai et al.
Subigya Nepal et al.
Understanding the dynamics of mental health among undergraduate students across the college years is of critical importance, particularly during a global pandemic. In our study, we track two cohorts of first-year students at Dartmouth Colle...
Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals [0.03%]
基于移动传感指标检测虚拟交互中社交焦虑个体的社交情境
Zhiyuan Wang,Maria A Larrazabal,Mark Rucker et al.
Zhiyuan Wang et al.
Mobile sensing is a ubiquitous and useful tool to make inferences about individuals' mental health based on physiology and behavior patterns. Along with sensing features directly associated with mental health, it can be valuable to detect d...
X-CHAR: A Concept-based Explainable Complex Human Activity Recognition Model [0.03%]
基于概念的可解释复杂人类活动识别模型
Jeya Vikranth Jeyakumar,Ankur Sarker,Luis Antonio Garcia et al.
Jeya Vikranth Jeyakumar et al.
End-to-end deep learning models are increasingly applied to safety-critical human activity recognition (HAR) applications, e.g., healthcare monitoring and smart home control, to reduce developer burden and increase the performance and robus...
Swapnil Sayan Saha,Sandeep Singh Sandha,Luis Antonio Garcia et al.
Swapnil Sayan Saha et al.
Deep inertial sequence learning has shown promising odometric resolution over model-based approaches for trajectory estimation in GPS-denied environments. However, existing neural inertial dead-reckoning frameworks are not suitable for real...
Auritus: An Open-Source Optimization Toolkit for Training and Development of Human Movement Models and Filters Using Earables [0.03%]
基于耳戴式设备的听觉丰富工具包：用于训练和开发人体运动模型和滤波器的开源优化工具包
Swapnil Sayan Saha,Sandeep Singh Sandha,Siyou Pei et al.
Swapnil Sayan Saha et al.
Smart ear-worn devices (called earables) are being equipped with various onboard sensors and algorithms, transforming earphones from simple audio transducers to multi-modal interfaces making rich inferences about human motion and vital sign...
SmokeMon: Unobtrusive Extraction of Smoking Topography Using Wearable Energy-Efficient Thermal [0.03%]
烟雾蒙：利用节能型热能可穿戴设备不引人注意地提取吸烟行为特征
Rawan Alharbi,Soroush Shahi,Stefany Cruz et al.
Rawan Alharbi et al.
Smoking is the leading cause of preventable death worldwide. Cigarette smoke includes thousands of chemicals that are harmful and cause tobacco-related diseases. To date, the causality between human exposure to specific compounds and the ha...
Real-time Context-Aware Multimodal Network for Activity and Activity-Stage Recognition from Team Communication in Dynamic Clinical Settings [0.03%]
基于团队沟通的动态临床环境下的实时情境感知多模态网络用于活动及活动阶段识别
Chenyang Gao,Ivan Marsic,Aleksandra Sarcevic et al.
Chenyang Gao et al.
In clinical settings, most automatic recognition systems use visual or sensory data to recognize activities. These systems cannot recognize activities that rely on verbal assessment, lack visual cues, or do not use medical devices. We exami...
Psychophysiological Arousal in Young Children Who Stutter: An Interpretable AI Approach [0.03%]
解读式人工智能方法在儿童口吃心理生理唤醒中的应用
Harshit Sharma,Y I Xiao,Victoria Tumanova et al.
Harshit Sharma et al.
The presented first-of-its-kind study effectively identifies and visualizes the second-by-second pattern differences in the physiological arousal of preschool-age children who do stutter (CWS) and who do not stutter (CWNS) while speaking pe...
mRisk: Continuous Risk Estimation for Smoking Lapse from Noisy Sensor Data with Incomplete and Positive-Only Labels [0.03%]
基于噪声传感器数据的不完整和仅正面标签的连续风险估计：预防吸烟复发的风险引擎mPidRisk
Md Azim Ullah,Soujanya Chatterjee,Christopher P Fagundes et al.
Md Azim Ullah et al.
Passive detection of risk factors (that may influence unhealthy or adverse behaviors) via wearable and mobile sensors has created new opportunities to improve the effectiveness of behavioral interventions. A key goal is to find opportune mo...
First-Gen Lens: Assessing Mental Health of First-Generation Students across Their First Year at College Using Mobile Sensing [0.03%]
第一代镜头：利用移动感应技术评估大学一年级中第一代学生的心理健康状况
Weichen Wang,Subigya Nepal,Jeremy F Huckins et al.
Weichen Wang et al.
The transition from high school to college is a taxing time for young adults. New students arriving on campus navigate a myriad of challenges centered around adapting to new living situations, financial needs, academic pressures and social ...