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Mobile phone sensors and supervised machine learning to identify alcohol use events in young adults: Implications for just-in-time adaptive interventions

Addictive behaviors, 2018-08, Vol.83, p.42-47

2018

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College from home during COVID-19: A mixed-methods study of heterogeneous experiences

PloS one, 2021-06, Vol.16 (6), p.e0251580-e0251580

2021

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Prediction of Hospital Readmission from Longitudinal Mobile Data Streams

Sensors (Basel, Switzerland), 2021-11, Vol.21 (22), p.7510

2021

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UbiComp 2003: Ubiquitous Computing: 5th International Conference, Seattle, WA, USA, October 12-15, 2003. Proceedings

2003

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iCAP: Interactive Prototyping of Context-Aware Applications

Lecture notes in computer science, 2006, p.254-271

2006

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A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications

Human-computer interaction, 2001-01, Vol.16 (2-4), p.97-166

2001

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Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study

JMIR formative research, 2023-05, Vol.7, p.e39862-e39862

2023

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Performance Evaluation Gaps in a Real-Time Strategy Game Between Human and Artificial Intelligence Players

IEEE access, 2018-01, Vol.6, p.13575-13586

2018

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AWARE: Mobile Context Instrumentation Framework

Frontiers in ICT, 2015-04, Vol.2

2015

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Personal privacy through understanding and action: five pitfalls for designers

Personal and ubiquitous computing, 2004-11, Vol.8 (6), p.440-454

2004

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Toward Building a Safe, Secure, and Easy-to-Use Internet of Things Infrastructure

Computer (Long Beach, Calif.), 2016-04, Vol.49 (4), p.88-91

2016

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Considering context in the design of intelligent systems: Current practices and suggestions for improvement

The Journal of systems and software, 2016-02, Vol.112, p.26-47

2016

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Toward Personalized Activity Recognition Systems With a Semipopulation Approach

IEEE transactions on human-machine systems, 2016-02, Vol.46 (1), p.101-112

2016

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uBPMN: A BPMN extension for modeling ubiquitous business processes

Information and software technology, 2016-06, Vol.74, p.55-68

2016

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Tensions in Representing Behavioral Data in an Electronic Health Record

Computer supported cooperative work, 2021-06, Vol.30 (3), p.393-424

2021

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A Real-Time Mobile Intervention to Reduce Sedentary Behavior Before and After Cancer Surgery: Pilot Randomized Controlled Trial

JMIR perioperative medicine, 2023-01, Vol.6, p.e41425-e41425

2023

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Smooth Gaze: a framework for recovering tasks across devices using eye tracking

Personal and ubiquitous computing, 2018-06, Vol.22 (3), p.489-501

2018

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Estimation of Symptom Severity During Chemotherapy From Passively Sensed Data: Exploratory Study

Journal of medical Internet research, 2017-12, Vol.19 (12), p.e420-e420

2017

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Sensor-based observations of daily living for aging in place

Personal and ubiquitous computing, 2015-01, Vol.19 (1), p.27-43

2015

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Understanding practices and needs of researchers in human state modeling by passive mobile sensing

CCF transactions on pervasive computing and interaction (Online), 2021-12, Vol.3 (4), p.344-366

2021

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Anonymous smartphone data collection: factors influencing the users’ acceptance in mobile crowd sensing

Personal and ubiquitous computing, 2016-02, Vol.20 (1), p.65-82

2016

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Principles of smart home control

Lecture notes in computer science, 2006, p.19-34

2006

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Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data

JMIR mHealth and uHealth, 2019-07, Vol.7 (7), p.e13209-e13209

2019

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Augmenting human senses to improve the user experience in cars: applying augmented reality and haptics approaches to reduce cognitive distances

Multimedia tools and applications, 2016-08, Vol.75 (16), p.9587-9607

2016

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Nightly sleep duration predicts grade point average in the first year of college

Proceedings of the National Academy of Sciences - PNAS, 2023-02, Vol.120 (8), p.e2209123120-e2209123120

2023

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Mobile phone sensors and supervised machine learning to identify alcohol use events in young adults: Implications for just-in-time adaptive interventions

College from home during COVID-19: A mixed-methods study of heterogeneous experiences

Prediction of Hospital Readmission from Longitudinal Mobile Data Streams

UbiComp 2003: Ubiquitous Computing: 5th International Conference, Seattle, WA, USA, October 12-15, 2003. Proceedings

iCAP: Interactive Prototyping of Context-Aware Applications

A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications

Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study

Performance Evaluation Gaps in a Real-Time Strategy Game Between Human and Artificial Intelligence Players

AWARE: Mobile Context Instrumentation Framework

Personal privacy through understanding and action: five pitfalls for designers

Toward Building a Safe, Secure, and Easy-to-Use Internet of Things Infrastructure

Considering context in the design of intelligent systems: Current practices and suggestions for improvement

Toward Personalized Activity Recognition Systems With a Semipopulation Approach

uBPMN: A BPMN extension for modeling ubiquitous business processes

Tensions in Representing Behavioral Data in an Electronic Health Record

A Real-Time Mobile Intervention to Reduce Sedentary Behavior Before and After Cancer Surgery: Pilot Randomized Controlled Trial

Smooth Gaze: a framework for recovering tasks across devices using eye tracking

Estimation of Symptom Severity During Chemotherapy From Passively Sensed Data: Exploratory Study

Sensor-based observations of daily living for aging in place

Understanding practices and needs of researchers in human state modeling by passive mobile sensing

Anonymous smartphone data collection: factors influencing the users’ acceptance in mobile crowd sensing

Principles of smart home control

Identifying Behavioral Phenotypes of Loneliness and Social Isolation with Passive Sensing: Statistical Analysis, Data Mining and Machine Learning of Smartphone and Fitbit Data

Augmenting human senses to improve the user experience in cars: applying augmented reality and haptics approaches to reduce cognitive distances

Nightly sleep duration predicts grade point average in the first year of college

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