Combining Continuous Smartphone Native Sensors Data Capture and Unsupervised Data Mining Techniques for Behavioral Changes Detection: A Case Series of the Evidence-Based Behavior (eB2) Study-Reference-Cited by-同舟云学术

Combining Continuous Smartphone Native Sensors Data Capture and Unsupervised Data Mining Techniques for Behavioral Changes Detection: A Case Series of the Evidence-Based Behavior (eB2) Study

Published:2018-12-10 Issue:12 Volume:6 Page:e197
ISSN:2291-5222
Container-title:JMIR mHealth and uHealth
language:en
Short-container-title:JMIR Mhealth Uhealth

Author:

Berrouiguet Sofian^ORCID,Ramírez David^ORCID,Barrigón María Luisa^ORCID,Moreno-Muñoz Pablo^ORCID,Carmona Camacho Rodrigo^ORCID,Baca-García Enrique^ORCID,Artés-Rodríguez Antonio^ORCID

Publisher

JMIR Publications Inc.

Subject

Health Informatics

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1. Mobile Phone-Based Unobtrusive Ecological Momentary Assessment of Day-to-Day Mood: An Explorative Study

2. Smartphone-based home care model improved use of cardiac rehabilitation in postmyocardial infarction patients: results from a randomised controlled trial

3. Supporting the Delivery of Total Knee Replacements Care for Both Patients and Their Clinicians With a Mobile App and Web-Based Tool: Randomized Controlled Trial Protocol

4. Sleep Quality Prediction From Wearable Data Using Deep Learning

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