학술논문

Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain
Document Type
Periodical
Source
IEEE Journal of Selected Topics in Signal Processing IEEE J. Sel. Top. Signal Process. Selected Topics in Signal Processing, IEEE Journal of. 10(5):962-974 Aug, 2016
Subject
Signal Processing and Analysis
Pain
Sensors
Smart phones
Mobile communication
Monitoring
Context
Biomedical monitoring
Activity monitoring
affective computing
audio sensing
behavioral signal processing
chronic pain
face expression
mobile health
mobile sensing
modular architecture
self-reporting
smartphones
survey
wearable technology
Language
ISSN
1932-4553
1941-0484
Abstract
Active and passive mobile sensing has garnered much attention in recent years. In this paper, we focus on chronic pain measurement and management as a case application to exemplify the state of the art. We present a consolidated discussion on the leveraging of various sensing modalities along with modular server-side and on-device architectures required for this task. Modalities included are: activity monitoring from accelerometry and location sensing, audio analysis of speech, image processing for facial expressions as well as modern methods for effective patient self-reporting. We review examples that deliver actionable information to clinicians and patients while addressing privacy, usability, and computational constraints. We also discuss open challenges in the higher level inferencing of patient state and effective feedback with potential directions to address them. The methods and challenges presented here are also generalizable and relevant to a broad range of other applications in mobile sensing.