Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain. Academic Article uri icon

Overview

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.

publication date

  • May 9, 2016

Identity

PubMed Central ID

  • PMC6430587

Scopus Document Identifier

  • 84982746742

Digital Object Identifier (DOI)

  • 10.1109/JSTSP.2016.2565381

PubMed ID

  • 30906495

Additional Document Info

volume

  • 10

issue

  • 5