A Survey on Freezing of Gait Detection and Prediction in Parkinson’s Disease

Lourdes Martínez-Villaseñor, Hiram Ponce, Luis Miralles-Pechuán

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Most of Parkinson’s disease (PD) patients present a set of motor and non-motor symptoms and behaviors that vary during the day and from day-to-day. In particular, freezing of gait (FOG) impairs their quality of life and increases the risk of falling. Smart technology like mobile communication and wearable sensors can be used for detection and prediction of FOG, increasing the understanding of the complex PD. There are surveys reviewing works on Parkinson and/or technologies used to manage this disease. In this review, we summarize and analyze works addressing FOG detection and prediction based on wearable sensors, vision and other devices. We aim to identify trends, challenges and opportunities in the development of FOG detection and prediction systems.

Original languageEnglish
Title of host publicationAdvances in Soft Computing - 19th Mexican International Conference on Artificial Intelligence, MICAI 2020, Proceedings
EditorsLourdes Martínez-Villaseñor, Hiram Ponce, Oscar Herrera-Alcántara, Félix A. Castro-Espinoza
PublisherSpringer Science and Business Media Deutschland GmbH
Pages169-181
Number of pages13
ISBN (Print)9783030608835
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event19th Mexican International Conference on Artificial Intelligence, MICAI 2020 - Mexico City, Mexico
Duration: 12 Oct 202017 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12468 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th Mexican International Conference on Artificial Intelligence, MICAI 2020
Country/TerritoryMexico
CityMexico City
Period12/10/2017/10/20

Keywords

  • FOG detection
  • FOG prediction
  • Freezing of gait
  • Machine learning
  • Parkinson

Fingerprint

Dive into the research topics of 'A Survey on Freezing of Gait Detection and Prediction in Parkinson’s Disease'. Together they form a unique fingerprint.

Cite this