sensors-logo

Journal Browser

Journal Browser

Special Issue "Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: 2 November 2019.

Special Issue Editors

Prof. Dr. Antonio Suppa
E-Mail Website
Guest Editor
Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy
Interests: pathophysiology of motor symptoms; Parkinson's disease (PD); human movement disorders; wireless and wearable technology; inertial measurement units (IMUs); early diagnosis and treatment of PD patients
Prof. Dr. Fernanda Irrera
E-Mail Website
Guest Editor
Department of Information Engineering, Electronics and Telecommunication, Sapienza University of Rome, 00184 Rome, Italy.
Interests: application of electronics and information technology; wearable electronic devices; Parkinson Disease-related symptoms monitoring
Prof. Dr. Joan Cabestany
E-Mail Website
Guest Editor
ISSET Research Group (Integrated Smart Sensors and Health Technologies), Department of Electronic Engineering, Universitat Politcnica de Catalunya, 08034 Barcelona, Spain
Interests: movement diseases; people with gait problems; the application of electronic and communication engineering in Parkinson Disease; identification and measurement of Parkinson Disease-related symptoms and falls

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to this Special Issue of Sensors entitled “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders”. The aim of this Special Issue is to collect the most up-to-date information about the objective evaluation of gait and balance impairment, by means of biosensors (IMUs, etc), in patients with various types of neurological disorders including Parkinson’s disease, dystonia, cerebellar ataxia, multiple sclerosis, stroke, and spasticity. We will accept full-length research articles and reviews focused on this research topic. We hope this initiative will encourage new ideas and produce unparalleled networking opportunities in the field.

Prof. Dr. Antonio Suppa
Prof. Dr. Fernanda Irrera
Prof. Dr. Joan Cabestany
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Wearable sensors
  • IMU
  • Gait
  • Balance
  • Parkinson’s disease
  • Movement disorders
  • Neurology
  • Real time monitoring
  • Longitudinal monitoring
  • Home monitoring

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Turning Analysis during Standardized Test Using On-Shoe Wearable Sensors in Parkinson’s Disease
Sensors 2019, 19(14), 3103; https://doi.org/10.3390/s19143103 - 13 Jul 2019
Abstract
Mobile gait analysis systems using wearable sensors have the potential to analyze and monitor pathological gait in a finer scale than ever before. A closer look at gait in Parkinson’s disease (PD) reveals that turning has its own characteristics and requires its own [...] Read more.
Mobile gait analysis systems using wearable sensors have the potential to analyze and monitor pathological gait in a finer scale than ever before. A closer look at gait in Parkinson’s disease (PD) reveals that turning has its own characteristics and requires its own analysis. The goal of this paper is to present a system with on-shoe wearable sensors in order to analyze the abnormalities of turning in a standardized gait test for PD. We investigated turning abnormalities in a large cohort of 108 PD patients and 42 age-matched controls. We quantified turning through several spatio-temporal parameters. Analysis of turn-derived parameters revealed differences of turn-related gait impairment in relation to different disease stages and motor impairment. Our findings confirm and extend the results from previous studies and show the applicability of our system in turning analysis. Our system can provide insight into the turning in PD and be used as a complement for physicians’ gait assessment and to monitor patients in their daily environment. Full article
Show Figures

Figure 1

Open AccessArticle
Comparing Gait Trials with Greedy Template Matching
Sensors 2019, 19(14), 3089; https://doi.org/10.3390/s19143089 - 12 Jul 2019
Abstract
Gait assessment and quantification have received an increased interest in recent years. Embedded technologies and low-cost sensors can be used for the longitudinal follow-up of various populations (neurological diseases, elderly, etc.). However, the comparison of two gait trials remains a tricky question as [...] Read more.
Gait assessment and quantification have received an increased interest in recent years. Embedded technologies and low-cost sensors can be used for the longitudinal follow-up of various populations (neurological diseases, elderly, etc.). However, the comparison of two gait trials remains a tricky question as standard gait features may prove to be insufficient in some cases. This article describes a new algorithm for comparing two gait trials recorded with inertial measurement units (IMUs). This algorithm uses a library of step templates extracted from one trial and attempts to detect similar steps in the second trial through a greedy template matching approach. The output of our method is a similarity index (SId) comprised between 0 and 1 that reflects the similarity between the patterns observed in both trials. Results on healthy and multiple sclerosis subjects show that this new comparison tool can be used for both inter-individual comparison and longitudinal follow-up. Full article
Show Figures

Figure 1

Back to TopTop