Next Article in Journal
Planar Body-Mounted Sensors for Electromagnetic Tracking
Next Article in Special Issue
A Quality Control Methodology for Heterogeneous Vehicular Data Streams
Previous Article in Journal
Electrochemical Detection of Glucose Molecules Using Laser-Induced Graphene Sensors: A Review
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sensors
Volume 21
Issue 8
10.3390/s21082821
sensors-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Smart-Insole Dataset: Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson’s Patients

by
Chariklia Chatzaki
1,*,
Vasileios Skaramagkas
2,
Nikolaos Tachos
3,4,
Georgios Christodoulakis
2,
Evangelia Maniadi
1,
Zinovia Kefalopoulou
5,
Dimitrios I. Fotiadis
3,4 and
Manolis Tsiknakis
1,2
1
Biomedical Informatics and eHealth Laboratory, Department of Electrical and Computer Engineering, Hellenic Mediterranean University, Estavromenos, 71004 Heraklion, Greece
2
Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology—Hellas, Vassilika Vouton, 71110 Heraklion, Greece
3
Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece
4
Department of Biomedical Research, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology—Hellas, 45110 Ioannina, Greece
5
Neurology Department, Patras University Hospital, 26404 Patra, Greece
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(8), 2821; https://doi.org/10.3390/s21082821
Submission received: 16 February 2021 / Revised: 30 March 2021 / Accepted: 14 April 2021 / Published: 16 April 2021
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Greece)
Browse Figures
Versions Notes

Abstract

Gait analysis is crucial for the detection and management of various neurological and musculoskeletal disorders. The identification of gait events is valuable for enhancing gait analysis, developing accurate monitoring systems, and evaluating treatments for pathological gait. The aim of this work is to introduce the Smart-Insole Dataset to be used for the development and evaluation of computational methods focusing on gait analysis. Towards this objective, temporal and spatial characteristics of gait have been estimated as the first insight of pathology. The Smart-Insole dataset includes data derived from pressure sensor insoles, while 29 participants (healthy adults, elderly, Parkinson’s disease patients) performed two different sets of tests: The Walk Straight and Turn test, and a modified version of the Timed Up and Go test. A neurologist specialized in movement disorders evaluated the performance of the participants by rating four items of the MDS-Unified Parkinson’s Disease Rating Scale. The annotation of the dataset was performed by a team of experienced computer scientists, manually and using a gait event detection algorithm. The results evidence the discrimination between the different groups, and the verification of established assumptions regarding gait characteristics of the elderly and patients suffering from Parkinson’s disease.
Keywords: gait analysis; Parkinson’s disease; insoles; pressure sensors; dataset gait analysis; Parkinson’s disease; insoles; pressure sensors; dataset

Share and Cite

MDPI and ACS Style

Chatzaki, C.; Skaramagkas, V.; Tachos, N.; Christodoulakis, G.; Maniadi, E.; Kefalopoulou, Z.; Fotiadis, D.I.; Tsiknakis, M. The Smart-Insole Dataset: Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson’s Patients. Sensors 2021, 21, 2821. https://doi.org/10.3390/s21082821

AMA Style

Chatzaki C, Skaramagkas V, Tachos N, Christodoulakis G, Maniadi E, Kefalopoulou Z, Fotiadis DI, Tsiknakis M. The Smart-Insole Dataset: Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson’s Patients. Sensors. 2021; 21(8):2821. https://doi.org/10.3390/s21082821

Chicago/Turabian Style

Chatzaki, Chariklia, Vasileios Skaramagkas, Nikolaos Tachos, Georgios Christodoulakis, Evangelia Maniadi, Zinovia Kefalopoulou, Dimitrios I. Fotiadis, and Manolis Tsiknakis. 2021. "The Smart-Insole Dataset: Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson’s Patients" Sensors 21, no. 8: 2821. https://doi.org/10.3390/s21082821

APA Style

Chatzaki, C., Skaramagkas, V., Tachos, N., Christodoulakis, G., Maniadi, E., Kefalopoulou, Z., Fotiadis, D. I., & Tsiknakis, M. (2021). The Smart-Insole Dataset: Gait Analysis Using Wearable Sensors with a Focus on Elderly and Parkinson’s Patients. Sensors, 21(8), 2821. https://doi.org/10.3390/s21082821

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop