On the Assessment of Gray Code Kernels for Motion Characterization in People with Multiple Sclerosis: A Preliminary Study

  • Matteo Moro
  • , Maria Cellerino
  • , Matilde Inglese
  • , Maura Casadio
  • , Francesca Odone
  • , Nicoletta Noceti

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

Abstract

Motor deficits in the lower limbs are common in people with multiple sclerosis (MS), impacting mobility and quality of life. Objective and quantitative metrics are crucial for effective identification and monitoring of motor deficits. Recent advancements in computer vision and human pose estimators allow for automatic extraction of movement information from video data, offering potential insights into human motion patterns. This exploratory study investigates the use of Gray-Code Kernels (GCKs) in characterizing gait patterns in individuals with advanced-stage MS compared to age- and sex-matched unimpaired controls. The preliminary results obtained demonstrate the promising potential of combining GCKs and pose estimators in characterizing gait patterns, warranting further investigation in this area.

Original languageEnglish
Title of host publicationApplications in Electronics Pervading Industry, Environment and Society - APPLEPIES 2023
EditorsFrancesco Bellotti, Miltos D. Grammatikakis, Ali Mansour, Massimo Ruo Roch, Ralf Seepold, Agusti Solanas, Riccardo Berta
PublisherSpringer Science and Business Media Deutschland GmbH
Pages241-247
Number of pages7
ISBN (Print)9783031481208
DOIs
StatePublished - 2024
Externally publishedYes
EventInternational Conference on Applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2023 - Genoa, Italy
Duration: 28 Sep 202329 Sep 2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1110 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2023
Country/TerritoryItaly
CityGenoa
Period28/09/2329/09/23

Keywords

  • Gray-code kernels
  • Human motion analysis
  • Human pose estimation
  • Multiple sclerosis

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