Accurate gait analysis in post-stroke patients using a single inertial measurement unit

Federico Parisi, Gianluigi Ferrari, Alessio Baricich, Marco D'Innocenzo, Carlo Cisari, Alessandro Mauro

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

Abstract

Improving independent mobility in post-stroke patients is one of the main goals of most rehabilitation strategies. While quantitative gait assessment is crucial to provide a meaningful feedback on the recovery progress, the irregularity of hemiparetic walking prevents the use of classical Inertial Measurement Unit (IMU)-based gait analysis algorithms. In this paper, we propose a novel low-cost system, which relies on a single wearable IMU attached to the lower trunk, to estimate spatio-temporal gait parameters of both hemiparetic and healthy subjects. A new procedure for temporal features' computation and two modified versions of well-known step length (i.e., spatial features) estimators are derived. In both cases, we exploit dynamic calibration constants, related to the power of an individual gait pattern, to deal with the typical asymmetry and inter-subject variability of hemiparetic gait. The spatio-temporal features estimated with the proposed methods are compared with ground-truth parameters extracted by an optoelectronic system. The obtained results show very high correlations between estimated and reference values.

Original languageEnglish
Title of host publicationBSN 2016 - 13th Annual Body Sensor Networks Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages335-340
Number of pages6
ISBN (Electronic)9781509030873
DOIs
Publication statusPublished - 18 Jul 2016
Event13th Annual Body Sensor Networks Conference, BSN 2016 - San Francisco, United States
Duration: 14 Jun 201617 Jun 2016

Publication series

NameBSN 2016 - 13th Annual Body Sensor Networks Conference

Conference

Conference13th Annual Body Sensor Networks Conference, BSN 2016
Country/TerritoryUnited States
CitySan Francisco
Period14/06/1617/06/16

Fingerprint

Dive into the research topics of 'Accurate gait analysis in post-stroke patients using a single inertial measurement unit'. Together they form a unique fingerprint.

Cite this