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Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson's Disease
- Source :
- Sensors, Vol 21, Iss 7680, p 7680 (2021), Sensors, Volume 21, Issue 22, ORCID, Microsoft Academic Graph, DOAJ-Articles, Multidisciplinary Digital Publishing Institute, OPUS FAU-Online-Publikationssystem der Friedrich-Alexander-Universität Erlangen-Nürnberg, PubMed Central, Sensors (Basel, Switzerland)
- Publication Year :
- 2021
-
Abstract
- 0.01). Both gait analysis systems distinguish Parkinson patients from controls. Our results indicate that wearable sensors generate valid gait parameters compared to the motion capture system and can consequently be used for clinically relevant gait recordings in flexible environments.<br />Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson’s Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore, the objective of this study was to compare gait parameters measured by a mobile sensor-based gait analysis system and a motion capture system as the gold standard. Gait parameters of 37 patients were compared between both systems after performing a standardized 5 × 10 m walking test by reliability analysis using intra-class correlation and Bland–Altman plots. Additionally, gait parameters of an age-matched healthy control group (n = 14) were compared to the Parkinson cohort. Gait parameters representing bradykinesia and short steps showed excellent reliability (ICC &gt<br />0.82. In a stridewise synchronization, no differences were observed for gait speed, stride length, stride time, relative stance and swing time (p &gt<br />0.96). Shuffling gait parameters reached ICC &gt<br />0.05). In contrast, heel strike, toe off and toe clearance significantly differed between both systems (p &lt
- Subjects :
- medicine.medical_specialty
Computer science
Parkinson's disease
STRIDE
Wearable computer
Walking
TP1-1185
Biochemistry
Motion capture
Article
Analytical Chemistry
Physical medicine and rehabilitation
Inertial measurement unit
three-dimensional gait analysis
medicine
Humans
ddc:610
Electrical and Electronic Engineering
Gait
Instrumentation
Gait Disorders, Neurologic
Reliability (statistics)
Chemical technology
fungi
spatiotemporal gait parameters
Reproducibility of Results
Parkinson Disease
Gold standard (test)
inertial sensors
Atomic and Molecular Physics, and Optics
machine learning algorithm
wearables
Gait analysis
Parkinson’s disease
Gait Analysis
human activities
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Sensors, Vol 21, Iss 7680, p 7680 (2021), Sensors, Volume 21, Issue 22, ORCID, Microsoft Academic Graph, DOAJ-Articles, Multidisciplinary Digital Publishing Institute, OPUS FAU-Online-Publikationssystem der Friedrich-Alexander-Universität Erlangen-Nürnberg, PubMed Central, Sensors (Basel, Switzerland)
- Accession number :
- edsair.doi.dedup.....e119351b4a6251dbf1f85249868f6b6e