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https://doi.org/10.17559/TV-20170603222557

Gait Analysis using Wearable Sensors with Multiple Sclerosis Patients

Aleksandra Jurisic Skevin   ORCID icon orcid.org/0000-0002-7487-8436 ; Faculty of Medical Science, University of Kragujevac, Svetozara Markovica 69, 34000 Kragujevac, Serbia
Nenad Filipovic   ORCID icon orcid.org/0000-0001-9964-5615 ; Faculty of Engineering, University of Kragujevac, SestreJanjica 6, 34000 Kragujevac, Serbia / BioIRC Research and Development Center for Bioengineering, Prvoslava Stojanovica 6, 34000 Kragujevac, Serbia
Nikola Mijailovic ; Faculty of Engineering, University of Kragujevac, SestreJanjica 6, 34000 Kragujevac, Serbia / BioIRC Research and Development Center for Bioengineering, Prvoslava Stojanovica 6, 34000 Kragujevac, Serbia
Ana Divjak ; Faculty of Medical Science, University of Kragujevac, Svetozara Markovica 69, 34000 Kragujevac, Serbia
Jasmin Nurkovic ; Faculty of Medical Science, University of Kragujevac, Svetozara Markovica 69, 34000 Kragujevac, Serbia
Radivoje Radakovic ; BioIRC Research and Development Center for Bioengineering, Prvoslava Stojanovica 6, 34000 Kragujevac, Serbia
Marija Gacic ; BioIRC Research and Development Center for Bioengineering, Prvoslava Stojanovica 6, 34000 Kragujevac, Serbia
Vesna Grbovic ; Faculty of Medical Science, University of Kragujevac, Svetozara Markovica 69, 34000 Kragujevac, Serbia

Puni tekst: engleski, pdf (1 MB) str. 339-342 preuzimanja: 185* citiraj
APA 6th Edition
Jurisic Skevin, A., Filipovic, N., Mijailovic, N., Divjak, A., Nurkovic, J., Radakovic, R., ... Grbovic, V. (2018). Gait Analysis using Wearable Sensors with Multiple Sclerosis Patients. Tehnički vjesnik, 25 (Supplement 2), 339-342. https://doi.org/10.17559/TV-20170603222557
MLA 8th Edition
Jurisic Skevin, Aleksandra, et al. "Gait Analysis using Wearable Sensors with Multiple Sclerosis Patients." Tehnički vjesnik, vol. 25, br. Supplement 2, 2018, str. 339-342. https://doi.org/10.17559/TV-20170603222557. Citirano 20.11.2019.
Chicago 17th Edition
Jurisic Skevin, Aleksandra, Nenad Filipovic, Nikola Mijailovic, Ana Divjak, Jasmin Nurkovic, Radivoje Radakovic, Marija Gacic i Vesna Grbovic. "Gait Analysis using Wearable Sensors with Multiple Sclerosis Patients." Tehnički vjesnik 25, br. Supplement 2 (2018): 339-342. https://doi.org/10.17559/TV-20170603222557
Harvard
Jurisic Skevin, A., et al. (2018). 'Gait Analysis using Wearable Sensors with Multiple Sclerosis Patients', Tehnički vjesnik, 25(Supplement 2), str. 339-342. https://doi.org/10.17559/TV-20170603222557
Vancouver
Jurisic Skevin A, Filipovic N, Mijailovic N, Divjak A, Nurkovic J, Radakovic R i sur. Gait Analysis using Wearable Sensors with Multiple Sclerosis Patients. Tehnički vjesnik [Internet]. 2018 [pristupljeno 20.11.2019.];25(Supplement 2):339-342. https://doi.org/10.17559/TV-20170603222557
IEEE
A. Jurisic Skevin, et al., "Gait Analysis using Wearable Sensors with Multiple Sclerosis Patients", Tehnički vjesnik, vol.25, br. Supplement 2, str. 339-342, 2018. [Online]. https://doi.org/10.17559/TV-20170603222557

Sažetak
In this study we investigated gait measurement with wearable sensor for subjects with and without multiple sclerosis (MS) and evaluation gait function.The gait function was measured with Avatar sensors system in 3 patients with MS and in 3 healthy subjects without MS. The system consists of a main sensor node and three additional fixtures. Each sensor node is wearing three-axial accelerometer and two-axis gyroscope. Cross-correlation analysis with the walk signal was applied.Coefficient values from cross-correlation are determined for all 6 subjects. Then for a new unknown subject the cross-correlation was applied and the mean value cross-correlation for healthy subjects was 0.0477, while in MS subjects this value was 0.0207. A proven validation for this small training system has shown the evidence for different gait analysis for MS and healthy subjects.This small study opens a new avenue for clinical diagnosis of potential MS subjects while wearable sensor can provide an objective framework for assessing gait abnormality. The measured data can provide better understanding on the progression of the disease and response to treatment.

Ključne riječi
cross-correlation coefficient; gait analysis; multiple sclerosis; wearable sensor

Hrčak ID: 205929

URI
https://hrcak.srce.hr/205929

Posjeta: 303 *