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Gait quality assessment in survivors from severe traumatic brain injury: An instrumented approach based on inertial sensors

Articolo
Data di Pubblicazione:
2019
Citazione:
(2019). Gait quality assessment in survivors from severe traumatic brain injury: An instrumented approach based on inertial sensors [journal article - articolo]. In SENSORS. Retrieved from https://hdl.handle.net/10446/263393
Abstract:
Despite existing evidence that gait disorders are a common consequence of severe traumatic brain injury (sTBI), the literature describing gait instability in sTBI survivors is scant. Thus, the present study aims at quantifying gait patterns in sTBI through wearable inertial sensors and investigating the association of sensor-based gait quality indices with the scores of commonly administered clinical scales. Twenty healthy adults (control group, CG) and 20 people who suffered from a sTBI were recruited. The Berg balance scale, community balance and mobility scale, and dynamic gait index (DGI) were administered to sTBI participants, who were further divided into two subgroups, severe and very severe, according to their score in the DGI. Participants performed the 10 m walk, the Figure-of-8 walk, and the Fukuda stepping tests, while wearing five inertial sensors. Significant differences were found among the three groups, discriminating not only between CG and sTBI, but also for walking ability levels. Several indices displayed a significant correlation with clinical scales scores, especially in the 10 m walking and Figure-of-8 walk tests. Results show that the use of wearable sensors allows the obtainment of quantitative information about a patient’s gait disorders and discrimination between different levels of walking abilities, supporting the rehabilitative staff in designing tailored therapeutic interventions.
Tipologia CRIS:
1.1.01 Articoli/Saggi in rivista - Journal Articles/Essays
Elenco autori:
Belluscio, V.; Bergamini, Elena; Tramontano, M.; Bustos, A. O.; Allevi, G.; Formisano, R.; Vannozzi, G.; Buzzi, M. G.
Autori di Ateneo:
BERGAMINI Elena
Link alla scheda completa:
https://aisberg.unibg.it/handle/10446/263393
Link al Full Text:
https://aisberg.unibg.it/retrieve/handle/10446/263393/657317/2019_Belluscio%20Sensors_TBI.pdf
Pubblicato in:
SENSORS
Journal
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Settore ING-INF/06 - Bioingegneria Elettronica e Informatica
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