Computing the local dynamic stability using accelerometer data from inertial sensors has recently been proposed as a gait measure which may be able to identify elderly people at fall risk. However, the assumptions supporting this potential were concluded as most studies implement a retrospective fall history observation. The aim of this study was to evaluate the potential of local dynamic stability for fall risk prediction in a cohort of subjects over the age of 60 years using a prospective fall occurrence observation. A total of 131 elderly subjects voluntarily participated in this study. The baseline measurement included gait stability assessment using inertial sensors and clinical examination by Tinetti Balance Assessment Tool. After the baseline measurement, subjects were observed for a period of one year for fall occurrence. Our results demonstrated poor multiple falls predictive ability of trunk local dynamic stability (AUC = 0.673). The predictive ability improved when the local dynamic stability was combined with clinical measures, a combination of trunk medial-lateral local dynamic stability and Tinetti total score being the best predictor (AUC = 0.755). Together, the present findings suggest that the medial-lateral local dynamic stability during gait combined with a clinical score is a potential fall risk assessment measure in the elderly population.

Local dynamic stability during gait for predicting falls in elderly people: A one-year prospective study / Bizovska, Lucia*; Svoboda, Zdenek; Janura, Miroslav; Bisi, Maria Cristina; Vuillerme, Nicolas. - In: PLOS ONE. - ISSN 1932-6203. - ELETTRONICO. - 13:5(2018), pp. e0197091.e0197091-e0197091.11. [10.1371/journal.pone.0197091]

Local dynamic stability during gait for predicting falls in elderly people: A one-year prospective study

Bisi, Maria Cristina;
2018

Abstract

Computing the local dynamic stability using accelerometer data from inertial sensors has recently been proposed as a gait measure which may be able to identify elderly people at fall risk. However, the assumptions supporting this potential were concluded as most studies implement a retrospective fall history observation. The aim of this study was to evaluate the potential of local dynamic stability for fall risk prediction in a cohort of subjects over the age of 60 years using a prospective fall occurrence observation. A total of 131 elderly subjects voluntarily participated in this study. The baseline measurement included gait stability assessment using inertial sensors and clinical examination by Tinetti Balance Assessment Tool. After the baseline measurement, subjects were observed for a period of one year for fall occurrence. Our results demonstrated poor multiple falls predictive ability of trunk local dynamic stability (AUC = 0.673). The predictive ability improved when the local dynamic stability was combined with clinical measures, a combination of trunk medial-lateral local dynamic stability and Tinetti total score being the best predictor (AUC = 0.755). Together, the present findings suggest that the medial-lateral local dynamic stability during gait combined with a clinical score is a potential fall risk assessment measure in the elderly population.
2018
Local dynamic stability during gait for predicting falls in elderly people: A one-year prospective study / Bizovska, Lucia*; Svoboda, Zdenek; Janura, Miroslav; Bisi, Maria Cristina; Vuillerme, Nicolas. - In: PLOS ONE. - ISSN 1932-6203. - ELETTRONICO. - 13:5(2018), pp. e0197091.e0197091-e0197091.11. [10.1371/journal.pone.0197091]
Bizovska, Lucia*; Svoboda, Zdenek; Janura, Miroslav; Bisi, Maria Cristina; Vuillerme, Nicolas
File in questo prodotto:
File Dimensione Formato  
Bizovskaetaal2018.pdf

accesso aperto

Tipo: Versione (PDF) editoriale
Licenza: Creative commons
Dimensione 1.39 MB
Formato Adobe PDF
1.39 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/658067
Citazioni
  • ???jsp.display-item.citation.pmc??? 14
  • Scopus 32
  • ???jsp.display-item.citation.isi??? 31
social impact