Automatic vs. clinical assessment of fall risk in older individuals: A proof of concept

Massimo W. Rivolta, Md Aktaruzzaman, Giovanna Rizzo, Claudio L. Lafortuna, Maurizio Ferrarin, Gabriele Bovi, Daniela R. Bonardi, Roberto Sassi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Falling in elderly is a worldwide major problem because it can lead to severe injuries, and even sudden death. Fall risk prediction would provide rapid intervention, as well as reducing the over burden of healthcare systems. Such prediction is currently performed by means of clinical scales. Among them, the Tinetti Scale is one of the better established and mostly used in clinical practice. In this work, we proposed an automatic method to assess the Tinetti scores using a wearable accelerometer. The balance and gait characteristics of 13 elderly subjects have been scored by an expert clinician while performing 8 different motor tasks according to the Tinetti Scale protocol. Two statistical analysis were selected. First, a linear regression study was performed between the Tinetti scores and 8 features (one feature for each task). Second, the generalization quality of the regression model was assessed using a Leave-One Subject-Out approach. The multiple linear regression provided a high correlation between the Tinetti scores and the features proposed (adj. R2 = 0:948; p = 0:003). Moreover, six of the eight features added statistically significantly to the prediction of the scores (p <0:05). When testing the generalization capability of the model, a moderate linear correlation was obtained (R2 = 0:67; p <0:05). The results suggested that the automatic method might be a promising tool to assess the falling risk of older individuals.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6935-6938
Number of pages4
Volume2015-November
ISBN (Print)9781424492718
DOIs
Publication statusPublished - Nov 4 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period8/25/158/29/15

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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