Document - A learning system for automatic Berg Balance Scale score estimation

2017

Journal article Open Access

A learning system for automatic Berg Balance Scale score estimation

Bacciu D., Chessa S., Gallicchio C., Micheli A., Pedrelli L., Ferro E., Fortunati L., La Rosa D., Palumbo F., Vozzi F., Parodi O.

Electrical and Electronic Engineering Reservoir computing Artificial Intelligence Berg Balance Scale Balance assessment Echo State Network Learning with temporal data Control and Systems Engineering

The objective of this work is the development of a learning system for the automatic assessment of balance abilities in elderly people. The system is based on estimating the Berg Balance Scale (BBS) score from the stream of sensor data gathered by a Wii Balance Board. The scientific challenge tackled by our investigation is to assess the feasibility of exploiting the richness of the temporal signals gathered by the balance board for inferring the complete BBS score based on data from a single BBS exercise. The relation between the data collected by the balance board and the BBS score is inferred by neural networks for temporal data, modeled in particular as Echo State Networks within the Reservoir Computing (RC) paradigm, as a result of a comprehensive comparison among different learning models. The proposed system results to be able to estimate the complete BBS score directly from temporal data on exercise #10 of the BBS test, with ?10 s of duration. Experimental results on real-world data show an absolute error below 4 BBS score points (i.e. below the 7% of the whole BBS range), resulting in a favorable trade-off between predictive performance and user's required time with respect to previous works in literature. Results achieved by RC models compare well also with respect to different related learning models. Overall, the proposed system puts forward as an effective tool for an accurate automated assessment of balance abilities in the elderly and it is characterized by being unobtrusive, easy to use and suitable for autonomous usage.

Source: Engineering applications of artificial intelligence 66 (2017): 60–74. doi:10.1016/j.engappai.2017.08.018

Publisher: Pineridge,, Swansea , Regno Unito

Metrics

Back to previous page

Cite as

BibTeX entry

@article{oai:it.cnr:prodotti:376191,
	title = {A learning system for automatic Berg Balance Scale score estimation},
	author = {Bacciu D. and Chessa S. and Gallicchio C. and Micheli A. and Pedrelli L. and Ferro E. and Fortunati L. and La Rosa D. and Palumbo F. and Vozzi F. and Parodi O.},
	publisher = {Pineridge,, Swansea , Regno Unito},
	doi = {10.1016/j.engappai.2017.08.018},
	journal = {Engineering applications of artificial intelligence},
	volume = {66},
	pages = {60–74},
	year = {2017}
}