@inproceedings{9efe9b64892f4d68931a5ee44d779f25,
title = "Bag-of-steps: Predicting lower-limb fracture rehabilitation length",
abstract = "This paper presents bag-of-steps, a new methodology to predict the rehabilitation length of a patient by monitoring the weight he is bearing in his injured leg and using a predictive model based on the bag-of-words technique. A force sensor is used to monitor and characterize the patient's gait, obtaining a set of step descriptors. These are later used to define a vocabulary of steps that can be used to describe rehabilitation sessions. Sessions are finally fed to a support vector machine classifier that performs the final rehabilitation estimation.",
author = "Albert Pla and Beatriz L{\'o}pez and Cristofor Nogueira and Natalia Mordvaniuk and Blokhuis, {Taco J.} and Holtslag, {Herman R.}",
year = "2016",
language = "English",
series = "ESANN 2016 - 24th European Symposium on Artificial Neural Networks",
publisher = "i6doc.com publication",
pages = "259--264",
booktitle = "ESANN 2016 - 24th European Symposium on Artificial Neural Networks",
note = "24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016 ; Conference date: 27-04-2016 Through 29-04-2016",
}