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Bag-of-steps: Predicting Lower-limb Fracture Rehabilitation Length

Lower-limb fracture surgery is one of the major causes for autonomy loss among aged people. For care institutions, tackling with an optimized rehabilitation process is a key factor as it improves both the patients quality of life and the associated costs of the after surgery process. This paper presents bag-of-steps, a new methodology to predict the rehabilitation length and discharge date of a patient using insole force sensors and a predictive model based on the bag-of-words technique. The sensors information is used to characterize the patients gait creating a set of step descriptors. This descriptors are later used to define a vocabulary of steps using a clustering method. The vocabulary is used to describe rehabilitation sessions which are finally entered to a classifier that performs the final rehabilitation estimation. The methodology has been tested using real data from patients that underwent surgery after a lower-limb fracture

Elsevier

Author: Pla, Albert
Mordvanyuk, Natalia
López Ibáñez, Beatriz
Raaben, Marco
Blokhuid, Taco J.
Holstlag, Herman R.
Date: 2018 June 5
Abstract: Lower-limb fracture surgery is one of the major causes for autonomy loss among aged people. For care institutions, tackling with an optimized rehabilitation process is a key factor as it improves both the patients quality of life and the associated costs of the after surgery process. This paper presents bag-of-steps, a new methodology to predict the rehabilitation length and discharge date of a patient using insole force sensors and a predictive model based on the bag-of-words technique. The sensors information is used to characterize the patients gait creating a set of step descriptors. This descriptors are later used to define a vocabulary of steps using a clustering method. The vocabulary is used to describe rehabilitation sessions which are finally entered to a classifier that performs the final rehabilitation estimation. The methodology has been tested using real data from patients that underwent surgery after a lower-limb fracture
Document access: http://hdl.handle.net/2072/319629
Language: eng
Publisher: Elsevier
Rights: Tots els drets reservats
Subject: Medicina -- Informàtica
Medicine -- Data processing
Title: Bag-of-steps: Predicting Lower-limb Fracture Rehabilitation Length
Type: info:eu-repo/semantics/article
Repository: Recercat

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