Name
Title | ||
|---|---|---|
Bag-of-steps: Predicting lower-limb fracture rehabilitation length by weight loading analysis. |
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. (C) 2017 Elsevier B.V. All rights reserved |
Year | Venue | Field |
|---|---|---|
2017 | Neurocomputing | Bag-of-words model,Rehabilitation,Hip fracture,Gait,Support vector machine,Gait analysis,Artificial intelligence,Cluster analysis,Vocabulary,Mathematics,Machine learning |
DocType | Volume | Citations |
Journal | 268 | 0 |
PageRank | References | Authors |
0.34 | 10 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Albert Pla | 1 | 73 | 10.08 |
| Natalia Mordvanyuk | 2 | 0 | 1.69 |
| Beatriz López | 3 | 7 | 4.06 |
| Marco Raaben | 4 | 0 | 0.34 |
| Taco J. Blokhuis | 5 | 0 | 1.69 |
| Herman R. Holstlag | 6 | 0 | 0.34 |