Ítem
|
Pla, Albert
Mordvanyuk, Natalia López Ibáñez, Beatriz Raaben, Marco Blokhuid, Taco J. Holstlag, Herman R. |
|
| 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 | |
| http://hdl.handle.net/2072/285890 | |
| eng | |
| Elsevier | |
| Tots els drets reservats | |
|
Medicina -- Informàtica
Medicine -- Data processing |
|
| Bag-of-steps: Predicting Lower-limb Fracture Rehabilitation Length | |
| info:eu-repo/semantics/article | |
| Recercat |
