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.
| Original language | English |
|---|---|
| Title of host publication | ESANN 2016 - 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning |
| Subtitle of host publication | Bruges, Belgium, April 27-28-29 |
| Publisher | i6doc.com publication |
| Pages | 259-264 |
| Number of pages | 6 |
| ISBN (Electronic) | 9782875870278 |
| Publication status | Published - 2016 |
| Event | 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016 - Bruges, Belgium Duration: 27 Apr 2016 → 29 Apr 2016 |
Conference
| Conference | 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016 |
|---|---|
| Country/Territory | Belgium |
| City | Bruges |
| Period | 27/04/16 → 29/04/16 |
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