Bag-of-steps: Predicting lower-limb fracture rehabilitation length

Albert Pla; Beatriz López; Cristofor Nogueira; Natalia Mordvaniuk; Taco J. Blokhuis; Herman R. Holtslag

Bag-of-steps: Predicting lower-limb fracture rehabilitation length

Albert Pla, Beatriz López, Cristofor Nogueira, Natalia Mordvaniuk, Taco J. Blokhuis, Herman R. Holtslag

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

1 Citation (Scopus)

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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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es2016-39Final published version, 1.49 MB

https://www.elen.ucl.ac.be/esann/proceedings/papers.php?ann=2016

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Pla, A., López, B., Nogueira, C., Mordvaniuk, N., Blokhuis, T. J., & Holtslag, H. R. (2016). Bag-of-steps: Predicting lower-limb fracture rehabilitation length. In ESANN 2016 - 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: Bruges, Belgium, April 27-28-29 (pp. 259-264). Article ES2016-39 i6doc.com publication. https://www.elen.ucl.ac.be/esann/proceedings/papers.php?ann=2016

@inproceedings{103305efc35745f6a076a711d87e9b9b,

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",

pages = "259--264",

booktitle = "ESANN 2016 - 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning",

publisher = "i6doc.com publication",

note = "24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016 ; Conference date: 27-04-2016 Through 29-04-2016",

}

Pla, A, López, B, Nogueira, C, Mordvaniuk, N, Blokhuis, TJ & Holtslag, HR 2016, Bag-of-steps: Predicting lower-limb fracture rehabilitation length. in ESANN 2016 - 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: Bruges, Belgium, April 27-28-29., ES2016-39, i6doc.com publication, pp. 259-264, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016, Bruges, Belgium, 27/04/16. <https://www.elen.ucl.ac.be/esann/proceedings/papers.php?ann=2016>

Bag-of-steps: Predicting lower-limb fracture rehabilitation length. / Pla, Albert; López, Beatriz; Nogueira, Cristofor et al.
ESANN 2016 - 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning: Bruges, Belgium, April 27-28-29. i6doc.com publication, 2016. p. 259-264 ES2016-39.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic

TY - GEN

T1 - Bag-of-steps

T2 - 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2016

AU - Pla, Albert

AU - López, Beatriz

AU - Nogueira, Cristofor

AU - Mordvaniuk, Natalia

AU - Blokhuis, Taco J.

AU - Holtslag, Herman R.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

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M3 - Conference contribution

AN - SCOPUS:84994175697

SP - 259

EP - 264

BT - ESANN 2016 - 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

PB - i6doc.com publication

Y2 - 27 April 2016 through 29 April 2016

ER -

Bag-of-steps: Predicting lower-limb fracture rehabilitation length

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