@InProceedings{6952414,
  author = {M. Martins and C. Santos and L. Costa and A. Frizera},
  booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
  title = {Gait feature selection in walker-assisted gait using NSGA-II and SVM hybrid algorithm},
  year = {2014},
  pages = {1173-1177},
  abstract = {Nowadays, walkers are prescribed based on subjective standards that lead to incorrect indication of such devices to patients. This leads to the increase of dissatisfaction and occurrence of discomfort and fall events. Therefore, it is necessary to objectively evaluate the effects that walker can have on the gait patterns of its users, comparatively to non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information and this study addresses this problem by selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. In order to do this, it is proposed an approach that combines multi-objective genetic and support vector machine algorithms to discriminate differences. Results with healthy subjects have shown that the main differences are characterized by balance and joints excursion. Thus, one can conclude that this technique is an efficient feature selection approach.},
  keywords = {gait analysis;genetic algorithms;medical computing;patient rehabilitation;support vector machines;gait feature selection;walker-assisted gait;NSGA-II;SVM hybrid algorithm;subjective standards;discomfort occurrence;fall events;gait patterns;gait analysis;spatiotemporal parameters;kinematics parameters;redundant information;multiobjective genetic algorithms;support vector machine algorithms;balance excursion;joints excursion;feature selection approach;Noise measurement;Sociology;Support vector machines;Hip;Correlation;Evolutionary algorithms;Walker-assisted gait;SVM;NSGA-II;Rehabilitation},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569924111.pdf},
}

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This leads to the increase of dissatisfaction and occurrence of discomfort and fall events. Therefore, it is necessary to objectively evaluate the effects that walker can have on the gait patterns of its users, comparatively to non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information and this study addresses this problem by selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. In order to do this, it is proposed an approach that combines multi-objective genetic and support vector machine algorithms to discriminate differences. Results with healthy subjects have shown that the main differences are characterized by balance and joints excursion. 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Frizera},\n booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},\n title = {Gait feature selection in walker-assisted gait using NSGA-II and SVM hybrid algorithm},\n year = {2014},\n pages = {1173-1177},\n abstract = {Nowadays, walkers are prescribed based on subjective standards that lead to incorrect indication of such devices to patients. This leads to the increase of dissatisfaction and occurrence of discomfort and fall events. Therefore, it is necessary to objectively evaluate the effects that walker can have on the gait patterns of its users, comparatively to non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information and this study addresses this problem by selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. In order to do this, it is proposed an approach that combines multi-objective genetic and support vector machine algorithms to discriminate differences. Results with healthy subjects have shown that the main differences are characterized by balance and joints excursion. 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