Artículo
On the feature extraction process in machine learning. An experimental study about guided versus non-guided process in falling detection systems
Autor/es | Escobar Linero, Elena
Luna Perejón, Francisco Muñoz Saavedra, Luis Sevillano Ramos, José Luis Domínguez Morales, Manuel Jesús |
Departamento | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores |
Fecha de publicación | 2022 |
Fecha de depósito | 2022-11-23 |
Publicado en |
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Premios | Premio Mensual Publicación Científica Destacada de la US. Escuela Técnica Superior de Ingeniería Informática |
Resumen | Falls are current events that can lead to severe injuries and even accidental deaths among the population, especially the elderly. Since them usually live alone and their contact with other people has decreased since ... Falls are current events that can lead to severe injuries and even accidental deaths among the population, especially the elderly. Since them usually live alone and their contact with other people has decreased since pandemic, recent years studies have focused on automatic fall detection systems with wearable devices using machine learning algorithms. Overall, and according to other works, these systems can be classified as non-guided, if the machine learning model directly uses raw data without feature extraction, or as guided systems, if a previous step of feature extraction is needed to reduce complexity of the algorithm. However, no recommendations are made in the literature on which system could be more advantageous for detecting fall events. Therefore, in this work, a detailed comparison between both types of systems is carried out, using the same process for different machine learning models in order to obtain an accurate classification of activities of daily living, falling risks, and falls. This process includes the optimization of models’ hyperparameters to obtain the best classifiers, followed by an assessment using common evaluation metrics, confusion matrices, ROC curves and execution times. Results show a better classification of models’ three classes for the non-guided models. However, the guided models show more stable metrics and lower computational load. |
Agencias financiadoras | Junta de Andalucía |
Identificador del proyecto | DAFNE US-1381619
MSF-PHIA US-1263715 |
Cita | Escobar Linero, E., Luna Perejón, F., Muñoz Saavedra, L., Sevillano Ramos, J.L. y Domínguez Morales, M.J. (2022). On the feature extraction process in machine learning. An experimental study about guided versus non-guided process in falling detection systems. Engineering Applications of Artificial Intelligence, 114 (September 2022, art.nº105170), 1-22. https://doi.org/10.1016/j.engappai.2022.105170. |
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