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Fall Detection Analysis Using a Real Fall Dataset

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Book cover International Joint Conference SOCO’18-CISIS’18-ICEUTE’18 (SOCO’18-CISIS’18-ICEUTE’18 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 771))

Abstract

This study focuses on the performance of a fall detection method using data coming from real falls performed by relatively young people and the application of this technique in the case of an elder person. Although the vast majority of studies concerning fall detection place the sensory on the waist, in this research the wearable device must be placed on the wrist because it’s usability. A first pre-processing stage is carried out as stated in [1, 17]; this stage detects the most relevant points to label. This study analyzes the suitability of different models in solving this classification problem: a feed-forward Neural Network and a rule based system generated with the C5.0 algorithm. A discussion about the results and the deployment issues is included.

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Acknowledgment

This research has been funded by the Spanish Ministry of Science and Innovation, under project MINECO-TIN2014-56967-R and MINECO-TIN2017-84804-R.

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Sakarya University, Serdivan, Sakarya, Turkey

    Samad Barri Khojasteh

  2. Computer Science Department, EIMEM, University of Oviedo, Oviedo, Spain

    Samad Barri Khojasteh, José R. Villar & Enrique de la Cal

  3. Control and Automatica Department, EPI, University of Oviedo, Gijón, Spain

    Víctor M. González

  4. Instituto Tecnológico de Castilla y León, Pol. Ind. Villalonquejar, 09001, Burgos, Spain

    Javier Sedano

Authors
  1. Samad Barri Khojasteh
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  2. José R. Villar
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  3. Enrique de la Cal
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  4. Víctor M. González
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  5. Javier Sedano
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Corresponding author

Correspondence to José R. Villar .

Editor information

Editors and Affiliations

  1. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    Manuel Graña

  2. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    José Manuel López-Guede

  3. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    Oier Etxaniz

  4. Department of Civil Engineering, University of Burgos, Burgos, Burgos, Spain

    Álvaro Herrero

  5. University of Salamanca, Salamanca, Salamanca, Spain

    José Antonio Sáez

  6. Department of Industrial Engineering, University of A Coruña, La Coruña, La Coruña, Spain

    Héctor Quintián

  7. University of Salamanca, Salamanca, Salamanca, Spain

    Emilio Corchado

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Khojasteh, S.B., Villar, J.R., de la Cal, E., González, V.M., Sedano, J. (2019). Fall Detection Analysis Using a Real Fall Dataset. In: Graña, M., et al. International Joint Conference SOCO’18-CISIS’18-ICEUTE’18. SOCO’18-CISIS’18-ICEUTE’18 2018. Advances in Intelligent Systems and Computing, vol 771. Springer, Cham. https://doi.org/10.1007/978-3-319-94120-2_32

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