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Findings About Selecting Body Parts to Analyze Human Activities Through Skeletal Tracking Joint Oriented Devices

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Ubiquitous Computing and Ambient Intelligence (UCAmI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10069))

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Abstract

Analyzing activities (either static postures or movements) made by a user is a complex process that can be done through a wide range of approaches. One part of these existing approaches support doing the recognition focusing their analysis on specific body parts. In fact, in previous publications a method was introduced for activity recognition (Body-Angles Algorithm) capable of analysing only using a single sample of those activitites and allowing the selection for each activity which are the relevant joints. But being able to analyse the body of the user selecting only a subset of the same, has both advantages and disadvantages. Therefore throughout this article we will expose those disadvantages, the applied solution to mitigate them and the results of an evaluation destined to clear which body parts make it easier to obtain high accuracy rates in recognition. Through this work we aim to give the scientific community lessons learned about the usage of different body areas in the analysis of activity recognition.

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Notes

  1. 1.

    The activities identified with [D] are done with the right side of the body. These are the asymmetric activities, those that can be performed with either the left [I] or right side of the body, and therefore two versions must be recorded in the system, one for each half of the body.

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Acknowledgments

This work was conducted in the context of UBIHEALTH project under International Research Staff Exchange Schema (MC-IRSES 316337) and the coordinated project grant TIN2013-47152-C3-1-R (FRASE), funded by the Spanish Ministerio de Ciencia e Innovación.

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Authors and Affiliations

  1. Escuela Superior de Informática de Ciudad Real, Laboratorio MamI, Universidad de Castilla-La Mancha, Paseo de la Universidad 4, 13071, Ciudad Real, Spain

    Carlos Gutiérrez López de la Franca, Ramón Hervás, Esperanza Johnson & José Bravo

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  1. Carlos Gutiérrez López de la Franca
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  2. Ramón Hervás
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  3. Esperanza Johnson
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  4. José Bravo
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Corresponding author

Correspondence to Carlos Gutiérrez López de la Franca .

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Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Carmelo R. García

  2. Departamento de Estadistica, Universidad La Laguna, La Laguna, Spain

    Pino Caballero-Gil

  3. Florida State University, Tallahassee, Florida, USA

    Mike Burmester

  4. University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Alexis Quesada-Arencibia

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Gutiérrez López de la Franca, C., Hervás, R., Johnson, E., Bravo, J. (2016). Findings About Selecting Body Parts to Analyze Human Activities Through Skeletal Tracking Joint Oriented Devices. In: García, C., Caballero-Gil, P., Burmester, M., Quesada-Arencibia, A. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2016. Lecture Notes in Computer Science(), vol 10069. Springer, Cham. https://doi.org/10.1007/978-3-319-48746-5_55

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  • DOI: https://doi.org/10.1007/978-3-319-48746-5_55

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