Assessment of human motivation through analysis of physiological and emotional signals in Industry 4.0 scenarios

Abstract

Traditional methods to evaluate the human motivation in companies include surveys, statistical techniques and psychological analysis. However, generating the required information using these methods is very costly and time demanding. As a solution, Industry 4.0 paradigm allows integrating Ambient Intelligence systems into the daily industrial operations in order to digitalize those activities. This paper proposes a solution to automatically assess the human motivation in Industry 4.0 scenarios with Ambient Intelligence infrastructure. The estimation is based on both physiological and emotional signals which are acquired (through on-body and environmental sensors) and processed in real-time using web services. The final representation of the human motivation is based on the extended Maslow’s hierarchy of needs. Moreover, an experimental validation is provided, in order to evaluate the performance of the proposed solution.

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Acknowledgements

Borja Bordel has received funding from the Ministry of Education through the FPU program (Grant Number FPU15/03977). Additionally, the research leading to these results has received funding from the Ministry of Economy and Competitiveness through SEMOLA project (TEC2015-68284-R) and from the Autonomous Region of Madrid through MOSI-AGIL-CM project (Grant P2013/ICE-3019, co-funded by EU Structural Funds FSE and FEDER).

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Correspondence to Borja Bordel.

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Bordel, B., Alcarria, R. Assessment of human motivation through analysis of physiological and emotional signals in Industry 4.0 scenarios. J Ambient Intell Human Comput (2017). https://doi.org/10.1007/s12652-017-0664-4

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Keywords

  • Industry 4.0
  • Human motivation
  • Maslow
  • Emotions recognition
  • ECG
  • Ambient intelligence
  • Humanized computing