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.