Читать книгу Handbook of Intelligent Computing and Optimization for Sustainable Development - Группа авторов - Страница 17

Souvik Das*, Kintada Prudhvi and J. Maiti

Indian Institute of Technology, Kharagpur, India

Abstract

The current study has proposed a mental workload prediction model using neural network and Bernoulli Boltzmann machine. For measuring mental workload, eye movement metrics were considered. The eye metrics were computed from the raw eye movement data, which were recorded using eye tracking device while solving a coding problems. We have found that the Bernoulli Boltzmann machine provides better accuracy in prediction of mental workload from eye metrics. The reason of providing low accuracy by neural network model may be attributed to less data. In future, the sensitivity of the neural network model can be observed by collecting more eye movement data.

Keywords: Mental workload, eye tracking, coding, deep learning model, artificial neural network, Bernoulli Boltzmann machine