Shahriar Zaman

Work place: Dept. of Biomedical Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh



Research Interests: Engineering, Computational Engineering, Bioinformatic Engineering


Shahriar Zaman has fulfilled his BSc degree from Khulna University of Engineering and Technology, Khulna, Bangladesh in Biomedical Engineering.

Author Articles
Classification of FNIRS Using Wigner-ville Distribution and CNN

By Shahriar Zaman Sheikh Md. Rabiul Islam

DOI:, Pub. Date: 8 Oct. 2021

Consumers undergo an intellectual burden when working with technological programs. Mostly in situations of several activities. For instance, while communicating when driving with the navigation device. It is not necessary to divert users from their primary duties in such circumstances. In memory cycles and related workload, the pre-frontal cortex (PFC) has a significant role to play. In this study, we have used data from 10 participants to evaluate the task behaviors in PFC with usable near-infrared spectroscopy (fNIRS), which is a non-invasive imaging modality. In classification, CNN research has been state of the art. This has undermined the need to extract features manually. In order to assess the mental workload, we implemented a time-frequency approach with CNN approach. Rather than traditional CNN network we used ResNet50 pretrained network here. Application of Wigner-Ville Distribution in Functional Imaging is introduced here. The proposed CNN approach achieves a considerable average improvement relative to conventional methods. The results across differences in time window length are benchmarked. Satisfactory result obtained with twenty five second window for which the CNN yields 98% correct classification where traditional CNN achieved 89% accuracy.

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