Books Published by ACSLab Members


  • 2017

      M. Lutfar Rahman, M. Shamim Kaiser, M. Arifur Rahman, and Md. Alamgir Hossain COMPUTER FUNDAMENTALS and ICT. , DIU Press, May 2017

      M. Lutfar Rahman, M. Shamim Kaiser, M. Arifur Rahman, and Md. Alamgir Hossain

  • 2013
    • Towards Reduced EEG Based Brain-Computer Interfacing for Mobile Robot Navigation

      Rapid development in highly parallel neurophysiological recording techniques along with sophisticated signal processing tools allow direct communication with neuronal processes at different levels. One important level from the point of view of Rehabilitation Engineering & Assistive Technology is to use the Electroencephalogram (EEG) signals to interface with assistive devices. This type of brain-computer interface (BCI) aims to reestablish the broken loop of the persons with motor dysfunction(s). However, with the growing availability of of instruments and processes for implementation, the BCI is also getting more complex. In this work, the authors present a model for reduced complexity BCI based on EEG signals through a few simple processes for automated navigation and control of robotic device. It is demonstrated that not only with few number of electrodes, but also using simple features like evoked responses caused by Saccadic eye movement can be used in building robust BCI for rehabilitation which may revolutionize the development of assitive devices for the disabled.

      M. Mahmud, A. Hussain

  • 2012
    • Decoding Network Activity from LFPs: A Computational Approach

      Cognition is one of the main capabilities of mammal brain and understanding it thoroughly requires decoding brain’s information processing pathways which are composed of networks formed by complex connectivity between neurons. Mostly, scientists rely on local field potentials (LFPs) averaged over a number of trials to study the effect of stimuli on brain regions under investigation. However, this may not be the right approach when trying to understand the exact neuronal network underlying the neuronal signals. As the LFPs are lumped activity of populations of neurons, their shapes provide fingerprints of the underlying networks. The method presented in this paper extracts shape information of the LFPs, calculate the corresponding current source density (CSD) from the LFPs and decode the underlying network activity. Through simulated LFPs it has been found that differences in LFP shapes lead to different network activity.

      M. Mahmud, D. Travalin, A. Hussain

    • Single LFP Sorting for High-resolution Brain-chip Interfacing

      Understanding cognition has fascinated many neuroscientists and made them put their efforts in deciphering the brain’s information processing capabilities for cognition. Rodents perceive the environment through whisking during which tactile information is processed at the barrel columns of the somatosensory cortex (S1). The intra– and trans–columnar microcircuits in the barrel cortex segregate and integrate information during activation of this pathway. Local Field Potentials (LFPs) recorded from these barrel columns provide information about the microcircuits and the shape of the LFPs provide the fingerprint of the underlying neuronal network. Through a contour based sorting method, we could sort neuronal evoked LFPs recorded using high–resolution Electrolyte–Oxide–Semiconductor Field Effect Transistor (EOSFET) based neuronal probes. We also report that the latencies and amplitudes of the individual LFPs’ shapes vary among the different clusters generated by the method. The shape specific information of the single LFPs thus can be used in commenting on the underlying neuronal network generating those signals.

      M. Mahmud, D. Travalin, S. Girardi, M. Maschietto, F. Felderer, S. Vassanelli

    • CyberRat Probes: High-Resolution Biohybrid Devices for Probing the Brain

      Neuronal probes can be defined as biohybrid entities where the probes and nerve cells establish a close physical interaction for communicating in one or both directions. During the last decade neuronal probe technology has seen an exploded development. This paper presents newly developed chip–based CyberRat probes for enhanced signal transmission from nerve cells to chip or from chip to nerve cells with an emphasis on in−vivo interfacing, either in terms of signal−to−noise ratio or of spatiotemporal resolution. The oxide−insulated chips featuring large−scale and high−resolution arrays of stimulation and recording elements are a promising technology for high spatiotemporal resolution biohybrid devices, as recently demonstrated by recordings obtained from hippocampal slices and brain cortex in implanted animals. Finally, we report on SigMate, an in−house comprehensive automated tool for processing and analysis of acquired signals by such large scale biohybrid devices.

      S. Vassanelli, F. Felderer, M. Mahmud, M. Maschietto, S. Girardi

  • 2011
  • 2007

      M. Shamim Kaiser, M. Arifur Rahman, Abu M Jafor Alam, A. K. M. Fazlul Haque FUNDAMENTALS OF COMMUNICATION. Reviewed By Dr. M. Lutfar Rahman, Professor, CSE, Dhaka University, Systech Publication Ltd, February 2007.

      M. Shamim Kaiser, M. Arifur Rahman, Abu M Jafor Alam, A. K. M. Fazlul Haque