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All Journal International Journal of Electrical and Computer Engineering International Journal of Informatics and Communication Technology (IJ-ICT) Indonesian Journal of Electrical Engineering and Computer Science
S. Hasan Saeed
Integral University
Computer Science & IT Electrical & Electronics Engineering

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A Novel Approach For Detection of Neurological Disorders through Electrical Potential Developed in Brain Mohd Suhaib Kidwai; S. Hasan Saeed
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (850.302 KB) | DOI: 10.11591/ijece.v9i4.pp2751-2759

Abstract

This paper talks about the phenomenon of recurrence and using this concept it proposes a novel and a very simple and user friendly method to diagnose the neurological disorders by using the EEG signals.The mathematical concept of recurrence forms the basis for the detection of neurological disorders,and the tool used is MATLAB.  Using MATLAB, an algorithm is designed which uses EEG signals as the input and uses the synchronizing patterns of EEG signals to determine various neurological disorders through graphs and recurrence plots
Evaluation and Analysis of Rate Control Methods for H.264/AVC and MPEG-4 Video Codec Imran Ullah Khan; M. A. Ansari; S. Hasan Saeed; Kakul Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (478.44 KB) | DOI: 10.11591/ijece.v8i2.pp1273-1280

Abstract

Audio, image and video signals produce a vast amount of data. The only solution of this problem is to compress data before storage and transmission. In general there is the three crucial terms as, Bit Rate Reduction, Fast Data Transfer and Reduction in Storage. Rate control is a vigorous factor in video coding. In video communications, rate control must ensure the coded bitstream can be transmitted effectively and make full use of the narrow bandwidth. There are various test models usually suggested by a standard during the development of video codes models in order to video coding which should be suffienciently be efficient based on H.264 at very low bit rate. These models are Test Model Number 5 (TMN5), Test Model Number 8 for H.263, and Verification Model 8 (VM8) for MPEG-4 and H.264 etc. In this work, Rate control analysis for H.264, MPEG-4 performed. For Rate control analysis test model verification model version 8.0 is adopted.
A Novel Approach to Study the Effects of Anesthesia on Respiratory Signals by using the EEG Signals Mohd Suhaib Kidwai; S. Hasan Saeed
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 6, No 2: August 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (600.452 KB) | DOI: 10.11591/ijict.v6i2.pp117-122

Abstract

General anesthesia plays a crucial role in many surgical procedures. It is a drug-induced, reversible state characterized by unconsciousness, anti-nociception or analgesia, immobility and amnesia. On rare occasions, however, the patient can remain unconscious longer than intended, or may regain awareness during surgery. There are no precise measures for maintaining the correct dose of anesthetic, and there is currently no fully reliable instrument to monitor depth of anesthesia. Although a number of devices for monitoring brain function or sympathetic output are commercially available, the anesthetist also relies on clinical assessment and experience to judge anesthetic depth. The undesirable consequences of overdose or unintended awareness might in principle be ameliorated by improved control if we could understand better the changes in function that occur during general anesthesia. Coupling functions prescribe the physical rule specifying how the inter-oscillator interactions occur. They determine the possibility of qualitative transitions between the oscillations, e.g. routes into and out of phase synchronization. Their decomposition can describe the functional contribution from each separate subsystem within a single coupling relationship. In this way, coupling functions offer a unique means of describing mechanisms in a unified and mathematically precise way. It is a fast growing field of research, with much recent progress on the theory and especially towards being able to extract and reconstruct the coupling functions between interacting oscillations from data, leading to useful applications in cardio respiratory interactions.In this paper, a novel approach has been proposed for detecting the changes in synchronism of brain signals, taken from EEG machine. During the effect of anesthesia, there are certain changes in the EEG signals. Those signals show changes in their synchronism. This phenomenon of synchronism can be utilized to study the effect of anesthesia on respiratory parameters like respiration rate etc, and hence the quantity of anesthesia can be regulated, and if any problem occurs in breathing during the effect of anesthesia on patient, that can also be monitored
Simulation and optimization of genetic algorithm-artificial neural network based air quality estimator Shirish Pandey; S. Hasan Saeed; N. R. Kidwai
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp775-783

Abstract

In this work intelligent model for estimation of the concentration of carbon monoxide in a polluted environment is developed on mat Lab platform. The results are validated using data collected from repository linked to University of California. The data records are over the duration of one year using E nose sensor placed in main city of Italy. The records are rectified and segmented at different length to extract the base and divergence values features. An artificial neural network model (ANN) is developed and the result is validated manually. Another optimized genetic algorithm-artificial neural network based air quality estimation model is developed which validate the result using artificial intelligence technique to get a better performance network.
Co-Authors Imran Ullah Khan Kakul Khan M. A. Ansari Mohd Suhaib Kidwai N. R. Kidwai Shirish Pandey