Efficient detection of myocardial infarction from single lead ECG signal

Cognitive load detection using circulant singular spectrum analysis and Binary Harris Hawks Optimization based feature selection

Cognitive load recognition during mental arithmetic activity facilitates to observe and identify the brain’s response towards stress stimulus. As a result, an efficient mental load characterization approach using electroencephalogram (EEG) signal and Bayesian optimized K-Nearest Neighbor (BO-KNN) has been proposed in this work. The study has been conducted on a recorded EEG dataset of 30 healthy subjects who were exposed to an arithmetic questioner. To obtain artifacts free EEG signal, the Savitzky–Golay filtering approach has been utilized. Further, the decomposition of the extracted EEG signal has been carried out using stationary wavelength transform. In this work, the entropy based feature extraction has been performed followed by F-score based feature selection. Top 40 features having the highest precedence have been used for classification using BO-KNN. The rigorous experimental analysis has been performed to analyze the effectiveness of the proposed method over other state-of-the-art methods and it shows that the classification accuracy is substantially improved.

Mental arithmetic task load recognition using EEG signal and Bayesian optimized K-nearest neighbor

EEG based stress classification by using difference plots of variational modes and machine learning

Automated attention deficit classification system from multimodal physiological signals

Solving an arithmetic problem is a complex task which involves fact retrieval, memory, sequencing and decision making. Automatic detection of such an activity from EEG signals will help in understanding of brain response to these cognitive tasks. In this work, we propose a mental arithmetic task detection algorithm from a single lead EEG signal. Fourier Decomposition method is used to decompose the signal into M uniform sub-bands and features, like energy, entropy, and variance, are computed from each of these sub-bands. Kruskal-Wallis method has been used to select only the statistically relevant features. These selected features are, then, used to classify the given EEG dataset into two classes using support vector machine with cubic kernel. To validate the efficacy of the proposed algorithm, simulation results are presented using dataset available on MIT PhysioNet, titled EEG during mental arithmetic task.

Mental Arithmetic Task Classification using Fourier Decomposition Method

: Confidentiality is major task for every sector, keeping things confidential among the organization is the most important factors. Providing security for information is also major concern for the fast growth of the digital exchange of data storage and transmission. As there is rapid growth of using images in many fields, so it is important to protect the private image data from intruders. In this paper, we propose Email authentication for encrypted and decrypted image. In our framework, first, the confidential image will be encrypted using a symmetric key algorithm, Advanced Encryption Standard (abbreviated as AES) by the sender and the encrypted image will be send via Email to receiver. The Cryptographic algorithms provides security to the image, as we proposed AES to our framework it will become more difficult to crack the original image for intruders. Moreover there are some other encryption algorithms to encrypt and decrypt the image but Advanced Encryption standard has its unique features like it protects from brute-force attack and image takes less rounds to encrypt,etc. that gives more security compare with other symmetric algorithms. And Email provides a secure transmission of encrypted image. The above results and analysis for crypto system based on AES algorithm give a high performance. So we have reason to believe that use of this method to encrypt and decrypt the image and sending via Email will have a very good prospect in the future.

Secure image transfer using smtp

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Mental Arithmetic Task Classification using Fourier Decomposition Method

Secure image transfer using smtp