Md. Ashfanoor Kabir, Celia Shahnaz
Shalini Stalin, Vandana Roy, Prashant Kumar Shukla, Atef Zaguia et al.
The electroencephalogram (EEG) signals are a big data which are frequently corrupted by motion artifacts. As human neural diseases, diagnosis and analysis need a robust neurological signal. Consequently, the EEG artifacts’ eradication is a vital step. In this research paper, the primary motion artif...
Samiul Alam, M. I. H. Bhuiyan
In this paper, a method using higher order statistical moments of EEG signals calculated in the empirical mode decomposition (EMD) domain is proposed for detecting seizure and epilepsy. The appropriateness of these moments in distinguishing the EEG signals is investigated through an extensive analys...
Nusrat Jahan Prottasha, Abdullah As Sami, Md. Kowsher, Saydul Akbar Murad et al.
The growth of the Internet has expanded the amount of data expressed by users across multiple platforms. The availability of these different worldviews and individuals' emotions empowers sentiment analysis. However, sentiment analysis becomes even more challenging due to a scarcity of standardized l...
Ahnaf Rashik Hassan, Siuly Siuly, Yanchun Zhang
Background and objective Epileptic seizure detection is traditionally performed by expert clinicians based on visual observation of EEG signals. This process is time-consuming, burdensome, reliant on expensive human resources, and subject to error and bias. In epilepsy research, on the other hand, m...
Md. Mustafizur Rahman, Ajay Krishno Sarkar, Md. Amzad Hossain, Md. Selim Hossain et al.
Assessment of the cognitive functions and state of clinical subjects is an important aspect of e-health care delivery, and in the development of novel human-machine interfaces. A subject can display a range of emotions that significantly influence cognition, and emotion classification through the an...
Umarani Nagavelli, Debabrata Samanta, Partha Chakraborty
At present, a multifaceted clinical disease known as heart failure disease can affect a greater number of people in the world. In the early stages, to evaluate and diagnose the disease of heart failure, cardiac centers and hospitals are heavily based on ECG. The ECG can be considered as a regular to...
Ahnaf Rashik Hassan, Abdülhamit Subaşı
Background and objective Computerized epileptic seizure detection is essential for expediting epilepsy diagnosis and research and for assisting medical professionals. Moreover, the implementation of an epilepsy monitoring device that has low power and is portable requires a reliable and successful s...
Nahian I. Hasan, Arnab Bhattacharjee
Multiple cardiovascular disease classification from Electrocardiogram (ECG) signal is necessary for efficient and fast remedial treatment of the patient. This paper presents a method to classify multiple heart diseases using one dimensional deep convolutional neural network (CNN) where a modified EC...
Mohammed Saidul Islam, Iqram Hussain, Md Mezbaur Rahman, Se Jin Park et al.
State-of-the-art healthcare technologies are incorporating advanced Artificial Intelligence (AI) models, allowing for rapid and easy disease diagnosis. However, most AI models are considered "black boxes," because there is no explanation for the decisions made by these models. Users may find it chal...
Md. Reazul Islam, Md. Mohsin Kabir, M. F. Mridha, Sultan Alfarhood et al.
With an aging population and increased chronic diseases, remote health monitoring has become critical to improving patient care and reducing healthcare costs. The Internet of Things (IoT) has recently drawn much interest as a potential remote health monitoring remedy. IoT-based systems can gather an...
Ahnaf Rashik Hassan, Md. Aynal Haque
Md. Abdul Awal, Sheikh Shanawaz Mostafa, Mohiuddin Ahmad, M. A. Rashid
Ahnaf Rashik Hassan, Abdülhamit Subaşı, Yanchun Zhang
Background: Epileptic seizure detection is traditionally performed by visual observation of Electroencephalogram (EEG) signals. Owing to its onerous and time-consuming nature, seizure detection based on visual inspection hinders epilepsy diagnosis, monitoring, and large-scale data analysis in epilep...
Md. Rashed-Al-Mahfuz, Mohammad Ali Moni, Shahadat Uddin, Salem A. Alyami et al.
BACKGROUND: Diagnosing epileptic seizures using electroencephalogram (EEG) in combination with deep learning computational methods has received much attention in recent years. However, to date, deep learning techniques in seizure detection have not been effectively harnessed due to sub-optimal class...