Erick Andres Perez Alday, Annie Gu, Amit Shah, Chad Robichaux et al.
Abstract The subject of the PhysioNet/Computing in Cardiology Challenge 2020 was the identification of cardiac abnormalities in 12-lead electrocardiogram (ECG) recordings. A total of 66,405 recordings were sourced from hospital systems from four distinct countries and annotated with clinical diagnos...
Ahnaf Rashik Hassan, Md. Aynal Haque
Mohd. Hamim, Sumit Paul, Syed Iqramul Hoque, Md. Nafiur Rahman et al.
The advancement of the Internet of Things technology is playing a key role in developing the health sector by making it much more accessible and affordable through easy to use applications for virtual and distant interactions with patients. Taking the capability of IoT technology into account, it is...
Iqram Hussain, Md Azam Hossain, Rafsan Jany, Md Abdul Bari et al.
Electroencephalography (EEG) is immediate and sensitive to neurological changes resulting from sleep stages and is considered a computing tool for understanding the association between neurological outcomes and sleep stages. EEG is expected to be an efficient approach for sleep stage prediction outs...
Anindya Bijoy Das, Mohammed Imamul Hassan Bhuiyan, Samiul Alam
Sayeed Shafayet Chowdhury, Rakib Hyder, Md Samzid Bin Hafiz, Mohammad Ariful Haque
Heart rate (HR) monitoring using photoplethysmographic (PPG) signals recorded from wearers' wrist greatly facilitates design of wearable devices and maximizes user experience. However, placing PPG sensors in wrist causes much stronger and complicated motion artifacts (MA) due to loose interface betw...
Qin Qin, Jianqing Li, Li Zhang, Yinggao Yue et al.
Automatic feature extraction and classification are two main tasks in abnormal ECG beat recognition. Feature extraction is an important prerequisite prior to classification since it provides the classifier with input features, and the performance of classifier depends significantly on the quality of...
Ahmed Imtiaz Humayun, Shabnam Ghaffarzadegan, Md. Istiaq Ansari, Zhe Feng et al.
OBJECTIVE: Cardiac auscultation is the most practiced non-invasive and cost-effective procedure for the early diagnosis of heart diseases. While machine learning based systems can aid in automatically screening patients, the robustness of these systems is affected by numerous factors including the s...
A M Muntasir Rahman, Tahsinur Rahman, Nawab Haider Ghani, Sazzad Hossain et al.
Patient monitoring is a pivotal part of the health care system nowadays, either at hospitals or at home. This paper proposes an intelligent patient monitoring system that automatically screens the patient's health condition through various sensors. The data is then processed using a Raspberry Pi and...
Md Shofiqul Islam, Khondokar Fida Hasan, Sunjida Sultana, Shahadat Uddin et al.
Deep learning-based models have achieved significant success in detecting cardiac arrhythmia by analyzing ECG signals to categorize patient heartbeats. To improve the performance of such models, we have developed a novel hybrid hierarchical attention-based bidirectional recurrent neural network with...
Mohammad Shahadat Hossain, Saifur Rahaman, Rashed Mustafa, Karl Andersson
Acute coronary syndrome (ACS) is responsible for the obstruction of coronary arteries, resulting in the loss of lives. The onset of ACS can be determined by looking at the various signs and symptoms of a patient. However, the accuracy of ACS determination is often put into question since there exist...
Sakib Mahmud, Nabil Ibtehaz, Amith Khandakar, Anas Tahir et al.
Cardiovascular diseases are the most common causes of death around the world. To detect and treat heart-related diseases, continuous blood pressure (BP) monitoring along with many other parameters are required. Several invasive and non-invasive methods have been developed for this purpose. Most exis...
Tanjim Mahmud, Anik Barua, Manoara Begum, Eipshita Chakma et al.
Cardiovascular diseases (CVDs), which include heart disorders, are the most prevalent and significant causes of death worldwide, including Bangladesh. Blood artery problems, rhythm issues, chest pain, heart attacks, strokes, and erratic blood pressure are a few of these. In Bangladesh, cardiovascula...
Muhammad Abdullah Arafat, Abdul Wadud Chowdhury, Md. Kamrul Hasan
Md. Raseduzzaman Ruman, Amit Barua, Waladur Rahman, Khan Roushan Jahan et al.
This paper represents the system for monitoring the patient's body 24/7 by using IoT. Now a days, patient monitoring system is getting much more popularity to the researcher and patient guardian. This system has the capability to monitor physiological parameters form patient body at every 15 seconds...