Mahmoud Dahmani, Muhammad E. H. Chowdhury, Amith Khandakar, Tawsifur Rahman et al.
In the 34 developed and 156 developing countries, there are ~132 million disabled people who need a wheelchair, constituting 1.86% of the world population. Moreover, there are millions of people suffering from diseases related to motor disabilities, which cause inability to produce controlled moveme...
Amith Khandakar, Sakib Mahmud, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz et al.
An intelligent insole system may monitor the individual's foot pressure and temperature in real-time from the comfort of their home, which can help capture foot problems in their earliest stages. Constant monitoring for foot complications is essential to avoid potentially devastating outcomes from c...
Nabil Ibtehaz, Muhammad E. H. Chowdhury, Amith Khandakar, Serkan Kıranyaz et al.
In recent years, physiological signal-based authentication has shown great promises, for its inherent robustness against forgery. Electrocardiogram (ECG) signal, being the most widely studied biosignal, has also received the highest level of attention in this regard. It has been proven with numerous...
Amran Hossain, Mohammad Tariqul Islam, Tawsifur Rahman, Muhammad E. H. Chowdhury et al.
Automated brain tumor segmentation from reconstructed microwave (RMW) brain images and image classification is essential for the investigation and monitoring of the progression of brain disease. The manual detection, classification, and segmentation of tumors are extremely time-consuming but crucial...
Promit Basak, Ahsanul Hoque Sakib, Muhammad E. H. Chowdhury, Nasser Al‐Emadi et al.
Monitoring the electrical pulse of fetal heart through a non-invasive fetal electrocardiogram (fECG) can easily detect abnormalities in the developing heart to significantly reduce the infant mortality rate and post-natal complications. Due to the overlapping of maternal and fetal R-peaks, the low a...
Nabil Ibtehaz, Muhammad E. H. Chowdhury, Amith Khandakar, Serkan Kıranyaz et al.
Abstract Raman spectroscopy provides a vibrational profile of the molecules and thus can be used to uniquely identify different kinds of materials. This sort of molecule fingerprinting has thus led to the widespread application of Raman spectrum in various fields like medical diagnosis, forensics, m...
Arafat Rahman, Muhammad E. H. Chowdhury, Amith Khandakar, Anas Tahir et al.
Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has become a potential field of research in recent years. Although several studies have been conducted, still there are some vital challenges present in the deployment of EEG-based biometrics, which is stable and c...
Md Shafayet Hossain, Mamun Bin Ibne Reaz, Muhammad E. H. Chowdhury, Sawal Hamid Md Ali et al.
Physiological signal measurement and processing are increasingly becoming popular in the ambulatory setting as the hospital-centric treatment is moving towards wearable and ubiquitous monitoring. Most of the physiological signals are highly susceptible to various types of noises, especially movement...
Md Shafayet Hossain, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali et al.
The electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals, highly non-stationary in nature, greatly suffers from motion artifacts while recorded using wearable sensors. Since successful detection of various neurological and neuromuscular disorders is greatly dependent ...
Sakib Mahmud, Muhammad E. H. Chowdhury, Serkan Kıranyaz, Malisha Islam Tapotee et al.
Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bo...
Fahmida Haque, Mamun Bin Ibne Reaz, Muhammad E. H. Chowdhury, Serkan Kıranyaz et al.
Background. Diabetic sensorimotor polyneuropathy (DSPN) is a major form of complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis is very common and well-established in the field of research, its application in DSPN diagnosi...
Anas Tahir, Muhammad E. H. Chowdhury, Amith Khandakar, Tawsifur Rahman et al.
The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 on pulmonary tissues, chest radiographic imaging has become a necessity for screening and monitoring the disease. Numerous...
Yazan Qiblawey, Anas Tahir, Muhammad E. H. Chowdhury, Amith Khandakar et al.
Detecting COVID-19 at an early stage is essential to reduce the mortality risk of the patients. In this study, a cascaded system is proposed to segment the lung, detect, localize, and quantify COVID-19 infections from computed tomography images. An extensive set of experiments were performed using E...
Arafat Rahman, Muhammad E. H. Chowdhury, Amith Khandakar, Serkan Kıranyaz et al.
Electroencephalography (EEG) based biometric systems are gaining attention for their anti-spoofing capability but lack accuracy due to signal variability at different psychological and physiological conditions. On the other hand, keystroke dynamics-based systems achieve very high accuracy but have l...
Kanchon Kanti Podder, Ludmila Emdad Khan, Jyoti Chakma, Muhammad E. H. Chowdhury et al.
According to UNESCO's Atlas of the World's Languages in Danger, 40% of the languages today are counted as endangered in the future. Indigenous languages are endangered because of the less availability of interactive learning mediums for those languages. Thus this paper proposes an interactive deep l...