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Results for “"Khawza Ahmed"”

16+ results

Progress in Brain Computer Interface: Challenges and Opportunities

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Simanto Saha, Khondaker A. Mamun, Khawza Ahmed, Raqibul Mostafa et al.

Journal: Frontiers in Systems NeuroscienceYear: 2021Citations: 353

Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Evidence of Variabilities in EEG Dynamics During Motor Imagery-Based Multiclass Brain–Computer Interface

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Simanto Saha, Khawza I. Ahmed, Raqibul Mostafa, Leontios J. Hadjileontiadis et al.

Journal: IEEE Transactions on Neural Systems and Rehabilitation EngineeringYear: 2017Citations: 88

Inter-subject and inter-session variabilities pose a significant challenge in electroencephalogram (EEG)-based brain-computer interface (BCI) systems. Furthermore, high dimensional EEG montages introduce huge computational burden due to excessive number of channels involved. Two experimental, i.e., ...

Life SciencesNeuroscienceCognitive Neuroscience
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Handwritten Bangla digit recognition using Sparse Representation Classifier

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Haider Adnan Khan, Abdullah Al Helal, Khawza I. Ahmed

Year: 2014Citations: 47

We present a framework for handwritten Bangla digit recognition using Sparse Representation Classifier. The classifier assumes that a test sample can be represented as a linear combination of the train samples from its native class. Hence, a test sample can be represented using a dictionary construc...

Physical SciencesEngineeringMedia Technology
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Predicting depressed patients with suicidal ideation from ECG recordings

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Ahsan H. Khandoker, Veena Luthra, Yousef Abouallaban, Simanto Saha et al.

Journal: Medical & Biological Engineering & ComputingYear: 2016Citations: 36

Globally suicidal behavior is the third most common cause of death among patients with major depressive disorder (MDD). This study presents multi-lag tone-entropy (T-E) analysis of heart rate variability (HRV) as a screening tool for identifying MDD patients with suicidal ideation. Sixty-one ECG rec...

Health SciencesMedicineCardiology and Cardiovascular Medicine
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HMM-based Supervised Machine Learning Framework for the Detection of fECG R-R Peak Locations

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Abu Sayeed Ahsanul Huque, Khawza I. Ahmed, Mohammad Abdul Mukit, Raqibul Mostafa

Journal: IRBMYear: 2019Citations: 32

Objective Fetal Electro Cardiogram (fECG) provides critical information on the wellbeing of a foetus heart in its developing stages in the mother's womb. The objective of this work is to extract fECG which is buried in a composite signal consisting of itself, maternal ECG (mECG) and noises contribut...

Physical SciencesComputer ScienceSignal Processing
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Screening Cardiovascular Autonomic Neuropathy in Diabetic Patients With Microvascular Complications Using Machine Learning: A 24-Hour Heart Rate Variability Study

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Mohanad Alkhodari, Mamunur Rashid, Mohammad Abdul Mukit, Khawza I. Ahmed et al.

Journal: IEEE AccessYear: 2021Citations: 30

Cardiovascular autonomic neuropathy (CAN) is one of the most overlooked complications associated with diabetes. It is characterized by damage in the autonomic nerves regulating heart rate and vascular compliance. Ewing battery is currently the diagnostic tool of choice but is unable to detect sub-cl...

Health SciencesMedicineCardiology and Cardiovascular MedicineOpen Access
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Enhanced inter‐subject brain computer interface with associative sensorimotor oscillations

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Simanto Saha, Khawza I. Ahmed, Raqibul Mostafa, Ahsan H. Khandoker et al.

Journal: Healthcare Technology LettersYear: 2016Citations: 24

Electroencephalography (EEG) captures electrophysiological signatures of cortical events from the scalp with high-dimensional electrode montages. Usually, excessive sources produce outliers and potentially affect the actual event related sources. Besides, EEG manifests inherent inter-subject variabi...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Wavelet Entropy-Based Inter-subject Associative Cortical Source Localization for Sensorimotor BCI

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Simanto Saha, Md Shakhawat Hossain, Khawza I. Ahmed, Raqibul Mostafa et al.

Journal: Frontiers in NeuroinformaticsYear: 2019Citations: 22

We propose event-related cortical sources estimation from subject-independent electroencephalography (EEG) recordings for motor imagery brain computer interface (BCI). By using wavelet-based maximum entropy on the mean (wMEM), task-specific EEG channels are selected to predict right hand and right f...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Suicidal Ideation Is Associated with Altered Variability of Fingertip Photo-Plethysmogram Signal in Depressed Patients

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Ahsan H. Khandoker, Veena Luthra, Yousef Abouallaban, Simanto Saha et al.

Journal: Frontiers in PhysiologyYear: 2017Citations: 19

Physiological and psychological underpinnings of suicidal behavior remain ill-defined and lessen timely diagnostic identification of this subgroup of patients. Arterial stiffness is associated with autonomic dysregulation and may be linked to MDD. The aim of this study was to investigate the associa...

Health SciencesMedicineCardiology and Cardiovascular MedicineOpen Access
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Superimposed training-based compressed sensing of sparse multipath channels

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Syed Junaid Nawaz, Khawza I. Ahmed, Mohammad Patwary, Noor M. Khan

Journal: IET CommunicationsYear: 2012Citations: 16

In a number of wireless communication applications, the impulse response of multipath communication channels has sparse nature. In this study, physical model for various propagation environments exhibiting sparse channel structure is considered. A superimposed (SI) training-based compressed channel ...

Physical SciencesEngineeringElectrical and Electronic Engineering
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Machine Learning for Screening Microvascular Complications in Type 2 Diabetic Patients Using Demographic, Clinical, and Laboratory Profiles

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Mamunur Rashid, Mohanad Alkhodari, Abdul Mukit, Khawza I. Ahmed et al.

Journal: Journal of Clinical MedicineYear: 2022Citations: 14

Microvascular complications are one of the key causes of mortality among type 2 diabetic patients. This study was sought to investigate the use of a novel machine learning approach for predicting these complications using only the patient demographic, clinical, and laboratory profiles. A total of 96...

Health SciencesMedicineCardiology and Cardiovascular MedicineOpen Access
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Classification of Short-Segment Pediatric Heart Sounds Based on a Transformer-Based Convolutional Neural Network

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Md Hassanuzzaman, Samit Kumar Ghosh, Mohammad Nurul Akhtar Hasan, Mohammad Abdullah Al Mamun et al.

Journal: IEEE AccessYear: 2025Citations: 11

Congenital heart diseases (CHDs), caused by structural abnormalities in the heart and blood vessels, pose a significant public health concern and contribute significantly to the socioeconomic burden, particularly in pediatric populations. Phonocardiograms (PCGs), as a non-invasive and cost-effective...

Health SciencesMedicinePulmonary and Respiratory MedicineOpen Access
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Prototyping Arduino and Android based m-health solution for diabetes mellitus patient

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Abu Sadat Sabbir, Khandakar Md. Bodroddoza, Abdul Hye, Md. Faysal Ahmed et al.

Year: 2016Citations: 10

Diabetes mellitus is a chronic disease and its prolonged existence may cause proliferation of diverse abnormalities in human physiological system. Maintaining a healthy lifestyle can improve the condition of a diabetic patient. However, continuous monitoring of diabetes level is necessary for adapti...

Health SciencesHealth ProfessionsGeneral Health Professions
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Recognition of Pediatric Congenital Heart Diseases by Using Phonocardiogram Signals and Transformer-Based Neural Networks

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Md Hassanuzzaman, Nurul Akhtar Hasan, Mohammad Abdullah Al Mamun, Mohanad Alkhodari et al.

Year: 2023Citations: 9

The phonocardiogram (PCG) or heart sound auscultation is a low-cost and non-invasive method to diagnose Congenital Heart Disease (CHD). However, recognizing CHD in the pediatric population based on heart sounds is difficult because it requires high medical training and skills. Also, the dependency o...

Health SciencesMedicinePulmonary and Respiratory Medicine
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Estimation of direction of arrival (DOA) using real-time Array Signal Processing

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Md Shahedul Amin, Ahmed-Ur-Rahman, Saabah B. Mahbub, Khawza I. Ahmed et al.

Year: 2008Citations: 9

Array Signal Processing (ASP) is a relatively new technique in Digital Signal Processing (DSP) with many potential applications in communication and speech processing. Direction of arrival (DOA) can be estimated using different techniques evolved with ASP. Spectral-based algorithm and subspace-based...

Physical SciencesComputer ScienceSignal Processing
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