• Fetal ECG extraction from maternal ECG using deeply supervised LinkNet++ model 

      Arafat, Rahman; Mahmud, Sakib; Chowdhury, Muhammad E.H.; Yalcin, Huseyin Cagatay; Khandakar, Amith; ... more authors ( Elsevier , 2023 , Article)
      Fetal heart monitoring and early disease detection using non-invasive fetal electrocardiograms (fECG) can help substantially to reduce infant death through improved diagnosis of Coronary Heart Disease (CHD) in the fetus. ...
    • NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern 

      Faisal, Md Ahasan Atick; Chowdhury, Muhammad E.H.; Mahbub, Zaid Bin; Pedersen, Shona; Ahmed, Mosabber Uddin; ... more authors ( Springer Nature , 2023 , Article)
      Neurodegenerative diseases damage neuromuscular tissues and deteriorate motor neurons which affects the motor capacity of the patient. Particularly the walking gait is greatly influenced by the deterioration process. Early ...
    • Signer-Independent Arabic Sign Language Recognition System Using Deep Learning Model 

      Podder, Kanchon Kanti; Ezeddin, Maymouna; Chowdhury, Muhammad E.H.; Sumon, Md Shaheenur Islam; Tahir, Anas M.; ... more authors ( Multidisciplinary Digital Publishing Institute (MDPI) , 2023 , Article)
      Every one of us has a unique manner of communicating to explore the world, and such communication helps to interpret life. Sign language is the popular language of communication for hearing and speech-disabled people. When ...