The mHealth Research group aims at developing biomedical signal processing and machine learning algorithms for remote health monitoring, and prototyping innovative mHealth devices for improving people’s health, overall well-being and quality of life.
OUR TEAM:
Md. Kawser Ahmed
Lecturer, BME, BUET.
M.Sc. Research Student
mHealth Research Group
Shoyad Nuhash
Lecturer, BME, BUET
M.Sc. Research Student
mHealth Research Group
Dr. Nawsabah Noor
[MBBS, MRCP(UK), ECFMG cert.]
Clinical Researcher
mHealth Research Group
Shams Nafisa Ali
Lecturer, BME, BUET
M.Sc. Research Student
mHealth Research Group
Samiul Based Shuvo
Lecturer, BME, BUET
M.Sc. Research Student
mHealth Research Group
Md. Tazuddin Ahmed
Lecturer, BME, BUET
M.Sc. Research Student
mHealth Research Group
Mohammad Zunaed Rafi
Research Assistant
mHealth Research Group
Kaisar Alman
Research Assistant
mHealth Research Group
Awsaf Rahman
Research Assistant
mHealth Research Group
Joydip Paul
Research Assistant
mHealth Research Group
Tonmoy Chandro Saha
Undergraduate Research Student
mHealth Research Group
Adhora Madhuri
Undergraduate Research Student
mHealth Research Group
Mahian Kabir Joarder
Undergraduate Research Student
mHealth Research Group
Tasmia Rahman Aanika
Undergraduate Research Student
mHealth Research Group
Asfina Hassan Juicy
Undergraduate Research Student
mHealth Research Group
Raiyun Kabir
Undergraduate Research Student
mHealth Research Group
Mahmud Wasif Nafee
Undergraduate Research Student
mHealth Research Group
Tasnia Binte Mamun
Undergraduate Research Student
mHealth Research Group
Nusaiba Sobir
Undergraduate Research Student
mHealth Research Group
S.M. Sakeef Sani
Undergraduate Research Student
mHealth Research Group
ADVISORS:
PROJECTS:
PUBLICATIONS:
[1] Shams Nafisa Ali, Samiul Based Shuvo, Md. Ishtiaque Sayeed Al-Manzo, Anwarul Hasan, Taufiq Hasan, “An End-to-end Deep Learning Framework for Real-Time Denoising of Heart Sounds for Cardiac Disease Detection in Unseen Noise”, IEEE Access, July 2023.
[2] Partho Ghosh, Md. Abrar Istiak, Nayeeb Rashid, Ahsan Habib Akash, Ridwan Abrar, Ankan Ghosh Dastider, Asif Shahriyar Sushmit, Taufiq Hasan “Activity Classification from First-Person Office Videos with Visual Privacy Protection”, IEEE Access, June 2023.
[3] Nusrat Binta Nizam, Sadi Mohammad Siddiquee, Mahbuba Shirin, Mohammed Imamul Hassan Bhuiyan, Taufiq Hasan“COVID-19 Severity Prediction from Chest X-ray Images Using an Anatomy-Aware Deep Learning Model.”, Journal of Digital Imaging, May 2023.
[4] Farhat Binte Azam, Md Istiaq Ansari, Shoyad Ibn Sabur Khan Nuhash, Ian McLane, Taufiq Hasan “Cardiac anomaly detection considering an additive noise and convolutional distortion model of heart sound recordings”, Artificial Intelligence in Medicine, November 2022.
[5] Uday Kamal, Mohammad Zunaed, Nusrat Binta Nizam, Taufiq Hasan “Anatomy-xnet: An anatomy aware convolutional neural network for thoracic disease classification in chest x-rays”, IEEE Journal of Biomedical and Health Informatics, August 2022.
[6] Nawsabah Noor, Taufiq Hasan, Meemnur Rashid, Kaisar Ahmed Alman, Homayra Tahseen Hossain, AKM Humayon Kabir “Nutritional Status and Severity Correlation of COPD Patients Admitted in Tertiary Care Hospital”, Bangladesh Journal of Medicine, April 2022.
[7] Nusrat Binta Nizam, Shoyad Ibn Sabur Khan Nuhash, Taufiq Hasan “Hilbert-envelope features for cardiac disease classification from noisy phonocardiograms”, Biomedical Signal Processing and Control, February 2022.
[8] Md Latifur Rahman, Nusrat Binta Nizam, Prasun Datta, Md Moynul Hasan, Taufiq Hasan, Mohammed Imamul Hassan Bhuiyan,“A Wavelet-CNN Feature Fusion Approach for Detecting COVID-19 from Chest Radiographs”, 11th International Conference on Electrical and Computer Engineering (ICECE), 2020.
[9] Mohammad Mostafiz, Rifat Jahan Azad, Nawsabah Noor, Shajib Ghosh, Haris Sair, Paul Nagy, Taufiq Hasan, “A Web-based Assistive Tool for Emergency Physicians in Diagnosing Intracranial Hemorrhage Subtypes from 2D Brain CT Images”, Society for Imaging Informatics in Medicine (SIIM) 2020 Annual Meeting, June 2020, Austin, Texas, USA (abstract).
[10] Nusrat Binta Nizam, Shoyad Nuhash, Ahmed Imtiaz Humayun, Tausif Amim Shadly, Ashraf Ur Rahman, Mohammad Enamul Hakim, AKM Monoarul Islam, Taufiq Hasan, “Cardiac Anomaly Screening Using Machine Learning Enabled Digital Stethoscopes”, Bangladesh Cardiac Society Conference, Dec. 2019, Dhaka, Bangladesh (abstract).
[11] Partho Ghosh, Md Istiak, Nayeeb Rashid, Ahsan Habib Akash, Ridwan Abrar, Ankan Ghosh Dastider, Asif Shahriyar Sushmit, and Taufiq Hasan. “Privacy-Aware Activity Classification from First Person Office Videos.” arXiv preprint arXiv:2006.06246 (2020). [PDF]
[12] Nurul Huda, Sadia Khan, Ragib Abid, Samiul Based Shuvo, Maheen Labib and Taufiq Hasan, “A Low-cost, Low-energy Wearable ECG System with Cloud-Based Arrhythmia Detection.” IEEE TenSymp 2020, Dhaka, Bangladesh.
[13] Ahmed Imtiaz Humayun, Shabnam Ghaffarzadegan, Md. Istiaq Ansari, Zhe Feng, and Taufiq Hasan, “Towards Domain Invariant Heart Sound Abnormality Detection using Learnable Filterbanks.” IEEE Journal of Biomedical and Health Informatics, 2020. [PDF]
[14] Ahmed Imtiaz Humayun, Asif Shahriyar, Taufiq Hasan, Mohammed Imamul Hassan Bhuiyan, “End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNets", IEEE BHI 2019, Chicago, USA [PDF]
[15] Asif Shahriyar, Shakib Uz Zaman, Ahmed Imtiaz Humayun, Taufiq Hasan, Mohammed Imamul Hassan Bhuiyan, “X-Ray Image Compression Using Convolutional Recurrent Neural Networks", IEEE BHI 2019, Chicago, USA [PDF]
[16] Ahmed Imtiaz Humayun, Md. Tauhiduzzaman Khan, Shabnam Ghaffarzadegan, Zhe Feng and Taufiq Hasan, “An Ensemble of Transfer, Semi-supervised and Supervised Learning Methods for Pathological Heart Sound Classification”, INTERSPEECH 2018, Hyderabad, India [PDF]
[17] Ahmed Imtiaz Humayun, Shabnam Ghaffarzadegan, Zhe Feng and Taufiq Hasan, “Learning Front-end Filter-bank Parameters using Convolutional Neural Networks for Abnormal Heart Sound Detection”, EMBC 2018, Hawaii, USA [PDF]
[18] Md. Tauhiduzzaman Khan, Shabnam Ghaffarzadegan, Zhe Feng and Taufiq Hasan, “A Low-cost Wearable Neckband for Robust Diet Activity Monitoring”, BHI 2018, Las Vegas, USA (Poster) [PDF]
Low-cost, Wearable ECG System with Cloud-Based Arrhythmia Detection
Continuous ECG monitoring is an essential tool for Cardiovascular Disease patients but in low resource countries, continuous monitoring of ECG become a challenge due to limited availability of ECG system, high prices and lack of skilled physicians. We present a low-cost, low-power and wireless Flexible fabric-based design of ECG monitoring system with cloud-based automatic arrhythmia detection using Convolutional Neural Network.
Cardiovascular Screening with Heart Sounds
Cardiovascular diseases cause 31% of global deaths. Machine learning enabled stethoscopes can help in early diagnosis by detecting abnormal heart sounds. Proposed end-to-end Deep Learning framework consists of a Littmann stethoscope that connects to the server via an Android smartphone for real-time diagnosis.
Wearable Smart Neckband for Diet Monitoring
Diet monitoring is crucial for diseases such as: diabetes, obesity, eating disorders, hypertension. Automatic monitoring is more effective and accurate than manual count of intake. Developed a fabric-based low-cost ($5) wearable neckband that monitors user’s eating and drinking activities.
RadAssist: An AI-Assisted Tele-Radiology Platform
Radiological imaging diagnosis plays an important role in clinical patient management. We aim to develop advanced deep learning models that can detect clinically important abnormalities from chest X-ray images. Developed system can be integrated within a tele-radiology framework for assisting a radiologist in making more efficient and effective diagnosis.
DengueDrops: A Smart IV Fluid Calculator for Hospitalized Dengue Patients
Dengue has been endemic in the country since 2000. The national guidelines provide methods for IV fluid administration based on patient parameters but the calculation being complex and time-consuming, pose challenges to healthcare professionals during peak dengue seasons when hospitals become overburdened with dengue patients. To address this issue, we propose DengueDrops, a web-based calculator for the calculation of the required fluid amounts and IV flow rates for non-shock (group-B) dengue patients.
OxyJet: A Jet Mixing Principle Based Low-Cost CPAP
The COVID-19 pandemic has affected more than 20 million people worldwide with a death toll of over 700 thousand. Although HFNO and NIPPV are effective in treating severe COVID-19 patients, high-cost of these devices make it impossible to procure sufficient amounts of such ventilation devices in low and middle income countries. We propose OxyJet CPAP, a low-cost NIPPV system that is easy to use, manufacture, and implement within an LMIC healthcare infrastructure.
Low-cost, Wearable ECG System with Cloud-Based Arrhythmia Detection
Continuous ECG monitoring is an essential tool for Cardiovascular Disease patients but in low resource countries, continuous monitoring of ECG become a challenge due to limited availability of ECG system, high prices and lack of skilled physicians. We present a low-cost, low-power and wireless Flexible fabric-based design of ECG monitoring system with cloud-based automatic arrhythmia detection using Convolutional Neural Network.
NEWS:
May 2020: mHealth Lab spin-off project RadAssist wins the 1st Runner-up prize in the “Act COVID-19 National Call” challenge organized by the ICT Ministry, Government of Bangladesh!
April 2020: mHealth Lab team wins the 2nd Runner-up prize in the “Design For Life | Ventilators for ALL” competition organized by Edge, The Foundation!
Dec 2019: mHealth Lab team as an R&D partner of Sonavi Labs (Baltimore, USA) wins the MIT Solve - Tiger Challenge 2019!
Oct 2019: Dr. Taufiq Hasan is invited to Technology Innovation Center, Johns Hopkins School of Medicine as a visiting scholar.
Sep 2019: Dr. Taufiq Hasan is invited to serve as a mentor in the 2019 African Biomedical Engineering Consortium (ABEC) design school to be held in Kampala, Uganda.
Aug 2019: Former Research Assistant Ahmed Imtiaz is starting his PhD at RICE University.
May 2019: Dr. Taufiq Hasan is appointed as a chair of the Biomedical Signal Processing Informatics session at IEEE BHI 2019.
May 2019: Dr. Paul Nagy, Deputy Director of Johns Hopkins Medicine Technology Innovation Center and Associate Professor of Radiology and Radiological Science, joins mHealth Research Group as an Advisor.
April 2019: Congratulations to Anirban Chakraborty and Nusrat Binta Nizam on their success at the Johns Hopkins Design Competition 2019!
April 2019: Paper on Heart Sound Classification and X-Ray Image Compression accepted at IEEE BHI.
October 2018: Dr. Alain Bernard Larbrique, Associate Professor, Johns Hopkins Bloomberg School of Public Health, joined mHealth Research Group as an Advisor.
September 2018: Congratulations to Ahmed Imtiaz Humayun for receiving ISCA Student and Young Scientist Travel grant for attending INTERSPEECH 2018 in Hyderabad, India.
July 2018: Paper on Heart Sound Classification system accepted in INTERSPEECH 2018 to be held in Hyderabad, India.
July 2018: Congratulations to BME undergraduate students Farhana Islam and Mehnaz Urbee for winning 3rd place in the UBORA design competition 2018, Pisa, Italy.
April 2018: Paper on learnable filterbanks for cardiac anomaly detection accepted in IEEE Engineering in Medicine and Biology Conference (EMBC) 2018 to be held in Hawaii, USA.
Department of Biomedical Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka 1000
© mHealth Lab, BME, BUET, 2019