Dr. Ahsan Khandoker
Prof. ahsan khandoker Professor Biomedical Engineering and Biotechnology

Contact Information
ahsan.khandoker@ku.ac.ae +971 2 312 4171

Biography

Professor Ahsan Khandoker is a theme leader of the Healthcare Engineering Innovation Center (HEIC) at Khalifa University. He has multidisciplinary research accomplishments in Bio-signal processing, Bioinstrumentation, Nonlinear modeling, and Artificial Intelligence techniques applied to sleep apnea, autonomic dysfunctions in cardiovascular diseases, diabetic autonomic neuropathy, fetal cardiology, and psychiatry. A number of ideas proposed in his work have influenced the efforts of the biosignal processing platforms developed by companies such as ResMed Sydney, Compumedics Melbourne Australia, Atom Medical Co Tokyo, and the startup company MARP Abu Dhabi (Twinkle Heart Fetal Phonogram device).

Professor Khandoker extended his collaborative research network to KAIST Korea, King Abdul Aziz University in Jeddah, KSA, Tohoku University Medical School in Japan, the University of Applied Sciences Jena in Germany, University of Rochester Medical Center USA. His research projects are funded by Abu Dhabi Education Council, Bill and Melinda Gates Foundation, Australian Research Council, Abu Dhabi Education Council, as well as Khalifa University Internal funds in cardiac and mental health monitoring research area in collaboration with Cleveland Clinic Abu Dhabi and several key international medical research facilities in Australia, Germany, and Japan. He has developed his teaching philosophy through teaching a variety of Engineering courses (from the first year to final year undergraduate courses and graduate level courses) in various parts of the world (Bangladesh, Malaysia, Japan, Australia, and the UAE) over the last 24 years (since 1996). He particularly emphasizes collaborative and student-centered learning styles which stimulate analytical and critical thinking and thus enhance problem-solving abilities. He designed the classes in such a way that they can empower and motivate students to continue lifelong learning.


Education
  • Ph.D., Electronic and Biomedical Engineering, Muroran Institute of Technology (Japan), 2004
  • MSc in Electronic and Biomedical Engineering, Muroran Institute of Technology (Japan), 2001
  • BSc in Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology (BUET) (Bangladesh), 1996

Teaching
  • Advanced Biosignal Processing (AERO620)
  • Biomedical Circuits and Signals (BMED640)
  • Biorobotics and Medical Device Design (BMED720)
  • Fundamentals of Biomedical Signal Processing (BIOL101)
  • Physiological Control Systems (BMED421)
  • Senior Design Project I (BMED497)
  • Senior Design Project I (BMED497)
  • Senior Design Project II (BMED498)

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Affiliated Centers, Groups & Labs

Research
Research Interests
  • Biomedical Signal Processing
  • Biomedical electronics and medical devices
  • Explainable AI in Medicine
  • Cardiovascular, Respiratory and neuromuscular diseases
  • Developmental and Computational Physiology
  • Digital Biomarkers in Mental Diseases

Research Projects

NOMAD study: Non-invasive Monitoring using Artificial-Intelligence during Dialysis (Funded by CIRA 2022-2025 in collaboration with SEHA Kidney Center Abu Dhabi). PI: Ahsan Khandoker

Hemodialysis (HD) treatment saves the lives of patients with kidney failure, but the procedure is inherently unphysiological and has risks including infection and cardiovascular instability which are associated with morbidity and mortality. Currently, HD requires frequent blood pressure monitoring but requires expert nursing and physician resources to ensure safety. The aim of this project is to use advances in noninvasive wearable technology and explainable AI to devise new algorithms to predict cardiovascular instability or detect infection so that the dialysis treatment can be modified automatically in real-time to treat such problems before they become critical. The partner SEHA Kidney Care will facilitate the clinical implementation of the proposed new technology. Ultimately this can be incorporated into existing dialysis systems with clear potential for commercialization. The outcomes of this project would make fundamental as well as translational research outputs for hemodialysis monitoring and has the potential to improve patient safety.

DENTAPNEA: Design of a low-power wireless dental mouthpiece to assess genioglossal muscle activity in obstructive sleep apnea patients at wakefulness and during sleep [Funded by KAU-KU Joint Project 2021-2024 in collaboration with King Abdul Aziz University Jeddah, KSA]. PI: Ahsan Khandoker

One of the essential prerequisites for effective lung ventilation is a patent upper airway (UA). A combination of inadequate genioglossal function (GG, an extrinsic tongue muscle) and UA-associated anatomy and physiology underlies obstructive sleep apnoea (OSA). Our aim is to design a dental mouthpiece device with embedded wireless Electromyography (EMG) amplifier that allows us to continuously monitor the electrical activity of the GG muscle during sleep and correlate it with gold standard polysomnography for diagnosing OSA. KAU team has started collaborating with KU team for developing a wireless EMG amplifier that acquires GG EMG through electrodes implemented in a dental mouthpiece. Such a device could be a quicker and inexpensive way to screen OSA. It would allow a more reliable interpretation of changes in GG EMG due to physiological mechanisms, thus providing a new methodology for investigating GG function and the role of fatigue in OSA.

Developing a new integrated abdominal Electrography system for noninvasively detecting fetal brain signals (Funded by CIRA 2019-023 in collaboration with Tohoku University Sendai, Japan). PI: Ahsan Khandoker

Fetal brain damage is a common contributing cause of preventable death and adverse neurological outcome (e.g. cerebral palsy) worldwide. At present, there is no device (invasive or non-invasive) in the market to measure fetal brain electrical activity. In this project, we, therefore, will first examine the patterns of fetal brain waves in a pregnant animal model (mice) and then investigate a new method for non-invasive measurement of human fetal brain development (32 weeks gestation till birth) by abdominal surface electrical signal with inexpensive gel electrodes, comparing with fetal fMRI images of the fetal brain and direct lead scalp electroencephagram during labor. The industry partner’s cash contributions for three years can ultimately be incorporated into their existing monitoring device with clear potential for commercialization. The outcomes of this project would make fundamental as well as translational research outputs for fetal neurological screening and its potential to reduce fetal deaths.

MindMyHeart: Personalized smart management test bed for Cardiovascular and Mental Diseases via Technology-enabled Physiological and Behavioral changes (Funded by KU-KAIST Joint Research Center 2019-2022). PI: Ahsan Khandoker

Cardiovascular disease (CVD) is the major cause of death in the UAE/Korea, causing one in every five deaths. Some lifestyle factors (such as an unhealthy diet, lack of exercise, and smoking), known to contribute to a higher risk of CVD, are also common in people with mental health issues (such as depression). Integrated Cardiac and Mental Rehabilitation can significantly improve mortality and morbidity rates, leading to longer independent living and reduced use of healthcare resources. The proposed collaborative project, namely MindMyHeart, sets an overall goal to introduce a personalized home-based rehabilitation program, enabling lifestyle behavioral change towards the increased quality of life with personalized management for CVD and mental health issues. The overall concept of the MindMyHeart platform is easily transferable to address other diseases providing market opportunities for commercialization.  MindMyHeart will be realized in collaboration with the KAIST, Korean Hospitals, and Cleveland Clinic Abu Dhabi through research visits.


Research Staff and Graduate Students:

Staff
Maisam Wahbah Postdoctoral Research Fellow
Mohammad Sami Zitouni Postdoctoral Research Fellow
Mohanad AlKhodari Research Associate
Kiyoe Funamoto Research Associate
Mostafa Moussa Research Associate
Students
Hessa Al Falahi Digital Biomarkers for Fine Motor Decline in Neuropsychiatric Disorders
Murad Almadani Novel AI based model for fetal Electrocardiogram
Amna Samjad Modelling fetal brain and heart interaction through physiological and behavioural information
Sona Al Yunus Integrated Cardiac Rehabilitation system empowering patients to more effectively manage their cardiac health
Yahya Al Zaabi Investigating the role of sleep disordered breathing and its treatment on depressive symptoms in the UAE
Mohammad Khalil Abu Hantash Care4MyHeart:Novel Home-based cardiac rehabilitation technology
Ghada Al Hussein OsteoMentor: An intelligent personalized virtual mentor for long-term self-management of osteoporosis
Namareq Widatalla Detection of End of T wave in fetal ECG signals
Feryal Alskafi EMOTIONAL AWARENESS IS LINKED TO BRAIN TO HEART COUPLING: A NEUROENGINEERING STUDY
Sara Nasrat Brain to heart coupling for use of wearable devices in mental health diagnostics (BRAIN2HEART)
Faris Al Nahdi INVESTIGATING GENIOGLOSSAL MUSCLE ACTIVITY IN OBSTRUCTIVE SLEEP APNEA PATIENTS BY POLYSOMNOGRAPHY
Adil Rehman DESIGN OF A LOW-POWER WIRELESS DENTAL MOUTHPIECE TO ASSESS GENIOGLOSSAL MUSCLE ACTIVITY
Additional Info

https://loop.frontiersin.org/people/75268/overview

https://www.researchgate.net/profile/Ahsan-Khandoker

Vacancies

Three  Research position [Postdoctoral fellows, Research Associate and Research Assistant] are available for three projects funded by Khalifa University Abu Dhabi. The expertise I am looking for are Biosignal processing, image processing, Machine learning, statistical modelling, physiological interpretation with application to cardiovascular diseases, mental health, fetal wellbeing etc. If you could find any suitable candidate who is interested to work in Abu Dhabi, please contact me asap with CV.