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Dr Udantha Abeyratne
Dr

Udantha Abeyratne

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Overview

Background

Recent News

August, 2019: Post Doctoral Researchers/Resercah Associates/PhD Candidates

A/Prof Abeyratne is accepting (2021) post-doctoral researchers/covering the areas of: pattern recognition, machine learning, respiratory sound analysis, digital signal processing and smart phone programming. Qualified students are invited to apply for PhD scholarships on a competitve basis.

June 2021:

Snore sound based Sleep Apnea diagnostics intellectual property developed by Dr. Udantha Abeyratne and his team are available for commercialisation. The technology is the culmination of 20 years of ground breaking work leading to four patent applications including two granted ones in the USA (the rest are under examination at various stages) and a large portfolio of peer reviewed publications in international scholarly journals. A Matlab implementation of re-trainable technology and performance comparions against American Academy of Sleep Medicine scoring critera of 2007 (AASM 2007) are available. Prior comparisons on Chicago Criteria ("AASM 1999") are also available via peer-reviewed literature. Our software models indicate that the technology can diagnose sleep apnea at a sensitivity and specificity approching that of a standard facility-based polysomnography (sensitivity, specificity around 90%, 90%-- cross validation studies). Note that the model development data sets available to us (n=100 approx) had been scored per AASM 2007 clinical criteria. Thus, the resulting models require a straight-forward re-training (re-calibration) process on AASM 2012 data before they can be used on subjects diagnosed under AASM 2012 criteria (which is the clinical scoring standard in effect since 2012).

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Assoc./Prof. Udantha Abeyratne is the inventor of the cough-sound based respiratory diagnosis technology (ResApp Health Ltd. (ASX: RAP)) and snore sound based sleep apnea diagnosis technology SnoreSounds.

He earned a PhD (Biomedical Engineering) from Drexel University, USA, and MEng and BScEE degrees in Electrical & Electronic Engineering from Tokushima U, Japan and U Peradeniya, (video here) Sri Lanka respectively. He also received formal post-graduate training in Higher Education (Grad Cert , U of Queensland, Australia) and Paediatric Sleep Science (Grad Cert., U of Western Australia, Australia). He is a Senior Member of the Institute of Electrical & Electronic Engineers (IEEE, USA), and a full Member of the American Academy of Sleep Medicine (AASM).

​Dr. Abeyratne started his research career with a paper on coding techniques for low-bandwidth communication channels. His master's thesis was on a machine learning approach to the human brain activity analysis using electroencephalography (EEG, Brain Waves) and evoked potentials. This approach won the best paper award in ISBET Brain Topography Conference (Osaka, Japan, 1990) and also placed Dr. Abeyratne as a finalist at the Young Investigators' Competition in IFMBE World Congress on Medical Physics and Biomedical Engineering, 1991 (Kyoto, Japan). He completed his PhD (1996) with Prof. Athina Petropulu as the advisor, working on Higher-Order-Spectra and medical ultrasound imaging. The thesis developed slice-based low-complexity algorithms for blind signal identification, tumor detection in ultarsound images, and image deconvolution.

Teaching Activities:

Assoc/Prof. Abeyratne has designed and taught university level courses on digital signal processing, electronic circuits, medical and general instrumentation, medical signal processing, medical imaging, control systems, project management and electromagnetic waves. He has supervised both undergraduate and postgraduate dissertation thesis projects in these areas. Within the last decade five students supervised by him won competitive awards at the UQ Innovation Expo.

Current Research Profile:

Assoc./Prof. Abeyratne's research interests encompass digital signal processing, machine learning, medical instrumentation, medical imaging, electrophysiology, bio-signal analysis and electronics. Over the last two decades A/Prof. Abeyratne has conceptualized, initiated and led the development of a number of innovative technologies funded by prestigious granting agencies such as the Bill & Melinda Gates Foundation, Australian Research Council and the A*-Star Singapore. His research programmes are characteristic of unorthodox approaches resulting in pioneering outcomes that produced spin-off companies, patents and scholarly publications. His research has recieved multiple peer accolades at the international level.

1. Electronic Instrument Design: hand-held ultrasound devices for medical, agricultural and industrial use; stethoscopes for the 21st century (The "Magithescope(c)", winner of two UQ Expo awards in 2013, 2014); biomimetic sensing devices (e.g. electronic nose, e-tongue), low-cost, portable electronic devices ("Tricoders") for diagnosing diseases such as apnea, asthma, pneumonia; wearable electrophysiological devices; real-time fatigue measurement and warning systems; hand-held instruments for the condition monitoring of machinery such as power transformers. Development of diagnostic and treatment devices for sleep apnea. Dr. Abeyratne is especially interested in developing accurate, multi-purpose and low-cost in-situ decision devices for applications in resource-poor regions of the world.

2. Diagnostic and Treatment Technology for Sleep Disorders: speech-like analysis of snore and breathing sounds; sleep diagnostic instrument design; sleep polysomnography, brain wave (EEG) analysis in sleep, quantification of fatigue and sleepiness; sleep apnea; design of apnea treatment devices (CPAP, dental devices); interaction of apnea and chronic diseases. mHealth approaches in sleep diagnostics. A/Prof. Abeyratne pioneered speech-like processing of respiratory sounds, leading to patents, papers and a spin-off company. He conceptualized and led the development of EEG based technology to quantifiy sleepiness in real-time in actual work environments. Outcomes of this program have recieved wide coverage in international media outlets due to its groundbreaking nature and the potential impact.

3. Respiratory Diagnostic Technology: diagnostic instrumentation and algorithm design for respiratory illnesses such as pneumonia, bronchiolitis, asthma, bronchiectasis and COPD; cough sound analysis in respiratory medicine; imaging technology for respiratory diagnosis; Portable diagnostic technologies and mHealth approaches for remote resource-poor areas of the world. About 1 million children below the age of 5 yrs die every year of pneumonia alone, mainly in remote resource-poor areas of the world. Poor access to diagnostics and medical treatment are the major reasons for pneumonia fatalities. A/Prof. Abeyratne proposed a ground-breaking new technology to diagnose pneumonia centred about cough sound analysis. For this research Dr. Abeyratne received funding from UQ, UniQuest and the Bill & Melinda Gates Foundation, which lauded the project (Page 4) as an exmaple for an innovative idea with high impact. Outcomes led to scholarly publications and contributed to patents as well as a spinoff company by UQ.

4. Signal Processing and Machine Intelligence: the analysis of bio-signals such as electroencephalography (EEG), electromyography (EMG); speech and industrial sound analysis, bowel sound analysis and the characterisation of inflammatory bowel disease; cardiovascular signal processing, source localization and blind source separation, higher order spectra, wavelets, pattern recognition, classifier design. Developing technology for monitoring the condition of Left Ventricular Assist Devices (LVAD).

5. mHealth: research on smart phone and other consumer devices as a platform for healthcare delivery. A/Prof Abeyratne is actively engaged in developing mHealth diagnostic solutions, including translating and customising sleep and respiratory technologies. He is also in the process of expanding the work to include meaningful deployment of the technology in both the developed and developing worlds, in collaboration with international NGOs, experts in community medicine, and the UQ spin-off companies resulting from the research program. New national and international collaborations are currently being negotiated to fund and facilitate this work.

The Research Team, Past & Present:

Associate professor Udantha Abeyratne, Dr. Keegan Kosasih (Past PhD graduate); Dr Duleep Herath (past PhD gradute, )Dr. Shahin Akhter (Past PhD graduate), Dr. Vinayak Swarnkar (Past PhD graduate ); Dr. Yusuf Amrulloh (Past PhD graduate); Dr. Shaminda de Silva (Past PhD graduate); Dr. Samantha Karunajeewa (Past PhD graduate); Dr. Suren Rathnayake (Past PhD graduate), Dr. Xiao Di (Past PhD graduate), Dr. T. Emoto (Past PhD work in UQ while at UT), ; Mrunal Markendeya (Current PhD Student); Karen McCloy (current PhD student), Ajith Wakwella (Past MPhil graduate); Lee Teck Hock (Past MPhil Graduate), Tang Xiaoyan (Past MPhil Graduate), Dr. Zhang Guanglan (Past MPhil Graduate), Dr. Syed Adnan (Past MPhil Graduate) and many past and present dissertation thesis students.

Research Collaborators:

Dr. Craig Hukins & Brett Duce (Princess Alexandra Hospital), Prof. Y. Kinouchi & Dr. T. Emoto (U of Tokushima, Japan), Dr. Sarah Biggs (Monash), Dr.Simon Smith (QUT), Dr. Chandima Ekanayake (Griffith U), Dr. Paul Porter (PMH Hospital), Prof. Anne Chang (Menzies School of Health Reserach, CDU), Dr. Scott Mckenzie (Princess Charles Hospital), Dr. Nirmal Weeresekera (JKMRC, UQ), Dr. Rina Triasih (Gadjah Mada U, Indonesia), Dr. K. Puvanendran (1998-2002: Singapore General Hospital, Singapore), Prof.Stanislaw Gubanski (Chalmers U, Sweden).

Availability

Dr Udantha Abeyratne is:
Available for supervision
Media expert

Qualifications

  • Bachelor (Honours) of Science (Advanced), University of Peradeniya
  • Masters (Coursework) of Engineering, University of Tokushima
  • Doctor of Philosophy, Drexel University
  • Postgraduate Diploma in Education, The University of Queensland
  • Postgraduate Diploma, University of Western Australia

Research interests

  • Cough Counting: Respiratory Diagnostics for the Developing and Developed Worlds

    Cough is a common and one of the earliest symptoms in a range of respiratory diseases such as bronchitis, Congestive Heart Disease, pneumonia, asthma and pertussis. Cough frequency and coughing patterns can be useful in the differential diagnosis of diseases and in assessing the treatment outcomes. The nature of nocturnal cough patterns can also be highly useful in managing respiratory diseases. The manual counting of coughs in overnight (or long term) recordings is a tedious process. We are developing cough identification technology targeting ubiquitous consumer devices such as iPads/smart phones. Our methods will be available for both adults and children, including subjects with respiratory diseases. These methods need further development, validation and implementation on smart phones. Students with a background on Digital Signal Processing/Machine Learning/Pattern Recognition/iOS-Android programming and a keen interest in biomedical signal processing will be suitable for this project.

  • Differential Diagnosis of Pneumonia: Respiratory Diagnostics for the Developing and Developed Worlds

    Pneumonia annually kills about a million children throughout the world. The vast majority of these deaths occur in resource poor regions such as the sub-Saharan Africa and remote Asia. Throughout the world pneumonia can be a serious problem in the aftermath of natural disasters and among the elderly. The management of pneumonia is difficult due to field-ready diagnostic facilities as well as the scarcity of trained healthcare workers. The World Health Organization (WHO) has developed a simple clinical algorithm to classify pneumonia. It has a reasonably high sensitivity but a poor specificity leading to over-prescription of antibiotics and the wastage of drug stocks. It has also met with operational challenges in remote communities. We are developing automated pneumonia diagnostic decision technology targeting ubiquitous consumer devices such as iPads/smart phones. Our mathematical algorithms will be available on self-contained smart phones. The phone will be used as the data acquisition, analysis and decision display unit. Our pilot studies indicate that it is indeed possible to diagnose pneumonia using cough sound analysis alone at high performance (sensitivity >90%, specificity>80%). We have also demonstrated that other clinical observations can be used alone, or, together with cough. Recent results we obtained suggest that other measurements alone (e.g. existence of runny nose, #days with runny nose, breathing rate and temperature) can achieve a sensitivity of 91% at the specificity around 72%. Specificity of our method is substantially higher than that, i.e., 38%, of the WHO algorithm while the sensitivities are similar. These methods need further development, validation and implementation on smart phones. Students with a background on Digital Signal Processing/Machine Learning/Pattern Recognition/iOS-Android programming and a keen interest in biomedical signal processing will be suitable for this project.

Research impacts

Patents rsulting from A/Prof Abeyratne's Research Programs:

Multi-parametric analysis of snore sounds for the community screening of sleep apnea with non-gaussianity index, #18880207, USA, Granted (2014); An expanded version under examination (#20150039110, USA, (2015)); Method and apparatus for determining sleep stages, Application #20110301487, USA (2011); A method and apparatus for processing patient sounds, application #2013239327 (Australia); #14/389291 (USA); #13768257.1 (Europe); 2015-502020 (Japan); #201380028268 (China); 10-2014-7030062 (Korea); About 5 other Australian & International PCT stage filings since 2005.

Research spinoff companies resulting from A/Prof Abeyratne's Research Programs (all through The University of Queensland):

News Media Coverage of Research Outputs:

More than 200 major news outlets have reported my work on sleep apnea and respiratory disgnostics. Examples include: ABC Science (Australia), Discovery News (USA), The Australian (Australia), Medical News Today (USA), Z-News (India), (Journal) Otolaryngology-Head & Neck Surgery, Springer USA Press Release, HealthLine News, Science Daily, Australian Life Sceintist, The Times (UK), Nine News (Australia) - video, CBC News (Canada), Sleep Review (journal), Lung Disease News, 2015.

Featured in Magazines

The Future of Healthcare, Ingenuity ("UQ Biomedical Engineering Research Addresses Global Issues", Pages 26-27), Discovery at UQ 2012 ("Sound Asleep?" Page 12), Bill & Melind Gates Foundation Discovery Stretegy Overview (page 4). International Innovation ("Field of Dreams"), UK, 2015.

Works

Search Professor Udantha Abeyratne’s works on UQ eSpace

186 works between 1989 and 2024

61 - 80 of 186 works

2013

Journal Article

ARMA-based spectral bandwidth for evaluation of bowel motility by the analysis of bowel sounds

Emoto, Takahiro, Shono, Koichi, Abeyratne, Udantha R., Okahisa, Toshiya, Yano, Hiromi, Akutagawa, Masatake, Konaka, Shinsuke and Kinouchi, Yohsuke (2013). ARMA-based spectral bandwidth for evaluation of bowel motility by the analysis of bowel sounds. Physiological Measurement, 34 (8), 925-936. doi: 10.1088/0967-3334/34/8/925

ARMA-based spectral bandwidth for evaluation of bowel motility by the analysis of bowel sounds

2013

Journal Article

Cough sound analysis can rapidly diagnose childhood pneumonia

Abeyratne, Udantha R., Swarnkar, Vinayak, Setyati, Amaliya and Triasih, Rina (2013). Cough sound analysis can rapidly diagnose childhood pneumonia. Annals of Biomedical Engineering, 41 (11), 2448-2462. doi: 10.1007/s10439-013-0836-0

Cough sound analysis can rapidly diagnose childhood pneumonia

2013

Journal Article

Automatic identification of wet and dry cough in pediatric patients with respiratory diseases

Swarnkar, Vinayak, Abeyratne, Udantha R., Chang, Anne B., Amrulloh, Yusuf A., Setyati, Amalia and Triasih, Rina (2013). Automatic identification of wet and dry cough in pediatric patients with respiratory diseases. Annals of Biomedical Engineering, 41 (5), 1016-1028. doi: 10.1007/s10439-013-0741-6

Automatic identification of wet and dry cough in pediatric patients with respiratory diseases

2013

Journal Article

Obstructive sleep apnea screening by integrating snore feature classes

Abeyratne, U. R., De Silva, S., Hukins, C. and Duce, B. (2013). Obstructive sleep apnea screening by integrating snore feature classes. Physiological Measurement, 34 (2), 99-121. doi: 10.1088/0967-3334/34/2/99

Obstructive sleep apnea screening by integrating snore feature classes

2013

Conference Publication

Neural Network based algorithm for automatic identification of cough sounds

Vinayak, V., Abeyratne, U. R., Amrulloh, Yusuf, Hukins, Craig, Triasih, Rina and Setyati, Amalia (2013). Neural Network based algorithm for automatic identification of cough sounds. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), Osaka, Japan, 3-7 July 2013. Piscataway, NJ, United States: IEEE. doi: 10.1109/EMBC.2013.6609862

Neural Network based algorithm for automatic identification of cough sounds

2013

Conference Publication

Automatic evaluation of gastrointestinal motor activity through the analysis of bowel sounds

Shono, Koichi, Emoto, Takahiro, Okahisa, Toshiya, Abeyratne, Udantha R., Yano, Hiromi, Akutagawa ,Masatake, Konaka, Shinsuke and Kinouchi, Yohsuke (2013). Automatic evaluation of gastrointestinal motor activity through the analysis of bowel sounds. 10th IASTED International Conference on Biomedical Engineering, BioMed 2013, Innsbruck, Austria, 13-15 February 2013. Anaheim, CA, United States: ACTA Press. doi: 10.2316/P.2013.791-069

Automatic evaluation of gastrointestinal motor activity through the analysis of bowel sounds

2013

Conference Publication

Variation of snoring properties with Macro Sleep Stages in a population of Obstructive Sleep Apnea

Akhter, Shahin, Abeyratne, U. R. and Swarnkar, Vinayak (2013). Variation of snoring properties with Macro Sleep Stages in a population of Obstructive Sleep Apnea. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), Osaka, Japan, 3-7 July 2013. Piscataway, NJ, United States: I E E E. doi: 10.1109/EMBC.2013.6609751

Variation of snoring properties with Macro Sleep Stages in a population of Obstructive Sleep Apnea

2013

Conference Publication

HMM-based snorer group recognition for Sleep Apnea diagnosis

Herath, Dulip L., Abeyratne, Udantha R. and Hukins, Craig (2013). HMM-based snorer group recognition for Sleep Apnea diagnosis. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013, Osaka, Japan, 3 - 7 July 2013. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/EMBC.2013.6610412

HMM-based snorer group recognition for Sleep Apnea diagnosis

2013

Conference Publication

Cough Sound Analysis - A new tool for diagnosing penumonia

Abeyratne, U. R., Swarnkar, V., Triasih, Rina and Setyati, Amaliya (2013). Cough Sound Analysis - A new tool for diagnosing penumonia. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’13), Osaka, Japan, 3-7 July 2013. Piscataway, NJ, United States: I E E E. doi: 10.1109/EMBC.2013.6610724

Cough Sound Analysis - A new tool for diagnosing penumonia

2013

Conference Publication

Automatic snore and breathing sound classification based on the signal envelope

Kashihara, Masato, Emoto, Takahiro, Abeyratne, Udantha R., Kawata, Ikuji, Akutagawa, Masatake, Konaka, Shinsuke and Kinouchi, Yohsuke (2013). Automatic snore and breathing sound classification based on the signal envelope. 10th IASTED International Conference on Biomedical Engineering, BioMed 2013, Innsbruck, Austria, 13-15 February 2013. Anaheim, CA, United States: ACTA Press. doi: 10.2316/P.2013.791-061

Automatic snore and breathing sound classification based on the signal envelope

2012

Journal Article

Impact of gender on snore-based obstructive sleep apnea screening

De Silva, S., Abeyratne, U. R. and Hukins, C. (2012). Impact of gender on snore-based obstructive sleep apnea screening. Physiological Measurement, 33 (4), 587-601. doi: 10.1088/0967-3334/33/4/587

Impact of gender on snore-based obstructive sleep apnea screening

2012

Conference Publication

High frequency analysis of cough sounds in pediatric patients with respiratory diseases

Kosasih, K., Abeyratne, U. R. and Swarnkar, V. (2012). High frequency analysis of cough sounds in pediatric patients with respiratory diseases. Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, San Diego, CA, U.S.A., 28 August - 1 September 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/EMBC.2012.6347277

High frequency analysis of cough sounds in pediatric patients with respiratory diseases

2012

Journal Article

An inverse technique for excitation design in nerve fascicle activation: a theoretical study

Abeyratne, Udantha R. and Xin, Yang (2012). An inverse technique for excitation design in nerve fascicle activation: a theoretical study. International Journal of Medical Engineering and Informatics, 4 (2), 184-195. doi: 10.1504/IJMEI.2012.046980

An inverse technique for excitation design in nerve fascicle activation: a theoretical study

2012

Conference Publication

Automated algorithm for Wet/Dry cough sounds classification

Swarnkar, V., Abeyratne, U. R., Yusuf, A. Amrulloh and Chang, Anne (2012). Automated algorithm for Wet/Dry cough sounds classification. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, San Diego, United States, 28 August-1 September 2012. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/EMBC.2012.6346632

Automated algorithm for Wet/Dry cough sounds classification

2012

Journal Article

Artificial neural networks for breathing and snoring episode detection in sleep sounds

Emoto, Takahiro, Abeyratne, Udantha R., Chen, Yongjian, Kawata, Ikuji, Akutagawa, Masatake and Kinouchi, Yohsuke (2012). Artificial neural networks for breathing and snoring episode detection in sleep sounds. Physiological Measurement, 33 (10), 1675-1689. doi: 10.1088/0967-3334/33/10/1675

Artificial neural networks for breathing and snoring episode detection in sleep sounds

2012

Conference Publication

Gender dependant snore sound based multi feature obstructive sleep apnea screening method

de Silva, Shaminda, Abeyratne, Udantha and Hukins, C. (2012). Gender dependant snore sound based multi feature obstructive sleep apnea screening method. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'12), San Diego, United States, 28 August - 1 September 2012. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/EMBC.2012.6347447

Gender dependant snore sound based multi feature obstructive sleep apnea screening method

2011

Journal Article

A method to screen obstructive sleep apnea using multi-variable non-intrusive measurements

De Silva, S., Abeyratne, U. R. and Hukins, C. (2011). A method to screen obstructive sleep apnea using multi-variable non-intrusive measurements. Physiological Measurement, 32 (4), 445-465. doi: 10.1088/0967-3334/32/4/006

A method to screen obstructive sleep apnea using multi-variable non-intrusive measurements

2011

Journal Article

Testing the system non-linearity in snoring sound via neural networks

Emoto, Takahiro, Abeyratne, Udantha R., Akutagawa, Masatake, Kinouchi, Yohsuke and Konaka, Shinsuke (2011). Testing the system non-linearity in snoring sound via neural networks. International Journal of Medical Engineering and Informatics, 3 (3), 299-310. doi: 10.1504/IJMEI.2011.042875

Testing the system non-linearity in snoring sound via neural networks

2011

Journal Article

High frequency region of the snore spectra carry important information on the disease of sleep apnoea

Emoto, T., Abeyratne, U. R., Akutagawa, M., Konaka, S. and Kinouchi, Y. (2011). High frequency region of the snore spectra carry important information on the disease of sleep apnoea. Journal of Medical Engineering & Technology, 35 (8), 425-431. doi: 10.3109/03091902.2011.626838

High frequency region of the snore spectra carry important information on the disease of sleep apnoea

2011

Conference Publication

Detecting the snore related sound using neural network based technique

Emoto, Takahiro, Abeyratne, Udantha R., Aoki, Yusuke, Akutagawa, Masatake, Kondo, Eiji, Kawata, Ikuji, Konaka, Shinsuke and Kinouchi, Yohsuke (2011). Detecting the snore related sound using neural network based technique. 8th IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, SPPRA, Innsbruck Austria, 2011. Anaheim, Calgary: ACTA Press. doi: 10.2316/P.2011.721-105

Detecting the snore related sound using neural network based technique

Funding

Past funding

  • 2018 - 2019
    Equipment for naturalistic sleep-wake, circadian rhythm, and stress measurement
    UQ Major Equipment and Infrastructure
    Open grant
  • 2017 - 2021
    Brain Asynchrony in Sleep Apnea
    NHMRC Project Grant
    Open grant
  • 2016 - 2018
    ResApp Research Project: Phase 2
    UniQuest Pty Ltd
    Open grant
  • 2015 - 2020
    Analysis of cough and breathing sounds obtained from clinical sites using iPhones and other recording devices
    UniQuest Pty Ltd
    Open grant
  • 2015 - 2017
    Research Sub-Contract between UQ and UniQuest for JHC Perth Clinical Study
    UniQuest Pty Ltd
    Open grant
  • 2014 - 2016
    Snore Sounds Technology
    UniQuest Pty Ltd
    Open grant
  • 2014 - 2015
    Project Asthma mHealth: smartphones for monitoring respiratory distress in asthma
    UQ Collaboration and Industry Engagement Fund - Seed Research Grant
    Open grant
  • 2012 - 2014
    Breathing and snoring Sound Analysis in Sleep Apnea
    ARC Discovery Projects
    Open grant
  • 2009 - 2012
    Diagnosis of Pneumonia Using Non-Contact Sound Recordings
    Bill & Melinda Gates Foundation
    Open grant
  • 2007 - 2009
    Non-contact Instrumentation for the Home Monitoring of Upper Airway Obstructions in Sleep
    ARC Discovery Projects
    Open grant
  • 2006
    Snore Analysis for the Diagnosis of Apnoea
    UQ External Support Enabling Grant
    Open grant
  • 2005 - 2006
    Collection, sharing, visualisation and analysis of locally gathered information from geographical remote areas vulnerable to tidal waves (ARC SR0567373 administered by University of Melbourne).
    University of Melbourne
    Open grant
  • 2004 - 2006
    Micro Structure Analysis Of Snore Signals For the Characterization of Upper Airways During Sleep
    UQ Early Career Researcher
    Open grant
  • 2003
    Novel Instrumentation and Signal Processing Paradigms in the Diagnosis of Sleep Apnoea
    UQ New Staff Research Start-Up Fund
    Open grant

Supervision

Availability

Dr Udantha Abeyratne is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Supervision history

Current supervision

  • Doctor Philosophy

    Physiologic Signal Correlates of Vigilance Related Cognitive Decline in Patients with Obstructive Sleep Apnoea

    Principal Advisor

    Other advisors: Associate Professor Nadeeka Dissanayaka

Completed supervision

Media

Enquiries

Contact Dr Udantha Abeyratne directly for media enquiries about:

  • Brain waves
  • cough sound analysis
  • Diagnosis of sleep disorders
  • Diagnostic ultrasound
  • fatigue & sleepiness
  • Medical instrumentation
  • mHealth
  • respiratory diagnostics
  • Sleep apnea
  • Sleep disorders
  • smart phone as a medical instrument
  • Snoring

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