New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficie ....New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficient algorithms for signal quality analysis and enhanced feature extraction methods in resource constrained wearable devices. This will improve the reliability and performance of wearable devices for adoption in intelligent decision-making systems.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Breathing and snoring sound analysis in sleep apnea. About 800,000 Australians suffer from the disease sleep Apnoea (OSA) which has snoring as its earliest symptom. We develop electronics and snore processing algorithms to classify snorers into OSA-positive and OSA-negative classes, based on advanced technology derived from speech recognition systems.
Tooth-mic Devices for Monitoring the Efficacy of Home-based Continuous Positive Airway Pressure (CPAP) Technology. Over 800,000 Australians suffer from Obstructive Sleep Apnea (OSA). OSA patients use twice the health resources compared to healthy people. They are 7 times more likely to cause traffic accidents; in NSW up to 43000 accidents/year are due to OSA. OSA is treatable & consequences such as strokes, diabetes & heart attacks are preventable. The standard OSA treatment is home-based Contin ....Tooth-mic Devices for Monitoring the Efficacy of Home-based Continuous Positive Airway Pressure (CPAP) Technology. Over 800,000 Australians suffer from Obstructive Sleep Apnea (OSA). OSA patients use twice the health resources compared to healthy people. They are 7 times more likely to cause traffic accidents; in NSW up to 43000 accidents/year are due to OSA. OSA is treatable & consequences such as strokes, diabetes & heart attacks are preventable. The standard OSA treatment is home-based Continuous Positive Airway Pressure Therapy. Unfortunately, no effective technique exists to measure the efficacy of the treatment. We propose enabling solutions to this problem via developing technology centered on breathing sound analysis. The project proposes joint work with a US-company facilitating access to advanced technology highly beneficial to Australia.Read moreRead less
Non-contact Instrumentation for the Home Monitoring of Upper Airway Obstructions in Sleep. Over 800,000 Australians suffer from obstructive sleep apnoea costing billions of dollars annually to the nation. Obstructive sleep apnoea patients use twice the health resources compared to a normal person, and 7 times more likely to cause traffic accidents. In NSW alone up to 43000 accidents per year are due to obstructive sleep apnoea. Obstructive sleep apnoea is treatable and thus consequences such as ....Non-contact Instrumentation for the Home Monitoring of Upper Airway Obstructions in Sleep. Over 800,000 Australians suffer from obstructive sleep apnoea costing billions of dollars annually to the nation. Obstructive sleep apnoea patients use twice the health resources compared to a normal person, and 7 times more likely to cause traffic accidents. In NSW alone up to 43000 accidents per year are due to obstructive sleep apnoea. Obstructive sleep apnoea is treatable and thus consequences such as stroke and heart attacks are preventable. At present over 90% patients remain undiagnosed. Current diagnosis is expensive and requires hospitalization; no acceptable mass screening device exists. This project proposes an enabling technology for the population screening of obstructive sleep apnoea based on analysing snoring sounds. Outcomes of the project have the potential to revolutionize the diagnosis of obstructive sleep apnoea.Read moreRead less