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Field of Research : Biomechanical Engineering
Status : Active
Research Topic : Recirculation System
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  • Researchers (57)
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  • Active Funded Activity

    ARC Future Fellowships - Grant ID: FT200100329

    Funder
    Australian Research Council
    Funding Amount
    $884,404.00
    Summary
    Platform technology to decode motor control through ultra high-field MRI. This project aims to advance our understanding of the poorly understood neural circuits that enable fine motor control in humans. To obtain this knowledge, new platform technology will be developed to capture the full kinematics of the hand during concurrent functional magnetic resonance imaging at ultra high-field. This device will allow testing of fundamental theories describing the canonical microcircuits involved in ha .... Platform technology to decode motor control through ultra high-field MRI. This project aims to advance our understanding of the poorly understood neural circuits that enable fine motor control in humans. To obtain this knowledge, new platform technology will be developed to capture the full kinematics of the hand during concurrent functional magnetic resonance imaging at ultra high-field. This device will allow testing of fundamental theories describing the canonical microcircuits involved in hand motion. Expected outcomes include new evidence of mirror neurons and observation of predictive error signals in the motor cortex. This new knowledge paves the way towards improved computer-brain interface technology which is likely to create benefits through translation to applications such as artificial limb control.
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    Active Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE210100001

    Funder
    Australian Research Council
    Funding Amount
    $875,000.00
    Summary
    A 3-photon imaging system for deep live imaging. This project aims to establish Australia’s first 3-photon microscope system with adaptive optics for deep intravital imaging. This advanced imaging system will enable researchers to investigate the biology of cells and tissue structures in a wide range of organs and engineered tissues, to a degree not possible with existing technology. This project will capitalise on advanced laser, microscope and adaptive optics technologies with the expected out .... A 3-photon imaging system for deep live imaging. This project aims to establish Australia’s first 3-photon microscope system with adaptive optics for deep intravital imaging. This advanced imaging system will enable researchers to investigate the biology of cells and tissue structures in a wide range of organs and engineered tissues, to a degree not possible with existing technology. This project will capitalise on advanced laser, microscope and adaptive optics technologies with the expected outcomes to include the generation of new knowledge of major biological systems, including the immune system and the nervous system. This will provide significant benefits to fundamental interdisciplinary research into immunology, infectious disease, neuroscience, mechanobiology and engineering.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT200100098

    Funder
    Australian Research Council
    Funding Amount
    $920,059.00
    Summary
    Advancing human movement evaluation using artificial intelligence. Human movement disorders affect one-third of Australians; however, conventional approaches to assessing joint motion are costly and largely clinic- or laboratory-based. This project aims to combine biomechanical modelling and advanced machine learning to non-invasively produce accurate, low-cost, user-friendly shoulder and elbow joint angle measurements using wearable inertial sensors. The technology will enable a non-expert to o .... Advancing human movement evaluation using artificial intelligence. Human movement disorders affect one-third of Australians; however, conventional approaches to assessing joint motion are costly and largely clinic- or laboratory-based. This project aims to combine biomechanical modelling and advanced machine learning to non-invasively produce accurate, low-cost, user-friendly shoulder and elbow joint angle measurements using wearable inertial sensors. The technology will enable a non-expert to obtain reliable kinematics data in any location. Accurate, wearable motion measurement will benefit next-generation healthcare including telemedicine and remote rehabilitation for isolated communities, performance monitoring of elite athletes and military personnel, and the gaming and film/animation industries.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200103492

    Funder
    Australian Research Council
    Funding Amount
    $420,000.00
    Summary
    Mathematical Modelling of the Mechanobiology of Arterial Plaque Growth. Plaque growth is a chronic inflammatory response induced by the interactions between endothelial cells, lipids, monocytes/macrophages, smooth muscle cells and platelets in the arteries. It involves many different biological processes, such as lipid deposition, inflammation and angiogenesis, and their interactions with the microcirculation. To understand the underlying mechanobiology, we propose to develop a mathematical mode .... Mathematical Modelling of the Mechanobiology of Arterial Plaque Growth. Plaque growth is a chronic inflammatory response induced by the interactions between endothelial cells, lipids, monocytes/macrophages, smooth muscle cells and platelets in the arteries. It involves many different biological processes, such as lipid deposition, inflammation and angiogenesis, and their interactions with the microcirculation. To understand the underlying mechanobiology, we propose to develop a mathematical model to interpret plaque growth by integrating these dynamic biological processes. It will offer a systematic rational understanding of plaque growth. New models will be provided to better interpret biological data and contribute to our knowledge in quantifying complex biological mechanisms during growth and development.
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    Showing 1-4 of 4 Funded Activites

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