300 research outputs found

    Nanoarray-Enhanced Micromechanical Pressure Sensor with Remote Optical Readout

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    We demonstrate a compact implantable intraocular pressure (IOP) sensor with remote optical readout for glaucoma research and patient management. Using non-invasive white light, we excite the sensor’s pressure-sensitive optomechanical cavity and detect the reflected light, whose optical signature changes as a function of IOP. The sensor has provided robust measurements of hydrostatic pressure between 10-60 mmHg with an accuracy of 0.15 mmHg

    Real-Time In Vivo Intraocular Pressure Monitoring using an Optomechanical Implant and an Artificial Neural Network

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    Optimized glaucoma therapy requires frequent monitoring and timely lowering of elevated intraocular pressure (IOP). A recently developed microscale IOP-monitoring implant, when illuminated with broadband light, reflects a pressure-dependent optical spectrum that is captured and converted to measure IOP. However, its accuracy is limited by background noise and the difficulty of modeling non-linear shifts of the spectra with respect to pressure changes. Using an end-to-end calibration system to train an artificial neural network (ANN) for signal demodulation we improved the speed and accuracy of pressure measurements obtained with an optically probed IOP-monitoring implant and make it suitable for real-time in vivo IOP monitoring. The ANN converts captured optical spectra into corresponding IOP levels. We achieved an IOP-measurement accuracy of ±0.1 mmHg at a measurement rate of 100 Hz, which represents a ten-fold improvement from previously reported values. This technique allowed real-time tracking of artificially induced sub-1 s transient IOP elevations and minor fluctuations induced by the respiratory motion of the rabbits during in vivo monitoring. All in vivo sensor readings paralleled those obtained concurrently using a commercial tonometer and showed consistency within ±2 mmHg. Real-time processing is highly useful for IOP monitoring in clinical settings and home environments and improves the overall practicality of the optical IOP-monitoring approach

    Real-Time In Vivo Intraocular Pressure Monitoring using an Optomechanical Implant and an Artificial Neural Network

    Get PDF
    Optimized glaucoma therapy requires frequent monitoring and timely lowering of elevated intraocular pressure (IOP). A recently developed microscale IOP-monitoring implant, when illuminated with broadband light, reflects a pressure-dependent optical spectrum that is captured and converted to measure IOP. However, its accuracy is limited by background noise and the difficulty of modeling non-linear shifts of the spectra with respect to pressure changes. Using an end-to-end calibration system to train an artificial neural network (ANN) for signal demodulation we improved the speed and accuracy of pressure measurements obtained with an optically probed IOP-monitoring implant and make it suitable for real-time in vivo IOP monitoring. The ANN converts captured optical spectra into corresponding IOP levels. We achieved an IOP-measurement accuracy of ±0.1 mmHg at a measurement rate of 100 Hz, which represents a ten-fold improvement from previously reported values. This technique allowed real-time tracking of artificially induced sub-1 s transient IOP elevations and minor fluctuations induced by the respiratory motion of the rabbits during in vivo monitoring. All in vivo sensor readings paralleled those obtained concurrently using a commercial tonometer and showed consistency within ±2 mmHg. Real-time processing is highly useful for IOP monitoring in clinical settings and home environments and improves the overall practicality of the optical IOP-monitoring approach

    In Vivo Intraocular Pressure Measurements Using A Miniaturized Nano-Photonic Sensor Implant

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    Purpose : We have been developing a nanophotonic pressure sensor whose optical resonance is directly related to intraocular pressure (IOP). Bench testing has demonstrated sensor near-infrared (NIR) reflectance to accurately track pressures from 0-50 mmHg. The current study examined sensor performance following implantation into rabbit eyes for up to one month

    Biocompatible Multifunctional Black-Silicon for Implantable Intraocular Sensor

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    Multifunctional black-silicon (b-Si) integrated on the surface of an implantable intraocular pressure sensor significantly improves sensor performance and reliability in six-month in vivo studies. The antireflective properties of b-Si triples the signal-to-noise ratio and increases the optical readout distance to a clinically viable 12 cm. Tissue growth and inflammation response on the sensor is suppressed demonstrating desirable anti-biofouling properties

    Acoustic Communication for Medical Nanorobots

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    Communication among microscopic robots (nanorobots) can coordinate their activities for biomedical tasks. The feasibility of in vivo ultrasonic communication is evaluated for micron-size robots broadcasting into various types of tissues. Frequencies between 10MHz and 300MHz give the best tradeoff between efficient acoustic generation and attenuation for communication over distances of about 100 microns. Based on these results, we find power available from ambient oxygen and glucose in the bloodstream can readily support communication rates of about 10,000 bits/second between micron-sized robots. We discuss techniques, such as directional acoustic beams, that can increase this rate. The acoustic pressure fields enabling this communication are unlikely to damage nearby tissue, and short bursts at considerably higher power could be of therapeutic use.Comment: added discussion of communication channel capacity in section

    Chemical Power for Microscopic Robots in Capillaries

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    The power available to microscopic robots (nanorobots) that oxidize bloodstream glucose while aggregated in circumferential rings on capillary walls is evaluated with a numerical model using axial symmetry and time-averaged release of oxygen from passing red blood cells. Robots about one micron in size can produce up to several tens of picowatts, in steady-state, if they fully use oxygen reaching their surface from the blood plasma. Robots with pumps and tanks for onboard oxygen storage could collect oxygen to support burst power demands two to three orders of magnitude larger. We evaluate effects of oxygen depletion and local heating on surrounding tissue. These results give the power constraints when robots rely entirely on ambient available oxygen and identify aspects of the robot design significantly affecting available power. More generally, our numerical model provides an approach to evaluating robot design choices for nanomedicine treatments in and near capillaries.Comment: 28 pages, 7 figure

    From Retinal Waves to Activity-Dependent Retinogeniculate Map Development

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    A neural model is described of how spontaneous retinal waves are formed in infant mammals, and how these waves organize activity-dependent development of a topographic map in the lateral geniculate nucleus, with connections from each eye segregated into separate anatomical layers. The model simulates the spontaneous behavior of starburst amacrine cells and retinal ganglion cells during the production of retinal waves during the first few weeks of mammalian postnatal development. It proposes how excitatory and inhibitory mechanisms within individual cells, such as Ca2+-activated K+ channels, and cAMP currents and signaling cascades, can modulate the spatiotemporal dynamics of waves, notably by controlling the after-hyperpolarization currents of starburst amacrine cells. Given the critical role of the geniculate map in the development of visual cortex, these results provide a foundation for analyzing the temporal dynamics whereby the visual cortex itself develops
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