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Researchers at the University of California, Davis have developed a device for multi-dimensional data extraction at the molecular level to allow one to simultaneously detect the presence of a single-molecule electrically, and to extract a chemical fingerprint to identify that molecule optically.

Researchers at the University of California, Davis have developed an invention that utilizes an integrated Raman scanning head and machine vision for high throughput chemical analysis of liquid biopsy samples.

Researchers at the University of California, Davis have developed a sleep quality measuring device to measure waking electroencephalogram (EEG) test to determine the adequacy of sleep

The disclosed methods offer a robust approach to accurately quantify skin optical properties across different skin tones, facilitating improved diagnosis, monitoring, and treatment in dermatology.

Researchers at UC Irvine have developed methods to facilitate the delivery of a high dose, low energy electron beam or X-ray in a compact manner.

One of the key limitations for devices used in point-of-care diagnostics (POCD) is their limit of detection; patient samples used for POCD devices often contain too low of the target analyte. FlexThrough is a newly developed, centrifugal disk (CD)-based method that utilizes the entirety of a liquid sample via recirculation of the sample for efficient mixing as it iteratively passes through the system.

Researchers at UC Irvine have developed an optical detection system for SARS-CoV-2 and other pathogens that features improvements in screening time, cost, sensitivity, and practicality. As vaccine availability, economic pressure, and mental health considerations has gradually returned society to pre-pandemic activities that require frequent and close interactions, it is imperative that SARS-CoV-2 detection systems remain effective.

Researchers at UC Irvine have developed a novel algorithm that more accurately filters raw blood pressure (BP) data collected from continuous non-invasive blood pressure sensors. The algorithm features improvements in eliminating baseline signal drift while maintaining signal integrity and BP estimation accuracy across significant hemodynamic changes.

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Sensor-based patient monitoring is a promising approach to assess risk, which can then be used by healthcare clinics to focus efforts on the highest-risk patients without having to spend the time manually assessing risk. For example, pressure ulcers/injuries are localized damage to the skin and/or underlying tissue that usually occur over a bony prominence and are most common to develop in individuals who have low-mobility, such as those who are bedridden or confined to a wheelchair and consequently are attributed to some combination of pressure, friction, shear force, temperature, humidity, and restriction of blood flow and are more prevalent in patients with chronic health problems. Sensor-based patient monitoring can be tuned to the individual based on the relative sensor readings. However, existing sensor-based monitoring techniques, such as pressure monitoring, are one-off solutions that are not supported by a comprehensive system which integrates sensing, data collection, storage, data analysis, and visualization. While traditional monitoring solutions are suitable for its intended purpose, these approaches require substantial re-programming as the suites of monitoring sensors change over time.

Detection of single ionizing particles at rates approaching the gigahertz (GHz) range per channel has potential for applications in medical imaging and treatment as well as particle and nuclear physics. Current ionizing particle detection systems detect with maximum frame rates of ~500 MHz. As accelerators (e.g. XFELs) are upgraded to deliver trains of pulses at faster rates, detection systems will need to keep pace. Methods and devices that can detect at GHz rates will be required to meet the demands of modern societal needs and equipment.

Common nuclear imaging techniques include computed tomography (CT), single photon emission CT (SPECT), and positron emission tomography (PET). PET differs from other nuclear imaging techniques in that it can visualize both functional and biological activities, including detection of metabolism within human tissues. PET is especially good for imaging patients with cancer, or brain or heart conditions. At low energies, when positrons collide with electrons near the radionuclide decay, Gamma rays (annihilation photons) are created. Gammas originating from the same electron-positron annihilation are generated exclusively in an entangled Bell state. Gammas which do not share an annihilation origin event, such as randoms, are not entangled. Additionally, a gamma which undergoes an internal scatter becomes decoherent (unentangled) from its pair, such as the gammas found in the scattered coincidence pairs. Scattered and random events degrade the image quality. Recently, quantum-based techniques utilizing entanglement of annihilation photons has been recognized as one approach to address scatter and random and to optimize the signal to noise (SNR) ratio.

High-frequency photoacoustic tomography (> 20 MHz) is becoming increasingly important in biomedical applications. However, it requires data acquisition (DAQ) to have commensurately high sampling rate, which imposes challenges to hardwires and increases the cost of building a PA imaging system. For example, the sampling rate should be higher than 80 MHz to cover 100% bandwidth of a 26-MHz transducer (Nuquist limit). A commercial PA imaging system such as Vevo LAZR X (Fujifilm VISUALSONICS Inc. ON, Canada) with 80-MHz sampling rate can cost more than 990,000$ in the United States.Many PA groups use clinical ultrasound DAQs, which are low cost but also have a low sampling rate, e.g., the iu22 system’s sampling rate is 32 MHz.

Hyperspectral imaging, the practice of capturing detailed spectral (color) information from the output of an optical instrument such as a microscope or telescope, is useful in biological and astronomical research and in manufacturing. In addition to being bulky and expensive, existing hyperspectral imagers typically require scanning across a specimen, limiting temporal resolution and preventing dynamic objects from being effectively imaged. Snapshot methods which eliminate scanning are limited by a tradeoff between spatial and spectral resolution.In order to address these problems, researchers at UC Berkeley have developed a hyperspectral imager which can be attached to the output of any benchtop microscope. The imager is compact (about 6-inches), and can achieve a higher spatial resolution than traditional snapshot imagers. Additionally, this imager needs only one exposure to collect measurements for an arbitrary number of spectral filters, giving it unprecedented spectral resolution.

Researchers at UC Irvine have redesigned the vaginal speculum, a medical device routinely used for pap smears, and other medical procedures that involve inspection of the vaginal canal (i.e. IUD insertions, STD testing, and hysterectomies). The novel design addresses several patient discomforts associated with currently used speculums and is more time- and cost-effective for health professionals.

Measurement of electrical activity in nervous tissue has many applications in medicine, but the implantation of a large number of sensors is traditionally very risky and costly. Devices must be large due to their necessary complexity and power requirements, driving up the risk further and discouraging adoption. To address these problems, researchers at UC Berkeley have developed devices and methods to allow small, very simple and power-efficient sensors to transmit information by backscatter feedback. That is, a much more complex and powerful external interrogator sends an electromagnetic or ultrasound signal, which is modulated by the sensor nodes and reflected back to the interrogator. Machine learning algorithms are then able to map the reflected signals to nervous activity. The asymmetric nature of this process allows most of the complexity to be offloaded to the external interrogator, which is not subject to the same constraints as implanted devices. This allows for larger networks of nodes which can generate higher resolution data at lower risks and costs than existing devices.

Success of deep brain stimulation (DBS) procedures relies heavily on the precise placement of electrodes. However, current options for learning this specialized procedure are limited to observing live cases, listening to audio recordings, or watching computer simulation videos. Researchers at UC Irvine have developed a first-of-its-kind, physical simulation model that allows for easy, convenient, and realistic demonstration of DBS electrode placement to benefit both medical professionals and patients alike.

Microelectrodes are the gold standard for measuring the activity of individual neurons at high temporal resolution in any nervous system region and central to defining the role of neural circuits in controlling behavior. Microelectrode technologies such as the Utah or Michigan arrays, have allowed tracking of distributed neural activity with millisecond precision. However, their large footprint and rigidity lead to tissue damage and inflammation that hamper long-term recordings. State of the art Neuropixel and carbon fiber probes have improved on these previous devices by increasing electrode density and reducing probe dimensions and rigidity. Although these probes have advanced the field of recordings, next-generation devices should enable targeted stimulation in addition to colocalized electrical recordings. Optogenetic techniques enable high-speed modulation of cellular activity through targeted expression and activation of light-sensitive opsins. However, given the strong light scattering and high absorption properties of neural tissue optogenetic interfacing with deep neural circuits typically requires the implantation of large-diameter rigid fibers, which can make this approach more invasive than its electrical counterpart.Approaches to integrating optical and electrical modalities have ranged from adding fiber optics to existing Utah arrays to the Optetrode or other integrated electro-optical coaxial structures. These technologies have shown great promise for simultaneous electrical recordings and optical stimulation in vivo. However, the need to reduce the device footprint to minimize immune responses for long-term recordings is still present.

A fundamental limitation for the implantable brain-machine interfaces (BMI) is the wiring requirements for power transfer and signal transmission. Microelectrode arrays (MEAs), the workhorse technology in neuroscience, offer multiplexed electrophysiological recordings with high temporal resolution. However, their use is inherently limited to a few hundred electrodes as direct electronic measurements suffer from complex wiring requirements and inherent bandwidth (spatial multiplexing) limitations due to electron-electron interactions within conductors. Moreover, electrode arrays can only record from small sections of the brain and require invasive cranial surgical operations. The recent discovery of genetically encoded voltage sensitive fluorescence indicators (GEVI) has created tremendous excitement as light offers unparalleled multiplexing and information carrying capabilities. However, GEVI cannot be used in humans as it requires expression of voltage sensitive molecules by neurons and therefore genetic manipulation. In addition, attenuation of visible light in biological tissue renders much of the brain inaccessable to fluorescence based techniques.  

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The inventors have developed a scalable laser aperture that emits light perpendicular to the surface. The aperture can, in principal, scale to arbitrarily large sizes, offering a universal architecture for systems in need of small, intermediate, or high power. The technology is based on photonic crystal apertures, nanostructured apertures that exhibit a quasi-linear dispersion at the center of the Brillouin zone together with a mode-dependent loss controlled by the cavity boundaries, modes, and crystal truncation. Open Dirac cavities protect the fundamental mode and couple higher order modes to lossy bands of the photonic structure. The technology was developed with an open-Dirac electromagnetic aperture, known as a Berkeley Surface Emitting Laser (BKSEL).  The inventors demonstrate a subtle cavity-mode-dependent scaling of losses. For cavities with a quadratic dispersion, detuned from the Dirac singularity, the complex frequencies converge towards each other based on cavity size. While the convergence of the real parts of cavity modes towards each other is delayed, going quickly to zero, the normalized complex free-spectral range converge towards a constant solely governed by the loss rate of Bloch bands. The inventors show that this unique scaling of the complex frequency of cavity modes in open-Dirac electromagnetic apertures guarantees single-mode operation of large cavities. The technology demonstrates scaled up single-mode lasing, and confirmed from far-field measurements. By eliminating limits on electromagnetic aperture size, the technology will enable groundbreaking applications for devices of all sizes, operating at any power level. BACKGROUND Single aperture cavities are bounded by higher order transverse modes, fundamentally limiting the power emitted by single-mode lasers, as well as the brightness of quantum light sources. Electromagnetic apertures support cavity modes that rapidly become arbitrarily close with the size of the aperture. The free-spectral range of existing electromagnetic apertures goes to zero when the size of the aperture increases. As a result, scale-invariant apertures or lasers has remained elusive until now.  Surface-emitting lasers have advantages in scalability over commercially widespread vertical-cavity surface-emitting lasers (VCSELs). When a photonic crystal is truncated to a finite cavity, the continuous bands break up into discrete cavity modes. These higher order modes compete with the fundamental lasing mode and the device becomes more susceptible to multimode lasing response as the cavity size increases. 

Researchers at the University of California, Davis have developed a large area sensor array for ultrasound imaging systems that utilizes high-bandwidth piezoelectric sensors and modular design elements.

As an important tool for electrophysiological recordings, neural electrodes implanted on the brain surface have been instrumental in basic neuroscience research to study large-scale neural dynamics in various cognitive processes, such as sensorimotor processing as well as learning and memory. In clinical settings, neural recordings have been adopted as a standard tool to monitor the brain activity in epilepsy patients before surgery for detection and localization of epileptogenic zones initiating seizures and functional cortical mapping. Neural activity recorded from the brain surface exhibits rich information content about the collective neural activities reflecting the cognitive states and brain functions. For the interpretation of surface potentials in terms of their neural correlates, most research has focused on local neural activities.   From basic neuroscience research to clinical treatments and neural engineering, electrocorticography (ECoG) has been widely used to record surface potentials to evaluate brain function and develop neuroprosthetic devices. However, the requirement of invasive surgeries for implanting ECoG arrays significantly limits the coverage of different cortical regions, preventing simultaneous recordings from spatially distributed cortical networks. However, this rich information content of surface potentials encoded for the large-scale cortical activity remains unexploited and little is known on how local surface potentials are correlated with the spontaneous neural activities of distributed large-scale cortical networks. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

Contact force is a natural way for humans to interact with the physical world around us. However, most of our interactions with the digital world are largely based on a simple binary sense of touch (contact or no contact). Similarly, when interacting with robots to perform complex tasks, such as surgery, we need to acquire the rich force information and contact location, to aid in the task. To address these issues, researchers at UC San Diego have developed WiForce, which is a ‘wireless’ sensor that can be attached to an object or robot, like a sticker. WiForce’s sensor transduces force magnitude and location into phase changes of an incident RF signal, which is reflected back to enable measurement of force and contact location.