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Telehealth-Mediated Physical Rehabilitation Systems and Methods

The use of telemedicine/telehealth increased substantially during the COVID-19 pandemic, leading to its accelerated development, utilization and acceptability. Telehealth momentum with patients, providers, and other stakeholders will likely continue, which will further promote its safe and evidence-based use. Improved healthcare by telehealth has also extended to musculoskeletal care. In a recent study looking at implementation of telehealth physical therapy in response to COVID-19, almost 95% of participants felt satisfied with the outcome they received from the telehealth physical therapy (PT) services, and over 90% expressed willingness to attend another telehealth session. While telehealth has enhanced accessibility by virtual patient visits, certain physical rehabilitation largely depends on physical facility and tools for evaluation and therapy. For example, limb kinematics in PT with respect to the shoulder joint is difficult to evaluate remotely, because the structure of the shoulder allows for tri-planar movement that cannot be estimated by simple single plane joint models. With the emergence of gaming technologies, such as videogames and virtual reality (VR), comes new potential tools for virtual-based physical rehabilitation protocols. Some research has shown digital game environments, and associated peripherals like immersive VR (iVR) headsets, can provide a powerful medium and motivator for physical exercise. And while low-cost motion tracking systems exist to match user movement in the real world to that in the virtual environment, challenges remain in bridging traditional PT tooling and telehealth-friendly physical rehabilitation.

(SD2019-414) MIMO synchronized large aperture Radar

 Researchers from UC San Diego developed Pointillism, a system that enables radars to overcome the challenges posed by specular reflections, sparsity and noise in the radar point clouds, to provide high-fidelity perception of the scene with 3D bounding boxes. Pointillism consists of multiple low-resolution radars placed in a optimal fashion to maximize the spatial diversity and scene information. Pointillism combines this spatial diversity with novel multi-radar fusion algorithms to tackle the problem of specular reflections, sparsity and noise in radar point clouds. Building upon the hardware and algorithms, Pointillism also introduces a novel data-driven approach that enables the detection of multiple dynamic objects in the scene, with their accurate location, orientation and 3D dimensions. Furthermore, Pointillism enables such perception even in inclement weather, thereby paving a way for radar to be the main-stream sensor for autonomous perception.

Flippo The Robo-Shoe-Fly: A Foot Dwelling Social Wearable Companion

Social interactions in school and office settings traditionally involve few coordinated physical interactions, and most group engagement centers on sharing electronic screens. Wearable robot companions are a promising new direction for encouraging coordinated physical movement and social interaction in group settings. A UC Santa Cruz researcher has developed a wearable social companion that encourages users to interact via physical movement.

Magneto-Optic Modulator

Brief description not available

Inter-Brain Measurements for Matching Applications

This technology utilizes inter-subject measurement of brain activity for the purpose of matching individuals. In particular, the invention measures the similarity and differences in neural activity patterns between interacting individuals (either in person or online) as a signature measurement for their matching capabilities. Relevant applications can be in the world of human resources (e.g., building collaborative teams), patient-therapist matching and others. The application relies on the utilization of both custom and commercial devices for measuring brain activity.

Reducing Electrical Current Variations in Phase-Locked Loop Systems

Researchers at the University of California, Davis have developed a method of eliminating electrical current mismatches in the charge pumps of phase-locked loops (PLL) systems - thereby increasing their power efficiency and phase detection capabilities.

Systems and Methods for Sound-Enhanced Meeting Platforms

Computer-based, internet-connected, audio/video meeting platforms have become pervasive worldwide, especially since the 2020 emergence of the COVID-19 pandemic lockdown. These meeting platforms include Cisco Webex, Google Meet, GoTo, Microsoft Teams, and Zoom. However, those popular platforms are optimized for meetings in which all the participants are attending the meeting online, individually. Accordingly, those platforms have shortcomings when used for hybrid meetings in which some participants are attending together in-person and others attending online. Also, the existing platforms are problematic for large meetings in big rooms (e.g. classrooms) in which most or all of the participants are in-person. To address those suboptimal meet platform situations, researchers at UC Berkeley conceived systems, methods, algorithms and other software for a meeting platform that's optimized for hybrid meetings and large in-person meetings. The Berkeley meeting platform offers a user experience that's familiar to users of the conventional meeting platforms. Also, the Berkeley platform doesn't require any specialized participant hardware or specialized physical room infrastructure (beyond standard internet connectivity).

Embedded Power Amplifier

Researchers at the University of California, Davis have developed an amplifier technology that boosts power output in order to improve data transmission speeds for high-frequency communications.

Absorptive Microwave Bandpass Filters

Researchers at the University of California, Davis have developed absorptive bandpass filters that enable improved passband flatness and good impedance matching both in-band and out-of-band.

A Fully Integrated Stretchable Sensor Arrays for Wearable Sign Language Translation To Voice

UCLA researchers in the Department of Bioengineering have developed a novel machine learning assisted wearable sensor system for the direct translation of sign language into voice with high performance.

New And Integrated Method For Continuous Auditory Brain Stimulation

Various examples of delivering continuous auditory stimulation of various kinds (sometimes referred to by the term “entrainment”) have been proposed to modulate brainwaves for therapeutic effect. Current methods of delivering continuous auditory stimulation typically present noises (in the form of clicks, tones, pulses) embedded in music. By modulating the user’s existing audial environment to embed continuous auditory sound stimulation, this technology creates a more tolerable and user-friendly experience that enables prolonged therapeutic stimulation for such neurodegenerative disorders as Alzheimer’s, Parkinson’s and Chronic Traumatic Encephalopathy (CTE).

Vibration Sensing and Long-Distance Sounding with THz Waves

UCLA researchers in the Department of Electrical and Computer Engineering have developed a terahertz (THz) detector that utilizes the micro-Doppler effect to detect vibrations and long-distance sounds.

Decision Making Spike Time Dependent Plasticity (STDP) Based Neuronal Network Learning

Biologically inspired neural networks are capable of performing sophisticated information processing. Information processing by the brain is multilayered and involves many sequential steps before sensory information can be interpreted and translated into a behavior or action. What makes this cascade powerful is its ability to learn and respond to an ever changing environment based on patterns. Eventually, information gathered from the senses may reach decision centers (such as lateral intra parietal cortex) that govern behavior and are under the influence of reward signals. While a great deal of research has gone into understanding mechanisms of learning at the cellular level, there is still much to discover regarding how learning at the cellular level gives rise to learning on the level of animal behavior. One of the most promising mechanisms of synaptic change for learning is spike time dependent plasticity ("STDP").

Deep Learning Network and Compression Framework over Limited Bandwidth Network Links

Researchers at the University of California, Davis have developed a technology that enables the quantization of discrete wavelet transformed coefficients to reduce bandwidth for cloud-based storage applications. 

Compact Ion Gun for Ion Trap Surface Treatment in Quantum Information Processing Architectures

Electromagnetic noise from surfaces is one of the limiting factors for the performance of solid state and trapped ion quantum information processing architectures. This noise introduces gate errors and reduces the coherence time of the systems. Accordingly, there is great commercial interest in reducing the electromagnetic noise generated at the surface of these systems.Surface treatment using ion bombardment has shown to reduce electromagnetic surface noise by two orders of magnitude. In this procedure ions usually from noble gasses are accelerated towards the surface with energies of 300eV to 2keV. Until recently, commercial ion guns have been repurposed for surface cleaning. While these guns can supply the ion flux and energy required to prepare the surface with the desired quality, they are bulky and limit the laser access, making them incompatible with the requirements for ion trap quantum computing.To address this limitation, UC Berkeley researchers have developed an ion gun that enables in-situ surface treatment without sacrificing high optical access, enabling in situ use with a quantum information processor.

Energy Efficient and Scalable Reconfigurable All-to-All Switching Architecture

Researchers at the University of California, Davis have developed a hierarchical optical switch architecture that is low latency and energy efficient.

Multi-Wavelength, Laser Array

Researchers at the University of California, Davis have developed a multi-wavelength, laser array that generates more precise wavelengths than current technologies. The array also delivers narrow linewidths and can operate athermally.

Higher-Speed and More Energy-Efficient Signal Processing Platform for Neural Networks

Researchers at the University of California, Davis have developed a nanophotonic-based platform for signal processing and optical computing in algorithm-based neural networks that is faster and more energy-efficient than current technologies.

Privacy Preserving Stream Analytics

UCLA researchers in the Department of Computer Science have developed a new privacy preserving mechanism for stream analytics.

Field Effect Bipolar Transistor

Researchers at the University of California have developed a field effect bipolar transistor (FEBT) on a unilateral silicon substrate using CMOS/BiCMOS technology for use in switching and amplification of electric signals and as a 1-transistor memory cell for storing information in a suitable circuit.

Nonlinearity Factorization for Up-Conversion Mixer Linearity Analysis

Researchers at the University of California, Davis have developed a nonlinearity factorization scheme/method to fully characterize the time-varying behavior of switching stages with low intermediate frequency (IF).

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