There is an increasing demand on computerized surgical instrumentation and implants that can acquire intra-operative or in-vivo data for surgeons and engineers. The sensory system is gaining complexity in order to obtain more accurate measurements. Although many off-the-shelf components and chips exist, multiple components are often required to achieve the desired function. Since space is limited in biomedical applications, application specific highly compacted integrated circuits are preferable. In this study, a chip is designed to process an array of microcantilever readout used in an intra-operative soft-tissue balancing instrument.
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http://dx.doi.org/10.1109/IEMBS.2006.259940 | DOI Listing |
Sensors (Basel)
December 2024
The Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon City 1108, Philippines.
Epilepsy, as a common brain disease, causes great pain and stress to patients around the world. At present, the main treatment methods are drug, surgical, and electrical stimulation therapies. Electrical stimulation has recently emerged as an alternative treatment for reducing symptomatic seizures.
View Article and Find Full Text PDFPhysiol Meas
January 2025
University of Duisburg-Essen, Bismarckstr. 81 (BB), Duisburg, 47057, GERMANY.
Objective: In recent years, wearable devices such as smartwatches and smart patches have revolutionized biosignal acquisition and analysis, particularly for monitoring electrocardiography (ECG). However, the limited power supply of these devices often precludes real-time data analysis on the patch itself.
Approach: This paper introduces a novel Python package, tinyHLS (High Level Synthesis), designed
to address these challenges by converting Python-based AI models into platform-independent hardware description language (HDL) code accelerators.
J Imaging
November 2024
Department of Electronic Devices, Circuits and Architectures, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania.
This review provides an in-depth analysis of current hardware acceleration approaches for image processing and neural network inference, focusing on key operations involved in these applications and the hardware platforms used to deploy them. We examine various solutions, including traditional CPU-GPU systems, custom ASIC designs, and FPGA implementations, while also considering emerging low-power, resource-constrained devices.
View Article and Find Full Text PDFCogn Neurodyn
December 2024
Laboratory of Brain Atlas and Brain-Inspired Intelligence, Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 China.
Motor imagery (MI) is an important brain-computer interface (BCI) paradigm. The traditional MI paradigm (imagining different limbs) limits the intuitive control of the outer devices, while fine MI paradigm (imagining different joint movements from the same limb) can control the mechanical arm without cognitive disconnection. However, the decoding performance of fine MI limits its application.
View Article and Find Full Text PDFSensors (Basel)
November 2024
State Key Laboratory of ASIC and System, Key Laboratory for Information Science of Electromagnetic Waves (MoE), School of Information Science and Technology, Fudan University, Shanghai 200433, China.
In terahertz communication systems, lens antennas used in transceivers are basically plano-convex dielectric lenses. The size of a plano-convex lens increases as the aperture increases, and thinner lenses have longer focal lengths. Through theory and simulation, we designed a Fresnel lens suitable for the terahertz band to meet the requirements of large aperture and short focal length, and simulated the performance, advantages, and disadvantages of the terahertz Fresnel lens.
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