Air Force Research Laboratory / Synopsys / Qualcomm / Xilinx / FPGA / /
Country
United States / / /
Event
Product Issues / /
Facility
American College of Cardiology / Open Cell Library / University of Illinois / Air Force Research Laboratory / /
IndustryTerm
signal peak detection algorithms / sensor fusion algorithms / nm technology / signal fusion algorithm / low energy / heart rate monitoring algorithms / hierarchical memory systems / backward search radius / onset detection algorithms / embedded applications / onset detection algorithm / biomedical applications / lightweight processor / threshold-based peak detection algorithm / local search / monitoring applications / low energy consumption / real time / embedded medical monitoring devices / peak detection algorithms / signal processing / lower energy / biomedical signal processing / real-time heart rate / real-time estimation / peak detection algorithm / energy / real-time heart rate monitoring / multiprocessor system-on-chip / backward search / heart rate estimation algorithm / final product / potential applications / energy consumption / explored different hardware technologies / software implementation / tight energy / real-time biomedical monitoring / real-time processing / heart estimation algorithm / embedded processors / tools / energy efficiency / detection algorithm / wearable monitoring devices / signal processing algorithms / complicated processing pipelines / wearable devices / wearable device / peak detection using energy analysis technique / on-chip / technology library / open-source algorithm / optimized peak detection algorithm / /
OperatingSystem
Android / /
Organization
FPGA / National Science Foundation / Medicine and Biology Society / Department of Energy / ASIC / University of Illinois / the American College / Air Force office of Scientific Research / Detection and Recovery Unit / /
Person
Jenny Applequist / Homa Alemzadeh / I. Al Khatib / /