進階篩選

Technical category
    • Intelligent In Situ Monitoring of Membrane Fouling

      AI & IOT Application FutureTech Intelligent In Situ Monitoring of Membrane Fouling

      This technology uses in-situ optical photointerrupt sensorin-situ acoustic ultrasonic transducer to measure the growth of fouling layer thickness during membrane water treatment. Being the world’s first to combine real-time filter speed attenuation dataphysical mode of clogging, the clogging of film can be instantly analyzed in a smart way which in turn effectively extends its lifetime. T
    • Cardiovascular Disease Detection, AnalysisEvaluation System-On-ChipPlatform

      Smart machinerynovel materials FutureTech Cardiovascular Disease Detection, AnalysisEvaluation System-On-ChipPlatform

      The objective of this project is to develop a portablewireless urine detection systemplatform for prevention of cardiovascular disease. The main idea is to develop a system-on-chip, a microelectrodemicrochannel chip to detect biomarkers concentrations in urine. And then, it will be wirelessly transmitted to a smart application platform to evaluate user’s cardiovascular status.
    • Multifunctional liquid crystal smart cloud sensors

      AI & IOT Application FutureTech Multifunctional liquid crystal smart cloud sensors

      This technology is a new microarray chip sensing technology that integrates "organic light-emitting diodes", "liquid crystal chemical sensors" and "mobile communication system" into "multifunctional liquid crystal smart cloud sensors". The obtained signals are uploaded to the cloud for multi-dimensional analysis to achieve multiplex detection in one single sample. This sensor device is lightweight, low-cost, simple to operate, and the target-of-interest can be custom-made according to user needs.
    • 腦電波控制功能性電刺激活動輔具系統

      FutureTech 腦電波控制功能性電刺激活動輔具系統

      We have developed a movement assistive system using EEG-controlled functional electric stimulation system. Users’ movement intentions are recognized by brain computer interface, implemented by deep learning network,the detected users’ intentions are then translated into commands to trigger a functional electric stimulation (FES) device to activate users’ particular movements, such as grasping, hand raising, holding a cup, etc. In our study, we have designed our own wireless dry-electrode EEG systemour own FES system.
  • 1