2023年7月27日

新的研究表明,持續的算法改進和數據有所改善的準確性技術優越,導致整體平均絕對相對的差異11.3%知道實驗室發布新的數據Bio-RFID傳感器技術。(來源:Towfiqu barbhuiya Unsplash)美國醫療器械公司知道實驗室宣布,其專有的生物——無線射頻識別(RFID)傳感器技術研究顯示出更高的精度。Bio-RFID技術利用光譜學為指導電磁能量通過一種物質或物質捕捉分子簽名。它可以被納入可穿戴、移動或桌上型形式因素。新的研究表明,持續的算法改進和優越的數據提高了技術的準確性。這導致了整體平均絕對相對偏差(MARD)的11.3%。使用G6 Dexcom公司將連續葡萄糖監測(CGM)作為參考設備,研究評估Bio-RFID傳感器不斷和無創性量化血糖的能力。研究數據收集今年5月完成。試驗中,了解實驗室用先進的數據預處理方法來訓練一個光Gradient-Boosting機器(lightGBM)模型。法的目的是預測血糖水平使用或引用3311年觀測設備值,從超過330小時的收集的數據來自13個健康受試者,醫療器械公司說。 Additionally, the firm published data in May that showed that data from five participants using 1,555 observations from 130 hours of data gathering and the initial implementation of the lightGBM ML model generated a MARD of 12.9%. Last month, Know Labs announced the completion of the construction of its Gen 1 prototype, which integrates the Bio-RFID sensor into a portable device. The medical device firm has been using the sensor for the past two years to conduct clinical research in a lab setting and has published results of its proven stability. Furthermore, the Gen 1 device is undertaking testing to optimise the sensor design for data collecting, including considering new environmental and human parameters. Know Labs is anticipating that the device will produce a vast amount of data observations to test algorithm performance in a variety of real-world circumstances where the company’s glucose monitoring device can be used. Do you have interesting content to share with us? Enter your email address so we can get in touch. Related Article