公开(公告)号：US20210259639A1

公开(公告)日：2021-08-26

申请号：US17176229

申请日：2021-02-16

申请人： Northeastern University

发明人： Daniel UVAYDOV ,  Raffaele GUIDA ,  Francesco RESTUCCIA ,  Tommaso MELODIA

IPC分类号： A61B5/00 ,  G16H40/60 ,  G06N3/08 ,  G06N3/04

摘要： A deep learning medical device implantable in a body is provided. The device includes a processing and communication unit and a sensing and actuation unit. The processing and communication unit includes a deep learning module including a neural network trained to process the input samples, received from the sensing and actuation unit, through a plurality of layers to classify physiological parameters and provide classification results. A communication interface in communication with the deep learning module receives the classification results for ultrasonic transmission through biological tissue. Methods of sensing and classifying physiological parameters of a body and methods of embedding deep learning into an implantable medical device are also provided.

公开(公告)号：US20240334209A1

公开(公告)日：2024-10-03

申请号：US18620310

申请日：2024-03-28

申请人： Northeastern University

发明人： Daniel UVAYDOV ,  Milin ZHANG ,  Salvatore D'ORO ,  Tommaso MELODIA ,  Francesco RESTUCCIA ,  Clifton Paul ROBINSON

IPC分类号： H04W24/02 ,  G06N3/0464 ,  G06N3/08 ,  H04B1/12

CPC分类号： H04W24/02 ,  G06N3/0464 ,  G06N3/08 ,  H04B1/12

摘要： Provided herein are methods and systems for identifying one or more unused or underused portions of a wireless radio frequency (RF) spectrum including providing a multi-label multi-class machine learning classifier trained using a set of RF transmission data, receiving, by a receiver, wireless RF signals in an environment suspected of containing unused or underused portions of said RF spectrum, classifying the received wireless RF signals using the classifier; and identifying unused or underused portions of said RF spectrum.