-
公开(公告)号：US09566216B2
公开(公告)日：2017-02-14
申请号：US14083215
申请日：2013-11-18
CPC分类号： A61K6/0835 , A61F2/30 , A61K6/0008 , A61K6/0067 , A61K6/0082 , A61K6/0085 , A61K6/0215 , A61K6/023 , A61K6/0235 , A61K6/06 , A61K6/0643 , A61K6/083 , A61K49/1878 , A61L24/00 , A61L2300/44 , A61L2400/12 , C08L33/10
摘要： A bone cement formulation comprising: (a) magnetic calcium phosphate nanoparticles present in an amount of 5.0-95 wt. % and having a largest linear dimension of 150 nm to 50 microns; (b) polymerizable acrylate monomer present in an amount of 5.0-95 wt. %; and (c) polyacrylate polymer present in an amount of 0-80 wt. % and having a largest linear dimension from 5.0 to 500 microns. Upon exposure to an alternating magnetic field the formulation is heated which results in polymerization of the acrylate monomer component. The formulation may also be polymerized via the use of chain polymerization initiators.
摘要翻译： 一种骨水泥制剂，其包含：（a）以5.0-95重量％的量存在的磁性磷酸钙纳米颗粒。 并且具有150nm至50微米的最大线性尺寸; （b）可聚合的丙烯酸酯单体，其量为5.0-95wt。 ％; 和（c）以0-80wt。％的量存在的聚丙烯酸酯聚合物。 并且具有5.0至500微米的最大直线尺寸。 在暴露于交变磁场之后，加热制剂，导致丙烯酸酯单体组分的聚合。 制剂也可以通过使用链聚合引发剂进行聚合。
-
公开(公告)号：US11721437B2
公开(公告)日：2023-08-08
申请号：US16429024
申请日：2019-06-02
摘要： A method of generating a digital twin and of using the digital twin to predict activity of an animate subject. The digital twin is generated from at least system model data and movement data. The digital twin can be activated to simulate a specified activity that the subject is performing or will perform. If desired, the subject can be instructed to perform the same activity while wearing at least one wearable sensor, which is applied to the digital twin. Using artificial intelligence techniques, the activity simulation predicts one or more physical outcomes from the activity.
-
公开(公告)号：US10445930B1
公开(公告)日：2019-10-15
申请号：US15982691
申请日：2018-05-17
摘要： A method of using a learning machine to provide a biomechanical data representation of a subject based on markerless video motion capture. The learning machine is trained with both markerless video and marker-based (or other worn body sensor) data, with the marker-based or body worn sensor data being used to generate a full biomechanical model, which is the “ground truth” data. This ground truth data is combined with the markerless video data to generate a training dataset.
-
-
搜索结果
3 条记录 (耗时 0.012 秒)
