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    • 1. 发明申请
    • POWERED PROSTHETIC DEVICES USING EMG-BASED LOCOMOTION STATE CLASSIFIER
    • 使用基于EMG的机车状态分类器的动力前置装置
    • WO2015006235A1
    • 2015-01-15
    • PCT/US2014/045608
    • 2014-07-07
    • THE STATE OF OREGON ACTING BY AND THROUGH THE STATE BOARD OF HIGHER EDUCATION ON BEHALF OF THE UNIVERSITY OF OREGON
    • HAHN, MichaelJOSHI, Deepak
    • A61F2/72
    • A61F2/72A61B5/04888A61B5/1123A61B5/1126A61F2/60A61F2002/704
    • Real-time control of a prosthetic device using EMG-based locomotion state classification computes a histogram [208] of a time-frequency spectrogram [206] of the EMG data [200] sampled from muscles, classifies the histogram using if-else rules [212] as representing a locomotion steady state [216] or locomotion transition state [214] in the prosthetic device, and controls the prosthetic device using the computed transitions between locomotion modes. The classification may be based on a comparison of feature values [210] derived from the histogram and stored feature values derived from histograms of known locomotion states. Alternatively, the classification may be based on matching scores calculated from the histogram and stored histograms of known locomotion states. The classifying preferably is performed using hierarchical if-else fuzzy classification rules [212], and may further include using a prior locomotion state and a state diagram specifying constraints on locomotion states accessible from other locomotion states.
    • 使用基于EMG的运动状态分类的假体装置的实时控制计算从肌肉采样的EMG数据[200]的时间频谱图[206]的直方图[208],使用if-else规则对直方图进行分类[ 212]表示假体装置中的运动稳定状态[216]或运动过渡状态[214],并且使用所计算的运动模式之间的转换来控制假体装置。 分类可以基于从直方图导出的特征值[210]与从已知运动状态的直方图导出的存储的特征值的比较。 或者,分类可以基于从直方图计算的匹配分数和存储的已知运动状态的直方图。 分类优选地使用分层的if-else模糊分类规则[212]来执行,并且还可以包括使用先前的运动状态和指定从其他运动状态可访问的运动状态的约束的状态图。
    • 10. 发明申请
    • ENHANCED PROTEIN SEPARATION AND ANALYSIS
    • 增强蛋白质分离和分析
    • WO2002082079A1
    • 2002-10-17
    • PCT/US2002/008723
    • 2002-03-22
    • THE STATE OF OREGON, acting by and THROUGH THE STATE BOARD OF HIGHER EDUCATION ON BEHALF OF THE UNIVERSITY OF OREGONMOLECULAR PROBES, INC.CAPALDI, Roderick, A.PATTON, Wayne, F.
    • CAPALDI, Roderick, A.PATTON, Wayne, F.
    • G01N33/48
    • G01N27/44773
    • Methods for enhancing separation and analysis of biological molecules, particularly proteins, and for characterizing tissue, cell, and subcellular (e.g., organelle) expressed protein profiles (proteomes or protein fingerprints) are disclosed. Multi-dimensional diagrams that illustrate the characteristics of the proteins in a sample, based at least in part on interactions between proteins in the system can be produced. In certain embodiments, the diagrams are three-dimensional and incorporate information on protein-protein interactions, protein charge, and protein size for substantially all of the protein species in the sample. Also described are methods of using the provided multi-dimensional diagrams to detect changes in biological systems that are for instance due to disease, drug treatment, environmental condition, and so forth. Methods are provided for correlating changes in three-dimensional proteomic diagrams to disease diagnosis and prognosis, toxicology, therapeutic compound (e.g., drug or hormone) efficacy and mode of action, and drug design.
    • 公开了用于增强生物分子特别是蛋白质的分离和分析以及表征组织,细胞和亚细胞(例如细胞器)表达的蛋白质谱(蛋白质组或蛋白质指纹图谱)的方法。 可以产生说明样品中蛋白质特征的多维图,至少部分地基于系统中蛋白质之间的相互作用。 在某些实施方案中,图是三维的,并且包含关于样品中基本上所有蛋白质种类的蛋白质 - 蛋白质相互作用,蛋白质电荷和蛋白质大小的信息。 还描述了使用所提供的多维图来检测例如由于疾病,药物治疗,环境状况等的生物系统的变化的方法。 提供了用于将三维蛋白质组图的变化与疾病诊断和预后,毒理学,治疗化合物(例如药物或激素)功效和作用方式以及药物设计相关联的方法。