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    • 5. 发明授权
    • Unified probabilistic framework for predicting and detecting seizure onsets in the brain and multitherapeutic device
    • 用于预测和检测大脑和多治疗装置中的癫痫发作的统一概率框架
    • US06678548B1
    • 2004-01-13
    • US09693423
    • 2000-10-20
    • Javier Ramón EchauzRosana EstellerBrian LittGeorge John Vachtsevanos
    • Javier Ramón EchauzRosana EstellerBrian LittGeorge John Vachtsevanos
    • A61B504
    • A61B5/7267A61B5/0476A61B5/076A61B5/4094A61B5/7275A61N1/08A61N1/36017A61N1/36064A61N1/36082A61N1/36135G06F19/00G06F19/3456G06F19/3481G06K9/6262G06K9/627G06K9/6278G16H50/20G16H50/50
    • A method and an apparatus for predicting and detecting epileptic seizure onsets within a unified multiresolution probabilistic framework, enabling a portion of the device to automatically deliver a progression of multiple therapies, ranging from benign to aggressive as the probabilities of seizure warrant. Based on novel computational intelligence algorithms, a realistic posterior probability function P(St|x) representing the probability of one or more seizures starting within the next T minutes, given observations x derived from IEEG or other signals, is periodically synthesized for a plurality of prediction time horizons. When coupled with optimally determined thresholds for alarm or therapy activation, probabilities defined in this manner provide anticipatory time-localization of events in a synergistic logarithmic-like array of time resolutions, thus effectively circumventing the performance vs. prediction-horizon tradeoff of single-resolution systems. The longer and shorter prediction time scales are made to correspond to benign and aggressive therapies respectively. The imminence of seizure events serves to modulate the dosage and other parameters of treatment during open-loop or feedback control of seizures once activation is triggered. Fast seizure onset detection is unified within the framework as a degenerate form of prediction at the shortest, or even negative, time horizon. The device is required to learn in order to find the probabilistic prediction and control strategies that will increase the patient's quality of life over time. A quality-of-life index (QOLI) is used as an overall guide in the optimization of patient-specific signal features, the multitherapy activation decision logic, and to document if patients are actually improving.
    • 一种用于在统一的多分辨率概率框架内预测和检测癫痫发作的方法和装置,使得该装置的一部分能够自动地递送多种治疗的进展,从良性到侵略性,随着癫痫发作的可能性。 基于新颖的计算智能算法,给出表示在下一个T分钟内开始的一次或多次癫痫发作的概率的现实后验概率函数P(St | x),给定从IEEG导出的观察值x或其他信号, 预测时间范围。 当与警报或治疗激活的最佳确定的阈值相结合时,以这种方式定义的概率提供事件在时间分辨率协同对数阵列中的预期时间定位,从而有效地规避了单分辨率的性能与预测 - 视距折衷 系统。 较长和较短的预测时间尺度分别对应于良性和侵略性疗法。 癫痫事件的紧急事件有助于在触发激活后,在开环或反馈控制缉获期间调节治疗的剂量和其他参数。 快速发作发作检测在框架内被统一为在最短或甚至负的时间范围内的退化形式的预测。 该设备需要学习才能找到随着时间的推移增加患者生活质量的概率预测和控制策略。 使用生活质量指数(QOLI)作为优化患者特异性信号特征,多功能激活决策逻辑的总体指导,并记录患者是否在实际改善。
    • 6. 发明授权
    • Method and apparatus for predicting the onset of seizures based on features derived from signals indicative of brain activity
    • 基于从指示脑活动的信号导出的特征来预测癫痫发作的方法和装置
    • US06658287B1
    • 2003-12-02
    • US09762455
    • 2001-05-18
    • Brian LittGeorge VachtsevanosJavier EchauzRosana Esteller
    • Brian LittGeorge VachtsevanosJavier EchauzRosana Esteller
    • A61B504
    • A61B5/048A61B5/0476A61B5/4094A61B5/726G06F19/00G06F19/3418G06F19/3481G16H15/00G16H40/63G16H50/20G16H50/50
    • This invention is a method, and system for predicting the onset of a seizure prior to electrograph onset in an individual. During an “off-line” mode, signals representing brain activity of an individual (either stored or real time) are collected, and features are extracted from those signals. A subset of features, which comprise a feature vector, are selected by a predetermined process to most efficiently predict (and detect) a seizure in that individual. An intelligent prediction subsystem is also trained “off-line” based on the feature vector derived from those signals. During “on-line” operation, features are continuously extracted from real time brain activity signals to form a feacture vector, and the feature vector is continuously analyzed with the intelligent prediction subsystem to predict seizure onset in a patient. The system, and method are preferably implemented in an implanted device (102) that is capable of warning externally an individual of the probability of a seizure, and/or automatically taking preventative actions to abort the seizure. In addition, methods are provided for applying intervention measures to an animal to abort or modulat a seizure by adjusting the modality of an intervention measure; and/or parameters of an intervention measure based upon a probability measure indicative of a likelihood of seizure occurrence; and/or a predicted time to seizure onset.
    • 本发明是一种预测个体发作前发作发作的方法和系统。 在“离线”模式中,收集表示个体(存储或实时)的大脑活动的信号,并从那些信号中提取特征。 包括特征向量的特征子集通过预定过程进行选择,以最有效地预测(和检测)该个体中的癫痫发作。 基于从这些信号导出的特征向量,智能预测子系统也被“离线”训练。 在“在线”操作中,从实时脑活动信号中连续提取特征,形成发情矢量,并通过智能预测子系统不断分析特征向量,预测病人发作发作。 系统和方法优选地实施在植入装置(102)中,所述植入装置能够从外部警告个体发作的可能性,和/或自动采取预防措施来中止缉获。 此外,还提供了通过调整干预措施的方式对动物施加干预措施来中止或调节癫痫发作的方法; 和/或基于指示发作发生可能性的概率测量的干预措施的参数; 和/或预测发作时间。
    • 7. 发明申请
    • SELF-ADAPTIVE BIO-SIGNAL AND MODULATION DEVICE
    • 自适应生物信号和调制装置
    • US20120143568A1
    • 2012-06-07
    • US13321339
    • 2010-05-20
    • Cherie KaganBrian LittJonathan Viventi
    • Cherie KaganBrian LittJonathan Viventi
    • G06F17/00H01L27/32H01L51/10
    • A61N1/0529A61N1/36082
    • A sensor-effector system includes an array of sensor-effector transducers providing a plurality of sensed signals and applying a plurality of effector signals. The array provides signals to input signal conditioning circuitry which digitizes and filters the plurality of sensed signals. A processor receives the digitized signals, and processes them to generate multiple feature vectors. It also analyzes the feature vectors to identify patterns and classify the identified patterns and generates at least one response vector resulting from the recognized pattern. The response vector is applied to output signal conditioning circuitry, coupled which converts the response vector to at least one analog signal which is applied as an effector signal to the array of sensor-effector transducers.
    • 传感器 - 效应器系统包括提供多个感测信号并施加多个效应器信号的传感器 - 效应器换能器阵列。 阵列向输入信号调理电路提供信号,数字化和滤波多个感测信号。 处理器接收数字化信号,并处理它们以产生多个特征向量。 它还分析特征向量以识别模式并对所识别的模式进行分类,并生成由识别的模式产生的至少一个响应向量。 响应矢量被应用于输出信号调节电路,其耦合,其将响应矢量转换为至少一个作为效应器信号施加到传感器 - 效应器换能器阵列的模拟信号。