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1. 发明授权

US07333851B2 Unified probabilistic framework for predicting and detecting seizure onsets in the brain and multitherapeutic device 有权
标题翻译：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
公开(公告)号：US07333851B2
公开(公告)日：2008-02-19
申请号：US10662072
申请日：2003-09-12
申请人： Javier Ramón Echauz , Rosana Esteller , Brian Litt , George John Vachtsevanos
发明人： Javier Ramón Echauz , Rosana Esteller , Brian Litt , George John Vachtsevanos
IPC分类号： A61B5/04
CPC分类号： A61B5/7267 , A61B5/0476 , A61B5/076 , A61B5/4094 , A61B5/7275 , A61N1/08 , A61N1/36017 , A61N1/36064 , A61N1/36082 , A61N1/36135 , G06F19/00 , G06F19/3456 , G06F19/3481 , G06K9/6262 , G06K9/627 , G06K9/6278 , G16H50/20 , G16H50/50
摘要： 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.
摘要翻译：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，给定从IEEG导出的观察值x或其他信号周期性地合成多个预测时间间隔。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。

2. 发明授权

US08065011B2 Adaptive method and apparatus for forecasting and controlling neurological disturbances under a multi-level control 有权
标题翻译：用于预测和控制多层次控制下的神经障碍的自适应方法和装置
公开(公告)号：US08065011B2
公开(公告)日：2011-11-22
申请号：US11469029
申请日：2006-08-31
申请人： Javier Ramón Echauz , Brian Litt , Rosana Esteller , George John Vachtsevanos
发明人： Javier Ramón Echauz , Brian Litt , Rosana Esteller , George John Vachtsevanos
IPC分类号： A61N1/00
CPC分类号： A61B5/076 , A61B5/0476 , A61B5/0482 , A61B5/4094 , A61B5/486 , A61B5/7203 , A61B5/726 , A61B5/7264 , A61B5/7267 , A61B5/7275 , A61N1/08 , A61N1/36082 , G06F19/00 , G06K9/00523
摘要： An adaptive method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented. This high level controller also establishes the initial system settings (off-line) and subsequent settings (on-line) or tunings through an outer control loop by an intelligent procedure that incorporates knowledge as it arises. The subsequent adaptive settings for the system are determined in conjunction with a low-level controller that resides within the implantable device. The device has the capabilities of forecasting brain disturbances, controlling the disturbances, or both. Forecasting is achieved by indicating the probability of an oncoming seizure within one or more time frames, which is accomplished through an inner-loop control law and a feedback necessary to prevent or control the neurological event by either electrical, chemical, cognitive, sensory, and/or magnetic stimulation.
摘要翻译：一种用于预测和控制人类神经系统异常的自适应方法和装置，例如癫痫发作或其他大脑紊乱。该系统基于多层次的控制策略。使用作为输入的一种或多种类型的生理测量，例如脑电，化学或磁性活动，心率，瞳孔扩张，眼睛运动，温度，某些物质的化学浓度，特征集是从预编程的离线特征库包含在监控控制架构中的高级别控制器中。该高级控制器将功能库存储在笔记本电脑或外部PC中。监督控制还包含一个知识库，它以离散的步骤连续更新，反馈信息来自可实现选定特征集（特征向量）的可植入装置。该高级控制器还通过包含知识的智能过程，通过外部控制环路建立初始系统设置（离线）和后续设置（在线）或调谐。系统的后续自适应设置与驻留在可植入装置内的低级别控制器一起确定。该装置具有预测大脑紊乱，控制干扰或两者兼有的能力。通过指示在一个或多个时间范围内即将到来的癫痫发作的概率来实现预测，该概率通过内环控制规律和通过电学，化学，认知，感觉和/或功能来预防或控制神经学事件所必需的反馈 /或磁刺激。

3. 发明授权

US06594524B2 Adaptive method and apparatus for forecasting and controlling neurological disturbances under a multi-level control 有权
公开(公告)号：US06594524B2
公开(公告)日：2003-07-15
申请号：US09735364
申请日：2000-12-12
申请人： Rosana Esteller , Javier Ramón Echauz , Brian Litt , George John Vachtsevanos
发明人： Rosana Esteller , Javier Ramón Echauz , Brian Litt , George John Vachtsevanos
IPC分类号： A61N118
CPC分类号： A61B5/076 , A61B5/0476 , A61B5/0482 , A61B5/4094 , A61B5/486 , A61B5/7203 , A61B5/726 , A61B5/7264 , A61B5/7267 , A61B5/7275 , A61N1/08 , A61N1/36082 , G06F19/00 , G06K9/00523
摘要： A method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programmed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented. This high level controller also establishes the initial system settings (off-line) and subsequent settings (on-line) or tunings through an outer control loop by an intelligent procedure that incorporates knowledge as it arises. The subsequent adaptive settings for the system are determined in conjunction with a low-level controller that resides within the implantable device. The device has the capabilities of forecasting brain disturbances, controlling the disturbances, or both. Forecasting is achieved by indicating the probability of an oncoming seizure within one or more time frames, which is accomplished through an inner-loop control law and a feedback necessary to prevent or control the neurological event by either electrical, chemical, cognitive, sensory, and/or magnetic stimulation.

4. 发明授权

US08086294B2 Unified probabilistic framework for predicting and detecting seizure onsets in the brain and multitherapeutic device 有权
标题翻译：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
公开(公告)号：US08086294B2
公开(公告)日：2011-12-27
申请号：US11837814
申请日：2007-08-13
申请人： Javier Ramón Echauz , Brian Litt , Rosana Esteller , George John Vachtsevanos
发明人： Javier Ramón Echauz , Brian Litt , Rosana Esteller , George John Vachtsevanos
IPC分类号： A61B5/04 , G01N33/48 , G01N31/00
CPC分类号： A61B5/7267 , A61B5/0476 , A61B5/076 , A61B5/4094 , A61B5/7275 , A61N1/08 , A61N1/36017 , A61N1/36064 , A61N1/36082 , A61N1/36135 , G06F19/00 , G06F19/3456 , G06F19/3481 , G06K9/6262 , G06K9/627 , G06K9/6278 , G16H50/20 , G16H50/50
摘要： A method and system for assessing a quality of life index to adjust an implanted device to optimize patient-specific feature signals and treatment therapies. Accumulated energy of intracranial electroencephalogram (IEEG) signals is calculated over multiple data channels during seizures over a fixed time period. Accumulated energy of a treatment control is calculated over the multiple data channels over all times of activation of the implanted device over the fixed time period. The accumulated energy of both the IEEG signals and treatment control are weighted by seizure and treatment factors to determine a quality value for the fixed time period. A quality of life index is determined as a weighted average of current and previous quality values for a plurality of fixed time periods.
摘要翻译：一种用于评估生活质量指数以调整植入装置以优化患者特异性特征信号和治疗疗法的方法和系统。在固定时间段内癫痫发作期间，通过多个数据通道计算颅内脑电图（IEEG）信号的累积能量。在固定时间段内在植入装置的所有激活时间内，通过多个数据通道计算处理控制的累积能量。 IEEG信号和治疗控制的累积能量通过扣押和处理因子加权，以确定固定时间段的质量值。生活质量指数被确定为多个固定时间段的当前和先前质量值的加权平均值。

5. 发明授权

US07146218B2 Adaptive method and apparatus for forecasting and controlling neurological disturbances under a multi-level control 有权
公开(公告)号：US07146218B2
公开(公告)日：2006-12-05
申请号：US10358039
申请日：2003-02-04
申请人： Rosana Esteller , Javier Ramón Echauz , Brian Litt , George John Vachtsevanos
发明人： Rosana Esteller , Javier Ramón Echauz , Brian Litt , George John Vachtsevanos
IPC分类号： A61N1/18 , A61B5/02
CPC分类号： A61B5/076 , A61B5/0476 , A61B5/0482 , A61B5/4094 , A61B5/486 , A61B5/7203 , A61B5/726 , A61B5/7264 , A61B5/7267 , A61B5/7275 , A61N1/08 , A61N1/36082 , G06F19/00 , G06K9/00523
摘要： A method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programmed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented. This high level controller also establishes the initial system settings (off-line) and subsequent settings (on-line) or tunings through an outer control loop by an intelligent procedure that incorporates knowledge as it arises. The subsequent adaptive settings for the system are determined in conjunction with a low-level controller that resides within the implantable device. The device has the capabilities of forecasting brain disturbances, controlling the disturbances, or both. Forecasting is achieved by indicating the probability of an oncoming seizure within one or more time frames, which is accomplished through an inner-loop control law and a feedback necessary to prevent or control the neurological event by either electrical, chemical, cognitive, sensory, and/or magnetic stimulation.

6. 发明授权

US06678548B1 Unified probabilistic framework for predicting and detecting seizure onsets in the brain and multitherapeutic device 有权
标题翻译：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
公开(公告)号：US06678548B1
公开(公告)日：2004-01-13
申请号：US09693423
申请日：2000-10-20
申请人： Javier Ramón Echauz , Rosana Esteller , Brian Litt , George John Vachtsevanos
发明人： Javier Ramón Echauz , Rosana Esteller , Brian Litt , George John Vachtsevanos
IPC分类号： A61B504
CPC分类号： A61B5/7267 , A61B5/0476 , A61B5/076 , A61B5/4094 , A61B5/7275 , A61N1/08 , A61N1/36017 , A61N1/36064 , A61N1/36082 , A61N1/36135 , G06F19/00 , G06F19/3456 , G06F19/3481 , G06K9/6262 , G06K9/627 , G06K9/6278 , G16H50/20 , G16H50/50
摘要： 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.
摘要翻译：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。

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