会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 33. 发明授权
    • PATIENT STATE DETECTION BASED ON SUPPORT VECTOR MACHINE BASED ALGORITHM
    • ERKENNUNG EINES PATITENTENZUSTANUSTAS NEC EINEM ALGORITHMUS AUF DER BASIS EINER SUPPTOR-VECTOR-MASCHINE
    • EP2429644B1
    • 2017-05-31
    • EP10702192.5
    • 2010-01-26
    • Medtronic, Inc.
    • CARLSON, David, L.DENISON, Timothy, J.SHOEB, Ali, H.
    • A61N1/36G06N99/00G06K9/62G06F19/00
    • A61N1/36082G06F2221/2101G06F2221/2105G06K9/6268G06N99/005G16H50/50
    • A patient state is detected with at least one classification boundary generated by a supervised machine learning technique, such as a support vector machine. The patient state can be, for example, a patient posture state. In some examples, the patient state detection is used to at least one of control the delivery of therapy to a patient, to generate a patient notification, to initiate data recording, or to evaluate a patient condition. In addition, an evaluation metric can be determined based on a feature vector, which is determined based on characteristics of a patient parameter signal, and the classification boundary. Example evaluation metrics can be based on a distance between at least one feature vector and the classification boundary and/or a trajectory of a plurality of feature vectors relative to the classification boundary over time.
    • 用监督机器学习技术(例如支持向量机)产生的至少一个分类边界来检测患者状态。 患者状态可以是例如患者姿势状态。 在一些示例中,患者状态检测用于控制对患者的治疗递送,产生患者通知,启动数据记录或评估患者状况中的至少一个。 此外,可以基于基于患者参数信号的特性确定的特征向量和分类边界来确定评估度量。 示例评估度量可以基于至少一个特征向量与分类边界之间的距离和/或相对于分类边界随时间的多个特征向量的轨迹。
    • 37. 发明公开
    • METHOD AND APPARATUS FOR DETECTION OF NERVOUS SYSTEM DISORDERS
    • 用于检测神经系统病症的方法和装置
    • EP2012659A2
    • 2009-01-14
    • EP07811786.8
    • 2007-01-26
    • MEDTRONIC, INC.
    • CARLSON, David, L.PANKEN, Eric, J.GIFTAKIS, Jonathon, E.
    • A61B5/00
    • A61B5/04012A61B5/0476A61B5/048A61B5/4094A61B5/7275A61N1/36082G06F19/00
    • Systems and methods for detecting and/or treating nervous system disorders, such as seizures, are disclosed. Certain embodiments of the invention relate generally to implantable medical devices (IMDs) adapted to detect and treat nervous system disorders in patients with an IMD. Certain embodiments of the invention include detection of seizures based upon comparisons of long-term and short-term representations of physiological signals. Other embodiments include prediction of seizure activity based upon analysis of physiological signal levels. An embodiment of the invention monitors the quality of physiological signals, and may be able to compensate for signals of low signal quality. A further embodiment of the invention includes detection of seizure activity following the delivery of therapy.
    • 公开了用于检测和/或治疗神经系统疾病例如癫痫发作的系统和方法。 本发明的某些实施例总体上涉及适用于检测和治疗IMD患者的神经系统病症的可植入医疗装置(IMD)。 本发明的某些实施例包括基于生理信号的长期和短期表示的比较来检测癫痫发作。 其他实施例包括基于生理信号水平的分析预测癫痫发作活动。 本发明的实施例监测生理信号的质量,并且可能能够补偿低信号质量的信号。 本发明的另一个实施方案包括在递送治疗后检测癫痫发作活动。