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PATIENT STATE DETECTION BASED ON SUPPORT VECTOR MACHINE BASED ALGORITHM
PATIENT STATE DETECTION BASED ON SUPPORT VECTOR MACHINE BASED ALGORITHM
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机译:基于支持向量机算法的患者状态检测
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摘要
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.
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