FLEXIBLE AND SCALABLE SENSOR ARRAYS FOR RECORDING AND MODULATING PHYSIOLOGIC ACTIVITY
    5.
    发明授权
    FLEXIBLE AND SCALABLE SENSOR ARRAYS FOR RECORDING AND MODULATING PHYSIOLOGIC ACTIVITY 有权
    灵活的SKALIERBARE SENSORANORDNUNGEN ZUR AUFZEICHNUNG UND MODULATION VON生理学家AKTIVITÄT

    公开(公告)号:EP2265171B1

    公开(公告)日:2016-03-09

    申请号:EP09721084.3

    申请日:2009-03-12

    IPC分类号: A61B5/04

    摘要: An implantable sensor array incorporates active electronic elements to greatly increase the number of sensors and their density that can be simultaneously recorded and activated. The sensors can be of various configurations and types, for example: optical, chemical, temperature, pressure or other sensors including effectors for applying signals to surrounding tissues. The sensors/effectors are arranged on a flexible and stretchable substrate with incorporated active components that allow the effective size, configuration, number and pattern of sensors/effectors to be dynamically changed, as needed, through a wired or wireless means of communication. Active processing allows many channels to be combined either through analog or digital means such that the number of wires exiting the array can be substantially reduced compared to the number of sensors/effectors on the array.

    摘要翻译: 可植入传感器阵列包含有源电子元件,可大大增加可同时记录和激活的传感器数量及其密度。 传感器可以具有各种配置和类型,例如:光学,化学,温度,压力或其它传感器,包括用于向周围组织施加信号的效应器。 传感器/效应器布置在柔性和可拉伸的基板上,并具有结合的有源部件,其允许根据需要通过有线或无线通信方式动态地改变传感器/效应器的有效尺寸,配置,数量和图案。 有源处理允许通过模拟或数字装置组合许多通道,使得与阵列上的传感器/效应器的数量相比,离开阵列的导线的数量可以显着减少。

    ADAPTIVE METHOD AND APPARATUS FOR FORECASTING AND CONTROLLING NEUROLOGICAL DISTURBANCES UNDER A MULTI-LEVEL CONTROL
    8.
    发明公开
    ADAPTIVE METHOD AND APPARATUS FOR FORECASTING AND CONTROLLING NEUROLOGICAL DISTURBANCES UNDER A MULTI-LEVEL CONTROL 审中-公开
    FOR预测与多级控制神经系统疾病控制的自适应方法和装置

    公开(公告)号:EP1341580A2

    公开(公告)日:2003-09-10

    申请号:EP01993260.7

    申请日:2001-12-11

    IPC分类号: A61N1/18

    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.