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传感器信号的时间分析与分类。

Temporal Analysis and Classification of Sensor Signals.

机构信息

Institute of Information Systems, Military University of Technology, 00-908 Warsaw, Poland.

出版信息

Sensors (Basel). 2023 Mar 10;23(6):3017. doi: 10.3390/s23063017.

Abstract

Understanding the behaviour of sensors, and in particular, the specifications of multisensor systems, are complex problems. The variables that need to be taken into consideration include, inter alia, the application domain, the way sensors are used, and their architectures. Various models, algorithms, and technologies have been designed to achieve this goal. In this paper, a new interval logic, referred to as Duration Calculus for Functions (DC4F), is applied to precisely specify signals originating from sensors, in particular sensors and devices used in heart rhythm monitoring procedures, such as electrocardiograms. Precision is the key issue in case of safety critical system specification. DC4F is a natural extension of the well-known Duration Calculus, an interval temporal logic used for specifying the duration of a process. It is suitable for describing complex, interval-dependent behaviours. Said approach allows one to specify temporal series, describe complex interval-dependent behaviours, and evaluate the corresponding data within a unifying logical framework. The use of DC4F allows one, on the one hand, to precisely specify the behaviour of functions modelling signals generated by different sensors and devices. Such specifications can be used for classifying signals, functions, and diagrams; and for identifying normal and abnormal behaviours. On the other hand, it allows one to formulate and frame a hypothesis. This is a significant advantage over machine learning algorithms, since the latter are capable of learning different patterns but fail to allow the user to specify the behaviour of interest.

摘要

理解传感器的行为,特别是多传感器系统的规格,是一个复杂的问题。需要考虑的变量包括应用领域、传感器的使用方式以及它们的架构。已经设计了各种模型、算法和技术来实现这一目标。在本文中,一种新的区间逻辑,称为函数持续时间演算(Duration Calculus for Functions,简称 DC4F),被应用于精确指定来自传感器的信号,特别是用于监测心脏节律的传感器和设备(如心电图)产生的信号。在安全关键系统规范的情况下,精度是关键问题。DC4F 是著名的持续时间演算(Interval Temporal Logic,用于指定过程持续时间的区间时间逻辑)的自然扩展。它适用于描述复杂的、区间相关的行为。这种方法允许人们指定时间序列、描述复杂的区间相关行为,并在统一的逻辑框架内评估相应的数据。使用 DC4F,一方面可以精确指定用于对不同传感器和设备生成的信号建模的函数的行为。这些规范可用于对信号、函数和图表进行分类,并识别正常和异常行为。另一方面,它允许人们提出和构造一个假设。这是一个显著的优势,因为机器学习算法虽然能够学习不同的模式,但却无法让用户指定感兴趣的行为。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7390/10052952/8ceba52617ac/sensors-23-03017-g001.jpg

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