Fatigue Detection Using Artificial Intelligence Framework

Vidhi Parekh, Darshan Shah, Manan Shah
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引用次数: 53

Abstract

Technological advances in healthcare have saved innumerable patients and are continuously improving our quality of life. Fatigue among health indicators of individuals has become significant due to its association with cognitive performance and health outcomes and, is one of the major factors contributing to the degradation of performance in daily life. This review serves as a source of studies which helped in better understanding of fatigue and also gave significant detection methods and systematic approaches to figure out the impacts and causes of fatigue. Artificial intelligence was turned out to be one of the essential tactics to detect or monitor fatigue. Artificial neural network, wavelet transform, data analysis of mouse interaction and keyboard patterns, image analysis, kernel learning algorithms, relation of fatigue and anxiety, and heart rate data examination studies were used in this paper to precisely assess the source, factors and features which influenced the recognition of fatigue.

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基于人工智能框架的疲劳检测
医疗保健的技术进步拯救了无数患者,并不断提高我们的生活质量。由于疲劳与认知表现和健康结果有关,个体健康指标中的疲劳已变得显著,是导致日常生活表现下降的主要因素之一。这篇综述是有助于更好地理解疲劳的研究来源,也为找出疲劳的影响和原因提供了重要的检测方法和系统方法。人工智能被证明是检测或监测疲劳的基本策略之一。本文运用人工神经网络、小波变换、鼠标交互和键盘模式的数据分析、图像分析、核学习算法、疲劳与焦虑的关系以及心率数据检测研究,准确评估了影响疲劳识别的来源、因素和特征。
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