HRV in an Integrated Hardware/Software System Using Artificial Intelligence to Provide Assessment, Intervention and Performance Optimization

Robert L. Drury
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引用次数: 2

Abstract

Heart rate variability (HRV) is increasingly recognized as a central variable of interest in health maintenance, disease prevention and performance optimization. It is also a sensitive biomarker of health status, disease presence and functional abilities, acquiring and processing high fidelity inter beat interval data, along with other psychophysiological parameters that can assist in clinical assessment and intervention, population health studies/digital epidemiology and positive performance optimization. We describe a system using high-throughput artificial intelligence based on the KUBIOS platform to combine time, frequency and nonlinear data domains acquired by wearable or implanted biosensors to guide in clinical assessment, decision support and intervention, population health monitoring and individual self-regulation and performance enhancement, including the use of HRV biofeedback. This approach follows the iP4 health model which emphasizes an integral, personalized, predictive, preventive and participatory approach to human health and well-being. It therefore includes psychological, biological, genomic, sociocultural, evolutionary and spiritual variables as mutually interactive elements in embodying complex systems adaptation.
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基于人工智能的HRV综合软硬件系统评估、干预和性能优化
心率变异性(HRV)越来越被认为是健康维护、疾病预防和性能优化的中心变量。它也是健康状况、疾病存在和功能能力的敏感生物标志物,可以获取和处理高保真的搏动间隔数据,以及其他心理生理参数,有助于临床评估和干预、人口健康研究/数字流行病学和积极的性能优化。我们描述了一个基于KUBIOS平台的高通量人工智能系统,该系统将可穿戴或植入生物传感器获取的时间、频率和非线性数据域结合起来,指导临床评估、决策支持和干预、人群健康监测以及个人自我调节和绩效提高,包括使用HRV生物反馈。这一方法遵循iP4卫生模式,该模式强调对人类健康和福祉采取综合、个性化、预测性、预防性和参与性方法。因此,它包括心理、生物、基因组、社会文化、进化和精神变量,作为体现复杂系统适应的相互作用因素。
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