颗粒过滤器
光容积图
计算机科学
功率(物理)
计算复杂性理论
粒子(生态学)
辅助粒子过滤器
滤波器(信号处理)
电子工程
实时计算
人工智能
算法
工程类
计算机视觉
卡尔曼滤波器
物理
海洋学
集合卡尔曼滤波器
地质学
量子力学
扩展卡尔曼滤波器
作者
Ali Akbari,Roozbeh Jafari
标识
DOI:10.1109/islped52811.2021.9502471
摘要
This article describes a novel methodology to balance computational power and estimation accuracy for the application of robust heartrate (HR) monitoring through leveraging particle filters. We formulate the power-accuracy trade-off as the number of particles in the particle filter framework, where a higher number of particles leads to higher computational resolution and accuracy at the cost of higher computational power. Our particle filter-based HR monitoring technique can be applied to a variety of physiological signals including but not limited to electrocardiogram (ECG) and photoplethysmogram (PPG).
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