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Breathing signal combining for respiration rate estimation in smart beds

机译:呼吸信号组合用于智能病床的呼吸速率估计

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One of the non-invasive ways to measure respiratory effort is in-bed pressure sensor arrays. Based on the area of the bed and the sensor array covered by a patient's body, some sensors may not include significant respiratory effort components or may have low signal to noise ratios. When combining signals from the different sensors, this can produce a low quality output signal. Signal combiners can overcome this problem. This paper describes two different methods of signal combining to achieve a good estimation of the respiratory rate and the respiratory signal itself. To assess the performance, a participant was asked to lay on the bed in supine position while having normal breathing. Our results indicate that both methods can perform very satisfactorily when compared to a gold standard signal, and that they can outperform some previously published methods.
机译:床内压力传感器阵列是测量呼吸作用的一种非侵入性方法。根据床的面积和患者身体覆盖的传感器阵列,某些传感器可能不包括大量的呼吸作用成分,或者信噪比可能较低。当组合来自不同传感器的信号时,这会产生低质量的输出信号。信号组合器可以解决此问题。本文介绍了两种不同的信号组合方法,可以很好地估计呼吸频率和呼吸信号本身。为了评估表现,要求参与者正常呼吸时仰卧躺在床上。我们的结果表明,与金标准信号相比,这两种方法的性能都非常令人满意,并且它们的性能可能优于某些以前发布的方法。

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