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首页> 外文会议>Proceedings of the 17th IASTED international conference on robotics applications ; Proceedings of the 11th IASTED international conference on biomedical engineering >LYING POSTURE DETECTION FOR UNCONSTRAINED MEASUREMENT OF RESPIRATION AND HEARTBEAT ON A BED
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LYING POSTURE DETECTION FOR UNCONSTRAINED MEASUREMENT OF RESPIRATION AND HEARTBEAT ON A BED

机译：卧姿检测，可无限制地测量床上的呼吸和心跳

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摘要

Daily monitoring of respiration and heartbeat while sleeping provides basic data for the assessment of personal health and early detection of diseases. The monitoring should not interfere with natural sleep, and it is desirable that the sensor be imperceptible to the person being measured. We propose a method for non-invasive and unconstrained measurement of the lying posture, respiration and heartbeat of a person on a rubber-based tactile sensor sheet. The tactile sensor is soft, flexible, and thin, and is not uncomfortable for the person lying on it. To extract faint heartbeat signals from pressure changes detected by the sensor, precision measurement based on improvement of the S/N ratio by averaging oversampled data is needed. This process takes some time and can be performed at only a limited number of locations on the sensor. To determine the locations, we detect the lying location and posture of the measured person on the sensor by using pattern recognition based on machine learning. In this paper, we describe the measurement method and report the experimental results.
机译：每天在睡眠时监测呼吸和心跳可为评估个人健康和早期发现疾病提供基本数据。监视不应干扰自然睡眠，并且希望传感器对被测者不敏感。我们提出了一种基于橡胶的触觉传感器板上的人的躺卧姿势，呼吸和心跳的无创且不受约束的测量方法。触觉传感器柔软，灵活，薄且对躺在它上面的人来说并不感到不适。为了从传感器检测到的压力变化中提取微弱的心跳信号，需要通过平均过采样数据来提高信噪比来进行精确测量。该过程需要一些时间，并且只能在传感器上的有限数量的位置上执行。为了确定位置，我们通过使用基于机器学习的模式识别来检测被测人在传感器上的躺卧位置和姿势。在本文中，我们描述了测量方法并报告了实验结果。

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