Wang Sikai, Liu Ming, Pang Bo, Li Peng, Yao Zhaolin, Zhang Xu, Chen Hongda
Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:441-444. doi: 10.1109/EMBC.2018.8512427.
In a gradually aging society, families and hospitals have a growing demand for reliable and unobtrusive physiological signal monitoring for elderly people. However, the existing respiration rate monitoring methods and algorithms are still unsatisfactory. In this work, we introduce a physiological signal acquisition patch which integrates 3-axis accelerator and 3-axis gyroscope to estimate respiration rate, as well as ECG(electrocardiogram) sensor and surface temperature sensor. A complete set of respiration rate estimation algorithms is embedded in our patch, which can be used to identify whether the patch is worn or not, and to recognize, segment, de-noise and reconstruct the respiration signal. In-situ experiments have been conducted to prove the validity of the algorithms described in this paper and the possibilities of estimating respiration rate using a physiological signal acquisition patch. The mean absolute error (MAE) is 0.11(about ±0.7 times in a minute), which is the least among similar studies that acquire respiratory rate from 3-axis accelerators or electrocardiogram.
在社会逐渐老龄化的背景下,家庭和医院对老年人可靠且不引人注意的生理信号监测需求日益增长。然而,现有的呼吸率监测方法和算法仍不尽人意。在这项工作中,我们推出了一种生理信号采集贴片,它集成了三轴加速度计和三轴陀螺仪来估计呼吸率,以及心电图(ECG)传感器和表面温度传感器。我们的贴片嵌入了一套完整的呼吸率估计算法,可用于识别贴片是否佩戴,以及对呼吸信号进行识别、分段、去噪和重构。已进行的现场实验证明了本文所述算法的有效性以及使用生理信号采集贴片估计呼吸率的可能性。平均绝对误差(MAE)为0.11(每分钟约±0.7次),这在从三轴加速度计或心电图获取呼吸率的类似研究中是最小的。