利用无线声学传感器的气管音频记录在睡眠期间自动检测心率

Automatic Heart Rate Detection during Sleep Using Tracheal Audio Recordings from Wireless Acoustic Sensor.

作者信息

Tomaszewska Julia Zofia, Młyńczak Marcel, Georgakis Apostolos, Chousidis Christos, Ładogórska Magdalena, Kukwa Wojciech

机构信息

School of Computing and Engineering, University of West London, London W5 5RF, UK.

Institute of Metrology and Biomedical Engineering, Faculty of Mechatronics, Warsaw University of Technology, 02-525 Warsaw, Poland.

出版信息

Diagnostics (Basel). 2023 Sep 11;13(18):2914. doi: 10.3390/diagnostics13182914.

DOI:10.3390/diagnostics13182914

PMID:37761281

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10529205/

Abstract

BACKGROUND

Heart rate is an essential diagnostic parameter indicating a patient's condition. The assessment of heart rate is also a crucial parameter in the diagnostics of various sleep disorders, including sleep apnoea, as well as sleep/wake pattern analysis. It is usually measured using an electrocardiograph (ECG)-a device monitoring the electrical activity of the heart using several electrodes attached to a patient's upper body-or photoplethysmography (PPG).

METHODS

The following paper investigates an alternative method for heart rate detection and monitoring that operates on tracheal audio recordings. Datasets for this research were obtained from six participants along with ECG Holter (for validation), as well as from fifty participants undergoing a full night polysomnography testing, during which both heart rate measurements and audio recordings were acquired.

RESULTS

The presented method implements a digital filtering and peak detection algorithm applied to audio recordings obtained with a wireless sensor using a contact microphone attached in the suprasternal notch. The system was validated using ECG Holter data, achieving over 92% accuracy. Furthermore, the proposed algorithm was evaluated against whole-night polysomnography-derived HR using Bland-Altman's plots and Pearson's Correlation Coefficient, reaching the average of 0.82 (0.93 maximum) with 0 BPM error tolerance and 0.89 (0.97 maximum) at ±3 BPM.

CONCLUSIONS

The results prove that the proposed system serves the purpose of a precise heart rate monitoring tool that can conveniently assess HR during sleep as a part of a home-based sleep disorder diagnostics process.

摘要

背景

心率是指示患者病情的重要诊断参数。心率评估也是各种睡眠障碍（包括睡眠呼吸暂停）诊断以及睡眠/觉醒模式分析中的关键参数。通常使用心电图仪（ECG）进行测量，该设备通过连接到患者上身的多个电极来监测心脏的电活动，或者使用光电容积脉搏波描记法（PPG）进行测量。

方法

以下论文研究了一种基于气管录音进行心率检测和监测的替代方法。本研究的数据集来自六名参与者以及心电图动态监测仪（用于验证），还有五十名接受整夜多导睡眠图测试的参与者，在此期间获取了心率测量值和录音。

结果

所提出的方法实现了一种数字滤波和峰值检测算法，该算法应用于通过无线传感器使用附着在胸骨上切迹的接触式麦克风获得的录音。该系统使用心电图动态监测仪数据进行了验证，准确率超过92%。此外，使用布兰德-奥特曼图和皮尔逊相关系数，将所提出的算法与整夜多导睡眠图得出的心率进行了评估，在0次/分钟误差容限下平均达到0.82（最大值为0.93），在±3次/分钟时平均达到0.89（最大值为0.97）。