[Quantitative analysis of breathing patterns based on wearable systems]

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Oct 25;38(5):893-902. doi: 10.7507/1001-5515.202004047.
[Article in Chinese]

Abstract

Breathing pattern parameters refer to the characteristic pattern parameters of respiratory movements, including the breathing amplitude and cycle, chest and abdomen contribution, coordination, etc. It is of great importance to analyze the breathing pattern parameters quantificationally when exploring the pathophysiological variations of breathing and providing instructions on pulmonary rehabilitation training. Our study provided detailed method to quantify breathing pattern parameters including respiratory rate, inspiratory time, expiratory time, inspiratory time proportion, tidal volume, chest respiratory contribution ratio, thoracoabdominal phase difference and peak inspiratory flow. We also brought in "respiratory signal quality index" to deal with the quality evaluation and quantification analysis of long-term thoracic-abdominal respiratory movement signal recorded, and proposed the way of analyzing the variance of breathing pattern parameters. On this basis, we collected chest and abdomen respiratory movement signals in 23 chronic obstructive pulmonary disease (COPD) patients and 22 normal pulmonary function subjects under spontaneous state in a 15 minute-interval using portable cardio-pulmonary monitoring system. We then quantified subjects' breathing pattern parameters and variability. The results showed great difference between the COPD patients and the controls in terms of respiratory rate, inspiratory time, expiratory time, thoracoabdominal phase difference and peak inspiratory flow. COPD patients also showed greater variance of breathing pattern parameters than the controls, and unsynchronized thoracic-abdominal movements were even observed among several patients. Therefore, the quantification and analyzing method of breathing pattern parameters based on the portable cardiopulmonary parameters monitoring system might assist the diagnosis and assessment of respiratory system diseases and hopefully provide new parameters and indexes for monitoring the physical status of patients with cardiopulmonary disease.

呼吸模式参数是指呼吸运动的特征模式参数,包括幅度、周期、胸腹贡献度、协调性等。呼吸模式参数的量化分析对于研究呼吸系统的生理病理变化和指导肺康复训练具有重要价值。本文给出了呼吸模式参数量化方法,包括潮气量、呼吸率、吸气时间、呼气时间、吸气时间分数、胸呼吸贡献比、胸腹相位差、峰值吸气气流等。本文引入呼吸信号质量指数来解决长时间记录的胸腹呼吸运动信号质量评价和量化分析问题,并提出了呼吸模式参数变异性的分析方法。在此基础上,使用穿戴式心肺生理参数监测系统采集了 23 名慢性阻塞性肺疾病(COPD)患者与 22 名肺功能正常者的 15 分钟自主呼吸状态下的胸腹呼吸运动信号,对呼吸模式参数及其变异性进行了量化分析。结果表明,COPD 患者和肺功能正常者在呼吸频率、吸气时间、呼气时间、胸腹相位差、峰值吸气气流这五项参数上的差异有统计学意义,COPD 患者呼吸模式参数的变异性要大于肺功能正常者,部分患者出现明显的胸腹不同步现象。基于穿戴式心肺生理参数监测系统的呼吸模式参数量化分析有望为呼吸系统疾病的诊断评估提供新的辅助决策支持信息,为心肺疾病患者健康状态监测提供新的参数和指标。.

Keywords: breathing pattern; chronic obstructive pulmonary disease; respiratory inductive plethysmography; signal quality; wearable system.

MeSH terms

  • Humans
  • Lung
  • Pulmonary Disease, Chronic Obstructive*
  • Respiration
  • Tidal Volume
  • Wearable Electronic Devices*

Grants and funding

国家自然科学基金面上项目(61471398);北京市科委医药协同科技创新研究(Z181100001918023);解放军总医院大数据研发项目(2018MBD-009)