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[1]刘爽黄婧琳许昌张婧黄文蒂匡薇梁真.智能呼吸训练联合云服务在慢性阻塞性肺疾病患者中的应用效果研究[J].中国卫生质量管理,2026,33(7):25-30.[doi:10.13912/j.cnki.chqm.2026.33.7.05]
　LIU Shuang,HUANG Jinglin,XU Chang.Research on the Application Effects of Intelligent Breathing Training Combined with Cloud Services in Patients with Chronic Obstructive Pulmonary Disease[J].Chinese Health Quality Management,2026,33(7):25-30.[doi:10.13912/j.cnki.chqm.2026.33.7.05]

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智能呼吸训练联合云服务在慢性阻塞性肺疾病患者中的应用效果研究

《中国卫生质量管理》[ISSN:1006-7515/CN:CN 61-1283/R] 卷: 33 期数: 2026年7期页码: 25-30 栏目: 特别关注出版日期: 2026-07-15

Title:: Research on the Application Effects of Intelligent Breathing Training Combined with Cloud Services in Patients with Chronic Obstructive Pulmonary Disease

作者:: 刘爽黄婧琳许昌张婧黄文蒂匡薇梁真; 北京大学深圳医院

Author(s):: LIU Shuang; HUANG Jinglin; XU Chang; Peking University Shenzhen Hospital

关键词:: 慢性阻塞性肺疾病; 智能呼吸训练; 可穿戴设备; 肺康复; 云服务

Keywords:: Chronic Obstructive Pulmonary Disease; Intelligent Breathing Training; Wearable Devices; Pulmonary Rehabilitation; Cloud Services

分类号:: R47

DOI:: 10.13912/j.cnki.chqm.2026.33.7.05

文献标志码:: B

摘要:: 目的探讨智能呼吸模式优化训练系统联合云服务应用于慢性阻塞性肺疾病（COPD）患者的呼吸训练效果。方法构建智能呼吸训练联合云服务呼吸康复管理模式，采用前瞻性类实验研究验证其相较于传统训练的康复效果。结果干预组肺功能改善显著，胸腹呼吸相位差从（28.5±5.2）°降至（15.3±3.8）°，第一秒用力呼气容积（FEV1）、用力肺活量（FVC）分别提升0.24 L、0.26 L，FEV1/FVC提高3.9百分点；6 min步行距离（6MWD）延长42.7 m，基础性日常生活活动（BADL）评分提高12分，呼吸困难量表（mMRC）分级降低0.5级，COPD评估测试（CAT）评分下降3.6分。多因素分析显示，智能呼吸训练是肺功能改善的独立保护因素［OR=2.15，95%CI（1.32-3.51）］。结论智能呼吸训练联合云服务呼吸康复管理模式通过呼吸力学监测与云平台的深度融合，构建了“监测-评估-管理”全周期闭环，实现了COPD呼吸康复从经验驱动向数据驱动的范式转换。

Abstract:: ObjectiveTo explore the effect of an intelligent breathing pattern optimization training system combined with cloud services on respiratory training in patients with chronic obstructive pulmonary disease (COPD). MethodsAn intelligent breathing training combined with cloud service-based pulmonary rehabilitation management model was constructed, and a prospective quasi-experimental study was conducted to verify its rehabilitation effects compared with conventional training.ResultsThe intervention group showed significant improvements in pulmonary function. The thoracoabdominal breathing phase difference decreased from (28.5 ± 5.2)° to (15.3 ± 3.8)°; FEV1 and FVC increased by 0.24 L and 0.26 L, respectively; FEV1/FVC improved by 3.9%. The 6-minute walk distance (6MWD) increased by 42.7 m, the Barthel Activities of Daily Living (BADL) score improved by 12 points, the modified Medical Research Council (mMRC) grade decreased by 0.5 levels, and the COPD Assessment Test (CAT) score decreased by 3.6 points. Multivariate analysis revealed that intelligent breathing training was an independent protective factor for pulmonary function improvement ［OR = 2.15, 95% CI:（1.32-3.51）］.Conclusion The intelligent breathing training combined with cloud service-based pulmonary rehabilitation management model, through the deep integration of respiratory mechanics monitoring and cloud platform, constructs a full-cycle closed loop of "monitoring-assessment-management", realizing a paradigm shift in COPD pulmonary rehabilitation from experience-driven to data-driven.

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更新日期/Last Update: 2026-07-15