A Non-invasive, Wearable, Miniaturized Auscultation Device for Diagnosis of Pulmonary Diseases

用于诊断肺部疾病的无创、可穿戴、小型听诊装置

• 批准号: 10261583
• 负责人: Farrokh Ayazi
• 金额: $ 7.55万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10261583
• 关键词: Accelerometer; Acoustics; Age; Air Sacs; Algorithmic Analysis; Algorithms; Ambulatory Monitoring; Asthma; Auscultation; Blood flow; Body mass index; Cardiac; Cardiopulmonary; Cardiovascular system; Cause of Death; Cessation of life; Chest wall structure; Child; Chronic Obstructive Airway Disease; Clinic; Clinical; Cone; Consumption; Coupling; Crackles; Dangerousness; Data; Dependence; Detection; Development; Devices; Diagnosis; Diagnostic; Diagnostic Procedure; Disease; Disease Progression; Early Diagnosis; Entropy; Erythema Infectiosum; Evaluation; Frequencies; Future; Goals; Health; Health Care Costs; Health Status; Healthcare Systems; Heart; Heart Rate; Heart Sounds; Home; Immune; Income; Individual; Judgment; Life; Liquid substance; Lung; Lung diseases; Maps; Measurement; Medical; Methods; Microgravity; Monitor; Motion; Noise; Organ; Outpatients; Output; Particulate; Patients; Physical activity; Physicians; Pneumonia; Population; Positioning Attribute; Preventive care; Preventive screening; Preventive treatment; Progressive Disease; Pulmonary Fibrosis; Pus; Quantitative Evaluations; Reading; Respiratory Sounds; Respiratory System; Running; Sampling; Schools; Signal Transduction; Skin; Stethoscopes; Structure; Surface; Symptoms; Testing; Time; Veins; Visit; Walking; Wheezing; Work; asthma exacerbation; asthmatic patient; base; body position; cardiopulmonary system; clinical Diagnosis; cost; design; detection method; diagnostic accuracy; digital; disability; disorder risk; effective therapy; electric impedance; experience; health care settings; heart rate monitor; improved; interstitial; lung injury; microdevice; microphone; miniaturize; nanofabrication; noninvasive diagnosis; personalized diagnostics; portability; prevent; prototype; reduce symptoms; respiratory; screening; seal; sensor; skills; sound; tobacco exposure; tool; vibration

Summary: Respiratory diseases (RDs) are the fifth cause of death in the US and impose over $150B on healthcare cost. RDs like asthma are incurable and can be life-threatening if not treated promptly. As most dangerous RDs are progressive and manageable with preventive treatment, early detection is crucial to prevent exacerbation. Current diagnosis relies on costly and time-consuming clinical visits, discouraging preventative screening without severe symptoms especially for low/middle-income population at higher RD risks due to more exposure to tobacco and work-related particulates. Diagnosis of RDs like asthma also relies on detection of intermittent abnormal respiratory sounds, which can benefit from prolonged recordings outside the clinic setting. In this project, a low-cost, low-profile, easy-to-use and effective device will be developed to detect adventitial asthma respiratory sounds, facilitating access to screening and continuous treatment monitoring in RD patients. Auscultation is a powerful, non-invasive and well-established method to evaluate health of cardiopulmonary system through sounds of lung and heart. Stethoscopes have been used by physicians for over two centuries in clinics, but they are unsuitable for continuous cardiopulmonary activities monitoring due to large form-factor and dependence on listening skills and experience, prohibiting critical applications like ambulatory monitoring and early detection of RDs in small children. A need exists for a low-profile, miniaturized, high-precision diagnostic device that is more accessible and can accurately detect and quantify respiratory abnormalities over prolonged measurements without relying on the skills and experience of a physician to interpret the sounds. To that end, the electronic interface and acoustic coupling of a MEMS-based accelerometer contact microphone (ACM) onto skin will be optimized to record respiratory sounds with high fidelity, and compared against clinical diagnosis. Breakthrough, hermetically-sealed, high-precision ACMs with unidirectional vibration sensitivity will be used to overcome limits of standard stethoscopes that are bulky, susceptible to airborne and rubbing noise, and hard to use. Besides lung and heart sounds, the ACM simultaneously acquires respiratory rate, heart rate and physical activities of the users. Data will be analyzed using simple algorithms like time-frequency analysis and continuous wavelet transformation to provide reliable information for diagnosis of asthma by detecting signature sounds like wheezing in a wide frequency range of 100Hz-5kHz. Diagnosis accuracy and comprehensiveness are expected to be improved by the ACM-enabled prolonged recording, capability of correlating respiratory sounds with heart sounds and body motions, and detection of higher frequency signals. Interface between ACM and skin will be optimized to increase acoustic coupling over a wide frequency range for wideband adventitious sounds. Low- profile wearable ACMs will be used in a clinical setting to detect adventitial respiratory sounds indicative of asthma and compared with medical-grade digital stethoscopes and clinician judgment. Potentials of the ACM for detecting information for other RDs like COPD and pneumonia will also be assessed for future developments.

摘要：呼吸系统疾病 (RD) 是美国第五大死因，造成的损失超过 $150B 医疗保健费用。像哮喘这样的 RD 是无法治愈的，如果不及时治疗可能会危及生命。正如大多数 危险的 RD 是进行性的，可以通过预防性治疗进行控制，早期发现对于预防至关重要 恶化。目前的诊断依赖于昂贵且耗时的临床就诊，阻碍了预防性预防 在没有严重症状的情况下进行筛查，特别是对于由于更多原因而具有较高 RD 风险的低/中等收入人群 接触烟草和与工作相关的颗粒物。哮喘等 RD 的诊断也依赖于检测 间歇性异常呼吸音，这可以从诊所外的长时间录音中受益。 在这个项目中，将开发一种低成本、薄型、易于使用且有效的设备来检测外膜 哮喘呼吸音，有助于 RD 患者进行筛查和持续治疗监测。 听诊是一种强大的、非侵入性的、行之有效的评估心肺健康的方法。 通过肺音和心音的系统。听诊器已被医生使用了两个多世纪 诊所，但由于外形尺寸大且不适合连续心肺活动监测 依赖于听力技能和经验，禁止动态监控等关键应用 早期发现幼儿的 RD。需要一种薄型、小型化、高精度的诊断装置 更易于使用且能够长期准确检测和量化呼吸异常的设备 无需依靠医生的技能和经验来解释声音即可进行测量。为此， 基于 MEMS 的加速度计接触式麦克风 (ACM) 的电子接口和声学耦合 皮肤将被优化，以高保真度记录呼吸音，并与临床诊断进行比较。 将使用具有单向振动敏感性的突破性密封高精度 ACM 克服标准听诊器体积大、易受空气传播和摩擦噪音影响以及坚硬的限制 使用。除了肺音和心音之外，ACM 还可以同时获取呼吸频率、心率和体能信息。 用户的活动。将使用简单的算法（例如时频分析和连续分析）来分析数据 小波变换通过检测特征声音为哮喘诊断提供可靠的信息 哮鸣音的频率范围很宽，100Hz-5kHz。期望诊断的准确性和全面性 通过支持 ACM 的长时间录音、将呼吸音与心脏相关联的能力来改进 声音和身体运动，以及更高频率信号的检测。 ACM 和皮肤之间的界面将 经过优化，可在宽频率范围内增加宽带外来声音的声学耦合。低的- Profile 可穿戴 ACM 将在临床环境中使用，以检测表明以下情况的外膜呼吸音： 哮喘并与医疗级数字听诊器和临床医生的判断进行比较。 ACM 的潜力 还将评估其他 RD（如慢性阻塞性肺病和肺炎）的检测信息，以供未来发展。