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: 10058025
• 负责人: Farrokh Ayazi
• 金额: $ 8.71万
• 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 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10058025
• 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 environment; 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; Techniques; Testing; Time; Veins; Visit; Walking; Wheezing; Work; asthma exacerbation; asthmatic patient; base; body position; cardiopulmonary system; clinical Diagnosis; cost; design; 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）是美国第五大死亡原因， 医疗费用。像哮喘这样的RD是无法治愈的，如果不及时治疗，可能危及生命。因为大多数 危险的RD是渐进的，可以通过预防性治疗进行管理，早期发现对于预防至关重要。 加重目前的诊断依赖于昂贵和耗时的临床访问，阻碍了预防性治疗。 筛查无严重症状，特别是对于低/中等收入人群，由于更多的 接触烟草和与工作有关的颗粒物。像哮喘这样的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记录中受益。 本项目将开发一种低成本、低姿态、易于使用和有效的装置来检测外膜 哮喘呼吸音，促进RD患者的筛查和持续治疗监测。 听诊是一种强有力的，非侵入性的和公认的方法来评估健康的心肺 通过肺和心脏的声音。听诊器已经被医生使用了两个多世纪， 但由于其外形尺寸较大， 依赖听力技能和经验，禁止关键应用，如门诊监测， 在幼儿中早期发现RD。需要一种低轮廓、小型化、高精度的诊断设备， 一种更容易获得的设备，可以在长时间内准确检测和量化呼吸异常， 在不依赖于医师的技能和经验来解释声音的情况下，可以进行测量。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到 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灵敏度的突破性密封高精度ACM 为了克服标准听诊器体积大、易受空气传播和摩擦噪声的影响、并且硬 使用.除了肺音和心音，ACM还同时采集呼吸率、心率和身体参数。 用户的活动。数据将使用简单的算法进行分析，如时间-频率分析和连续 小波变换，通过检测特征音， 喘息的频率范围很宽，在100 Hz-5 kHz之间。预期诊断准确性和全面性 通过ACM启用的长时间记录来改善，将呼吸音与心脏相关联的能力 声音和身体运动，以及检测更高频率的信号。ACM和皮肤之间的界面将 优化以在宽频率范围内增加宽带偶然声音的声耦合。低- 轮廓可穿戴ACM将用于临床环境，以检测指示以下情况的外膜呼吸音： 哮喘并与医用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COPD和肺炎）的检测信息，以用于未来的发展。