Screening for Sleep Disordered Breathing with Minimally Obtrusive Sensors
Screening for Sleep Disordered Breathing with Minimally Obtrusive Sensors
批准号:
8648375
负责人:
Brian Robert Snider
金额:
$23.43万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-15 至 2016-08-31
关键词:
AcousticsAddressAdultAgeAgreementAirAlgorithmsApneaArrhythmiaBerlinBiological ProcessBreathingCaringCategoriesClassificationClinicClinicalClinics and HospitalsDataData CollectionDevicesDiagnosisDigital Signal ProcessingEnvironmentEventGoalsGoldGuidelinesHealthHealth systemHome environmentHourHumanHypertensionIndividualInsulin ResistanceLabelLocationManualsMeasuresMonitorNoiseObstructive Sleep ApneaOxygenPatientsPerformancePeripheralPhysiologic pulsePolysomnographyPopulationProceduresProcessPublishingPulse RatesQuestionnairesReportingResearchRunningSeveritiesSignal TransductionSleepSleep Apnea SyndromesSnoringSocietiesStrokeSurveysSymptomsSystemTarget PopulationsTechniquesTestingTimeTrainingVisualWireless TechnologyWorkclinically relevantcostdesigndiagnosis standardindexingoperationpatient populationpublic health relevancerespiratoryscreeningsensorsoundusabilityvehicular accident
中文摘要
总结
睡眠呼吸障碍 (SDB) 被认为是一种普遍存在且诊断不足的疾病,与以下疾病相关:
有害的健康问题,给社会带来高昂的代价。目前诊断 SDB 的黄金标准是时间-
耗时、昂贵且引人注目(需要许多连接线)的睡眠研究或多导睡眠图 (PSG)。
拟议研究的直接目标是开发和评估硬件设计和一套
用于自动检测阻塞性、中枢性或混合性呼吸暂停和呼吸不足的算法,
使用环境麦克风和无线脉冲获得外周血氧饱和度 (SpO2) 和脉搏率数据
血氧计。长期目标是创造一种低成本、易于操作、干扰最小的家用设备,
可用于在患者家中筛查 SDB。
我们的具体目标是:(1) 通过选择干扰最小的传感器硬件来开发筛查系统
扩展最先进的算法,用于根据声学、SpO2 和脉搏率数据自动检测 SDB;
(2) 使用所提出的系统在睡眠实验室和家中从代表性人群中收集患者数据;
(3) 通过比较所提出的系统对收集到的数据的性能来确定筛选精度
数据与标准 PSG 得出的临床结果相比较; (4) 衡量家用筛查设备的可用性
根据目标人群,要求参与家庭数据收集的受试者完成一项调查
拟议系统的设置和操作的各个方面。
英文摘要
Summary
Sleep disordered breathing (SDB) is believed to be a widespread, under-diagnosed condition associated with
detrimental health problems, at a high cost to society. The current gold standard for diagnosis of SDB is a time-
consuming, expensive, and obtrusive (requiring many attached wires) sleep study, or polysomnography (PSG).
The immediate objective of the proposed research is to develop and evaluate a hardware design and a set
of algorithms for automatically detecting obstructive, central, or mixed apneas and hypopneas from acoustic,
peripheral oxygen saturation (SpO2), and pulse rate data, using an ambient microphone and a wireless pulse
oximeter. The long-term goal is to create a low-cost, easy-to-operate, minimally obtrusive, at-home device that
can be used to screen for SDB in patients' homes.
Our specific aims are to: (1) develop a screening system by selecting minimally obtrusive sensor hardware and
extending state-of-the art algorithms for automatically detecting SDB from acoustic, SpO2, and pulse rate data;
(2) collect patient data in the sleep lab and at home from representative populations using the proposed system;
(3) determine the screening accuracy by comparing the performance of the proposed system on the collected
data against standard PSG-derived clinical results; and (4) measure the usability of an at-home screening device
by the target population, by asking subjects who participated in the at-home data collection to complete a survey
on various aspects of the setup and operation of the proposed system.
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