CN110325110A - 用于气道阻塞的系统、方法和生物标记 - Google Patents
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/346—Analysis of electrocardiograms
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- A61B5/7405—Details of notification to user or communication with user or patient ; user input means using sound
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- A—HUMAN NECESSITIES
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- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
Abstract
提供两种生物标记以用于阻塞性呼吸暂停。第一生物标记根据生物电信号确定吸气努力的幅度和计时。将呼吸率与正常的检测前的速率进行比较,并将努力的幅度与正常幅度进行比较。如果一系列的吸气努力高于正常幅度并且幅度正在增加,但是以正常速率,则可能存在阻塞性呼吸暂停。第二生物标记确定心率和呼吸率。建立心跳间期的正常的较低阈值,并且如果发生亚阈值事件(短RR间期),则针对呼吸率标准化视窗比较每个亚阈值事件序列的开始时间。如果亚阈值事件的数量超过视窗的最小值,则可能存在阻塞性呼吸暂停。
Description
技术领域
本发明涉及用于检测阻塞性呼吸暂停或呼吸困难的系统和方法以及用于阻塞性呼吸暂停或呼吸困难的生物标记的领域。
背景技术
气道阻塞可能是严重的健康紧急情况,其会在数分钟内导致死亡。部分阻塞也可能如此。
呼吸暂停是指暂停呼吸。在呼吸暂停期间,肺的体积最初保持不变。根据气道阻塞的方式(开放性),肺部与环境之间可能存在或可能不存在气流;肺内的气体交换和细胞呼吸不会受到严重影响。
在阻塞性呼吸暂停中,尝试呼吸,这导致膈膜和其他呼吸肌肉(包括肋间肌)的激活增加。在几分钟的较长时间呼吸暂停后,血氧下降,并且发生各种二次反应。
癫痫发作与阻塞性呼吸暂停有关。癫痫发作活动扩散到喉运动神经元,引起喉痉挛。喉痉挛导致部分气道闭塞或完全气道闭塞。癫痫发作活动改变呼吸频率、幅度、变异性,并且可能引起中枢性呼吸暂停。只有阻塞性呼吸暂停与快速严重的动脉氧饱和度降低,心动过缓以及死亡相关联。猝死是气道阻塞期间呼吸停止和几乎同时出现的LV扩张和心搏停止的结果。癫痫导致的猝死可能是足以导致阻塞性呼吸暂停的癫痫诱发的喉痉挛的结果,其导致在数十秒内呼吸停止和心脏停搏。
喉返神经(RLN)是迷走神经(颅神经X)的分支,其提供除了环甲肌之外的喉部的所有内在肌肉。这些肌肉用作打开和关闭声带,并且包括环杓后肌,其是打开声带的唯一肌肉。除了从两侧受神经支配的杓间肌之外,神经提供身体同一侧上的肌肉。参见en.wikipedia.org/wiki/Recurrent_laryngeal_nerve。喉返神经为声带下方的喉部提供感觉,为心脏深部神经丛提供心脏分支,并分支到气管、食道和咽下缩肌。环杓后肌,唯一可以打开声带的肌肉,受到这种神经的神经支配。神经还将来自声带下表面下方的喉粘膜以及感觉、分泌和运动纤维的感觉信息携带到食道和气管的颈段。
癫痫监测单元中的死亡率研究(MORTEMUS)确定了癫痫患者从开始全身性强直阵挛性癫痫发作开始到最终死亡的一致事件序列[Ryvlin等人,Lancet Neurol。12:966,2013]。将10个案例用于确定癫痫发作的最终结果是在几分钟内末端呼吸暂停和最终心脏骤停。最重要的是,这项研究为他们的SUDEP案例建立了单一的模式。
通过引用明确地并入本文的U.S.5,800,470公开了一种呼吸肌肌电图速率响应植入式起搏器。直接检测到的肌电图(EMG)信号被放大并带通滤波,处理以去除任何心电图(ECG)或起搏脉冲信号,全波整流,处理以产生移动时间平均信号,其中通过该移动时间平均信号,可以结合移动时间平均EMG的连续斜率检测之间的吸气和呼气时间来计算和处理峰值、最大斜率和EMG移动时间平均值的平均斜率,以产生表示通气速率的速率控制信号。可以从电极中选择性地拾取EMG,该电极植入胸骨旁肋间肌、外肋间肌、内肋间肌、膈膜或任何其他呼吸肌(诸如,斜角肌或胸锁乳突肌)中或植入其附近并且耦合到常规设计或特殊配置起搏器脉冲发生器和心脏起搏/感测导联系统。
通过引用明确地并入本文的U.S.4,961,423提出了采用特定的肌电图或EMG(与肌肉活动相关的电信号图)信号处理电路结合常规心脏起搏导联系统来导出控制信号,该控制信号在反射在与患者心脏接触的电极上时反映患者的呼吸。通过使用特定的过滤和信号处理,建议将心电图(ECG)信号与EMG信号和起搏刺激脉冲分开,该起搏刺激脉冲来自在起搏尖端上拾取的聚合信号,并且可以电极配对或在单独电极上专用于检测EMG。
通过引用明确地并入本文的Getzel等人的“Variation of Cardiac PacemakerRate Relative to Respiration”,IEEE Proceedings of 32nd CEMB,1979,第123页,和“Variation of Cardiac Pacemaker Rate Relative to Respiration”,IEEE Trans,onBiomed.Eng.,Vol.BME-26,No.9,1979年9月,第526页,描述了膈膜肌电图的电子积分以产生与呼吸微小体积成比例的控制信号,从而用作起搏器的控制生理输入。
通过引用明确并入本文的US 2016/0089540描述了一种治疗患者的方法,其包括:感测指示呼吸的生物参数;分析生物参数以识别呼吸循环;识别呼吸循环的吸气阶段;以及将刺激递送至患者的舌下神经,其中如果呼吸循环的吸气阶段的持续时间大于整个呼吸循环的持续时间的预定部分,则递送刺激。
因此,已知ECG信号中存在呼吸伪影。还知道的是,固有ECG信号是呼吸响应的,其包括R-R间期。
Nakase等人,“Laryngospasm,central and obstructive apnea duringseizures:Defining pathophysiology for sudden death in a rat model,EpilepsyResearch,第128卷,126-139(2016年12月),DOI:dx.doi.org/10.1016/j.eplepsyres.2016.08.004;www.epires-journal.com article/S0920-1211(16)30124-3/abstract,描述了使用动物模型进行癫痫猝死的病理生理学,并且具有多个图表,这些图表示出了喉痉挛、阻塞性呼吸暂停、阻塞性呼吸暂停期间的去饱和、在抵抗闭合气道尝试吸气时产生的力的直接测量以及ECG记录中存在伪影的证据。
癫痫扩散到自主神经系统被认为在癫痫突然意外死亡中起重要作用(SUDEP;(Bermeo-Ovalle等人,2015;Devinsky,2011;Lathers等人,2008;Sakamoto等人,2008;Shorvon和Tomson,2011;Stewart,2011;Surges和Sander,2012;Tolstykh和Cavazos,2013))。大约1%的美国人口患有癫痫;根据人们如何定义猝死,这些患者中2%至17%的死亡标记为SUDEP(例如(Nei和Hays,2010))。在患有癫痫的成年人中,死亡率是非癫痫患者的2到3倍(Langan,2000;Thurman等人,2014),并且SUDEP是一个最常见的死亡原因(Lathers等人,1998;Wannamaker,1985)。
已知癫痫发作会产生显著的呼吸变化(综述于(Massey等人,2014;Sowers等人,2013))。猝发性呼吸暂停(Blum,2009)涉及癫痫发作期间的氧去饱和(Bateman等人,2008;Seyal等人,2010)。实际上,动物研究确定了猝发性低氧血症在癫痫发作引起的死亡中的重要程度,因为对羊的研究表明,猝发性通气不足会导致严重的心动过缓和死亡(Johnston等人,1995;Johnston等人,1997)。已经在大鼠(Sakamoto等人,2008;Stewart,2011)、猫(Schraeder和Lathers,1983)和小鼠(Faingold等人,2010;Uteshev等人,2010)中注意到类似的发现。然而,尚未完全解决将癫痫发作与呼吸功能障碍联系起来的生理机制。
猝发性呼吸窘迫的一个可能原因是喉痉挛、部分或完全阻塞上呼吸道的声带的强直内收。在癫痫发作期间或在发作后观察到喉痉挛,当试图放置气管内导管(Tavee和Morris,2008)或强烈的吸气努力伴有严重的气短时(Amir等人,1983),由喘鸣和气道变窄证明。在化学诱发的癫痫发作期间,猫和仔猪经历通气不足和声门阻塞(Learning等人,1999;Terndrup等人,1995a;Terndrup等人,1995b)。在SUDEP案例中肺水肿是尸检中最常见的一个调查发现,这也是喉痉挛的间接证据(Antoniuk等人,2001;Morentin和Alcaraz,2002;Salmo和Connolly,2002)。当“拉动”闭合气道时可能发生肺水肿-吸气努力增加了肺毛细血管压力(Ead,2003;Murray-Calderon和Connolly,1997;Umbrain和Camu,1993)。癫痫发作可能经由自主髓质运动区扩散到迷走神经的喉分支(即声带的传出神经支配)而引起猝发性喉痉挛。
氨基甲酸酯/红藻氨酸盐模型(综述于(Naggar和Stewart,2015;Stewart,2011))用于允许在癫痫发作期间详细研究喉痉挛。该模型允许在癫痫发作期间进行侵入性监测。从喉返神经、到喉部的主要运动输出(Bartlett,2011;Brancatisano等人,1991;Kuna等人,1991;Kuna等,1988;Kuna等人,1990)以及同时的喉镜检查(Mor等人,2014)获得记录,以确定癫痫发作期间RLN活动的模式、癫痫发作对喉功能的影响以及喉功能障碍对呼吸的影响。这些数据突出了癫痫发作期间喉痉挛的复杂性,以及喉功能的变化如何导致死亡。
为了在动态环境中监测心脏信号,可以使用多种选择。可以从胸壁、四肢和手指获取生物电信号。也可以使用脉冲信息获得心率和脉搏可变性,脉冲信息可以通过皮肤、腕部、踝部和手指上的体积描记仪和光学传感器获得。
参见:
www.vitalconnect.com/upload/Documents/EngeryExpenditure2014_MobiHealth_published.pdf;
www.vitalconnect.com/upload/Documents/Longterm-Remote-Monitoring_HealthInnovations_2014_published.pdf;
www.vitalconnect.com/upload/Documents/AutomatedPrediction_2014_IEEE_published.pdf;
www.vitalconnect.com/upload/Documents/2014-Sleep-Abstract.pdf;
www.vitalconnect.com/upload/press/Chan2013EMBC_VitalConnectPatch.pdf;
www.vitalconnect.corn/upload/press/Selvaraj2013EMBC_OSAeventDetectionRespiratorySignals.pdf;
www.vitalconnect.com/upload/press/Chan2013EMBC_RespirationECGandAccelerometer.pdf;
Rosenberg M.、Samuel M.、Thosani A.、Zimetbaum P.,”Use of a noninvasivecontinuous monitoring device in the management of atrial fibrillation:a pilotstudy”,Pacing Clin Electrophysiol.2013;36(3):328-333。
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在US 2012/0004523中公开了基于指尖静电计的心动循环传感器。
发明内容
已知癫痫发作会产生显著的呼吸变化,并且癫痫发作扩散到自主神经系统可能导致危及生命的心血管和呼吸功能障碍。猝发性呼吸暂停和/或猝发性心动过缓已被公认为癫痫发作中的自主表现的一部分。长期的围猝发性呼吸暂停和心动过缓都被认为是癫痫猝死(SUDEP)的危险因素。SUDEP是癫痫患者死亡的主要原因。然而,对于SUDEP的生理机制知之甚少,甚至没有已知的SUDEP事件的具体指示。猝发性呼吸窘迫的一个可能原因是喉痉挛、部分或完全阻塞上呼吸道的声带的强直内收。使用大鼠模型,研究了由于癫痫发作和诱发的低氧血症引起的猝死。基于发明人的发现,一些癫痫发作引起喉痉挛,喉痉挛足够严重到产生完全的气道阻塞。一旦闭塞,抵抗闭合气道吸气的尝试就会逐渐变强,直到尝试停止(呼吸停止点)。这些尝试在心电图(ECG)和脑电图(EEG)信号的记录中产生明显的伪影,其幅度与尝试吸气的力高度相关。在闭塞晚期,RR间期变异性由于整体较慢的心率以及与尝试吸气密切相关联的额外的非常短的RR间期而显著增加。
在阻塞性呼吸暂停期间由喉痉挛引起的ECG和EEG中的伪像在时间上对应并且在尺寸上与直接测量实验动物的吸气努力相关。同样地,这些吸气努力引起来自包括膈膜肌和肋间肌的呼吸肌肉的强肌电图(EMG)信号,同时由此产生的低氧血症导致心动过缓和心率变异性的突然增加以及在每次尝试吸气时的非常短的RR间期。
通过RR间期分析和伪影检测以及ECG和EEG记录的量化,可以自动识别ECG中的R波。
通过这些信号检测并分析的这些生理效应可以用作阻塞性呼吸暂停(例如喉痉挛)的实际生物标记。特定于上呼吸道闭塞的两种特定生物标记包括:
-叠加在ECG信号上的高频EMG信号
-R-R波间期的变化
高频信号具有对应于吸气努力的幅度,并且因此,可以通过随时间监测呼吸伪影来建立自适应基线。当发生阻塞性呼吸暂停时,呼吸伪影以独特的方式改变。连续尝试时振幅增加,并且这些尝试的计时与正常呼吸率不同。高频信号和R-R波间期的变化都对阻塞性呼吸暂停有反应,并且表示包括膈膜肌和肋间肌的呼吸肌肉的呼吸暂停活动模式。
因为这些生物标记本身不需要ECG分析,所以可以从用于心脏监测的非标准位置(诸如手指或手腕)上的电极检测这些生物标记。如此,监测设备可以采用腕带、环的形式或其它方便的形式。当然,也可以采用传统的胸部电极。
R-R间期是基本心率,并且因此可以以替代方式确定速率及其可变性,例如,在没有心电图电极的情况下。例如,物理或光学脉冲传感器、声学传感器、心冲击描记图传感器等。
另一方面,来自呼吸肌肉(包括膈膜肌和肋间肌)的高频肌电图信号叠加在心电图信号上通常需要电子传感器以进行检测。然而,可以采用其它类型的呼吸传感器和检测,但是当直接测量呼吸时,减少了对生物标记或间接测量呼吸暂停的需要。
这些生物标记的组合清楚地表明在人的呼吸被阻塞时,尝试呼吸并在这些尝试中产生大的呼吸力。此时发出警报警告看护人员将提供足够的时间来确保不发生呼吸停止,或者如果确实发生呼吸停止,可以采取复苏步骤以挽救生命。这些生物标记也可以应用于过去的案例并用于监测患者以改善结果。
这些生物标记可以应用于各种类型的阻塞性呼吸暂停。虽然优选的系统和方法针对猝发性阻塞性呼吸暂停,但哮喘病症可能产生类似的生物标记。因此,当发生哮喘发作时,气道受到限制,导致胸部压力降低和较大的吸气努力。哮喘性呼吸暂停倾向于是不完全阻塞,并且因此随着时间推移的模式可能与喉痉挛诱发的呼吸暂停不同,但是生物标记足够广泛以允许应用于各种用途。
在哮喘的情况下,人们可能试图确定阻塞的程度,这不总是直接明显的,特别是在运动诱发的哮喘中,其中增加的需求叠加在气道限制上。然而,该限制将加大所需的努力,并且增加压力差,从而因此可以将哮喘限制与仅仅由于用力而增加的呼吸率区分开。
基于这些生物标记,提供了一种系统和方法,其可以检测阻塞性呼吸暂停的时间段并且用于及时发出警报以防止呼吸停止或及时进行复苏。
该系统和方法的特定方面是从ECG数据、EEG数据或其他生物电信号中提取一种或两种生物标记。因此,用于生物标记提取的数据可以来自多个源。在其中已经收集了ECG数据或EEG数据并且可将其用于分析的情况下,例如,在医院环境中的任何连续ECG记录或EEG记录,诸如在重症监护室、癫痫监测单元等中使用的,可以将生物标记识别算法添加到现有器械中。在门诊或家庭环境中,可以通过最小侵入性“手镯”获取ECG,诸如用于普及的HR监测的手镯,除了通常将遥测组件添加到手镯和接收站,例如智能电话,其将容纳用于警报的生物标记检测软件和硬件。带电极的帽子或头皮监视器也可以提供EEG数据。
当然,可以在传感器模块内提供数据分析,并且从模块发出听觉警报和/或视觉警报。感觉阻塞可能导致大约10至30秒的潜伏期,并且患者发生永久性损伤之前的时间仅为几分钟,从而仅提供较小的视窗来防止患者气道完全喉部阻塞,并且因此现场护理人员需要立即提供帮助,而远程监测可能无效。但是,在医院或其它设施内,远程无线警报可能是有用的。类似地,在不完全阻塞的情况下,诸如支气管收缩,呼吸暂停的发病和消退为干预提供了更大的机会视窗。
生物标记提取涉及对两种生物标记中的每一种生物标记获取ECG信号并以不同方式对其进行处理。
生物标记1
用于生物标记1(伪影生长)的算法涉及以下步骤,其应用到以约10Hz至>1kHz的带宽记录的ECG:
1.将二次滤波器应用到数据以通过大约300Hz至1kHz。
2.通过诸如整流和积分或信号“包络”量化的方法来检测和测量呼吸伪影。
3.将值与幅度阈值进行比较。
4.保持事件的值和时间高于阈值。
5.将连续事件之间的间期与建立用于呼吸率的视窗进行比较。
6.如果发生以下情况,发出声音警报:
·a)3个连续事件高于阈值,以及
·b)事件之间的间期适合呼吸率,以及
·c)事件幅度稳定或增加。
更一般地,获得生物电信号,其包括来自包括膈膜肌和肋间肌肉活动的呼吸肌肉的活动的影响。处理生物电信号以表示吸气努力的幅度和计时。将呼吸率与正常的检测前的速率进行比较,并将生物电信号的幅度与检测前的正常幅度进行比较。如果一系列的吸气努力高于正常幅度并且幅度正在增加,但是其以正常速率增加,则可能存在阻塞性呼吸暂停。
生物标记2
生物标记2的算法(超短RR间期)涉及通过以下步骤分析所获取的ECG信号:
1.检测R波。
2.测量RR间期。
3.比较间期与基线范围。
4.如果检测到超短间期(RR间期低于阈值),则存储事件的值和时间。
5.即刻将连续的短间期存储为单个事件。
6.将连续事件之间的时间与建立用于呼吸率的视窗进行比较。
7.如果发生以下情况,发出声音警报:
a)由呼吸间期间隔开3组短间期。
更一般地,确定心率,并且与基线平均值进行比较。建立正常的较低阈值,并且如果发生亚阈值事件(短RR间期),则针对呼吸率标准化视窗比较每个亚阈值事件序列的开始。如果亚阈值事件的数量超过视窗的最小值,则可能存在阻塞性呼吸暂停。
该技术可以在接收生物电信号的任何设备中实施,该生物电信号包括从呼吸肌肉发出的肌电信号。例如,除了正常的除颤器功能之外,可以向自动体外除颤器(AED)设备提供程序指令,该程序指令允许ECG电极读取肌电信号并提供阻塞性呼吸暂停指示。如上所述,本系统试图将当前的生物电信号与基线信号进行比较,该基线信号可能在紧急情况下不可用。同样地,AED倾向于与看护的人类用户一起使用,他们可以观察患者。然而,用户可能未受过训练,并且因此自动监测患者的呼吸暂停以及区分不同类型的呼吸暂停可能是有用的,特别是对于其中连到AED的患者具有正常窦性心律但尚未遇险的鉴别诊断。
因此,本发明的目的是提供一种用于检测阻塞性呼吸暂停的方法,其包括:接收来自哺乳动物的生物电信号,该生物电信号包括呼吸肌肉的肌电活动,该呼吸肌肉包括膈膜肌和肋间肌;处理生物电信号以分离肌电活动;基于分离的肌电活动确定吸气努力的计时和幅度;确定吸气努力的基线幅度;将吸气努力的幅度与所确定的吸气努力的基线幅度进行比较;以及如果一系列吸气努力具有大于基线幅度的随时间增加的幅度,则确定发生阻塞性呼吸暂停。
该方法还可以包括:确定吸气努力的基线计时;以及将吸气努力的计时与所确定的吸气努力的基线计时进行比较,其中如果一系列吸气努力具有大于基线幅度的随时间增加的幅度以及基线计时,则确定发生阻塞性呼吸暂停。
在确定发生阻塞性呼吸暂停之前,可以通过一系列三次吸气努力来确定吸气努力的计时和幅度。
生物电信号可以是心电图信号。生物电信号可以是脑电图信号。可以从单个末端获取生物电信号。
该方法还可以包括响应于确定发生阻塞性呼吸暂停而产生听觉警报。该方法还可以包括响应于确定发生阻塞性呼吸暂停而产生无线通信。
可以从哺乳动物接收生物电信号,该生物电信号包括呼吸肌肉的肌电活动,该呼吸肌肉包括膈膜肌和肋间肌,包括接收心电图信号、脑电图信号和肌电信号中的至少一种。生物电信号的处理可以用于分离肌电活动,其包括使生物电信号经受具有约300Hz至1kHz之间的通带的带通滤波器。生物电信号的处理可以用于分离肌电活动,其包括确定通带内的信号功率随时间的变化。
将吸气努力的幅度与所确定的吸气努力的基线幅度进行比较可以包括将吸气努力的一系列幅度和计时与表示吸气努力的正常幅度和计时范围的基线视窗进行比较。
如果一系列吸气努力具有大于基线幅度的随时间增加的幅度,则可以确定发生阻塞性呼吸暂停,其包括确定三次连续吸气努力是否具有大于阈值的幅度,该阈值具有稳定幅度和增加的幅度中的至少一个,而吸气努力之间的间期在正常范围内。
本发明的另一个目的是提供一种确定阻塞性呼吸暂停的方法,其包括:确定呼吸间期内相应呼吸率的基线心跳间间期和正常变化范围;确定患者的心跳间间期和呼吸率;确定一系列心跳间间期的开始,该一系列心跳间期超出正常变化范围并低于相应呼吸率的基线心跳间间期;如果在呼吸间期内低于相应呼吸率的基线心跳间间期的一系列至少一个心跳间间期的多次开始超过阈值,则确定阻塞性呼吸暂停的开始。阈值可以是三。
可以基于生物电信号确定心跳间间期和呼吸率。
生物电信号可以是心电图信号、脑电图信号和/或肌电信号。可以从单个末端获取生物电信号。
该方法还可以包括响应于确定阻塞性呼吸暂停的开始而产生听觉警报。该方法还可以包括响应于确定阻塞性呼吸暂停的开始而产生无线通信。该方法还可以包括响应于确定阻塞性呼吸暂停的开始而通过电话网络自动生成e911(增强型911)呼叫。
可以通过确定心电图的R-R间期来确定心跳间间期。
该方法还可以包括建立视窗,该视窗区分相应呼吸率的正常心跳间间期和短心跳间间期;并且记录超出相应呼吸率的视窗的心跳间间期的时间。
本发明的又一个目的是提供一种用于检测阻塞性呼吸暂停的系统,其包括:输入,该输入被配置为接收来自哺乳动物的生物电信号,该生物电信号包括呼吸肌肉的肌电活动,该呼吸肌肉包括膈膜肌和肋间肌;至少一个处理器,其被配置为:处理生物电信号以分离肌电活动;基于分离的肌电活动确定吸气努力的计时和幅度;确定吸气努力的基线幅度;将吸气努力的幅度与所确定的吸气努力的基线幅度进行比较;以及如果一系列吸气努力具有大于基线幅度的随时间增加的幅度,则确定发生阻塞性呼吸暂停;以及输出,该输出用于根据确定发生阻塞性呼吸暂停来传送警报。
本发明的另一个目的是提供一种用于确定阻塞性呼吸暂停的系统,其包括:输入,该输入被配置为接收定义心跳间间期的信息;至少一个处理器,其被配置为:确定呼吸间期内相应呼吸率的基线心跳间间期和正常变化范围;确定患者的心跳间间期和呼吸率;确定一系列心跳间间期的开始,该间期超出正常变化范围,并低于相应呼吸率的基线心跳间间期;如果在呼吸间期内低于相应呼吸率的基线心跳间间期的一系列至少一个心跳间间期的多次开始超过阈值,则确定阻塞性呼吸暂停的开始;以及输出,该输出用于根据所确定的开始来传送警报。
通过阅读本说明书,这些和其它目的将变得显而易见。
附图说明
图1A示出了通过高通滤波在EEG和ECG中增强的伪像。箭头表示最后一次呼吸尝试。
图1B示出了ECG伪影和EEG伪影与峰值吸气压力(PIP)的相关性。
图1C示出了RR随时间(底部)、阻塞期间的PIP(中间)和PIP峰值标记(顶部)的图。闭塞后期RR的变化增加。
图1D示出了RR间期的标准偏差(n=16只动物)。
图1E示出了相对于PIP的作为时间函数的RR间期的图(n=16只动物)。
图2示出了癫痫发作期间RLN活性的极端增加。
图3示出了红藻氨酸诱发的癫痫发作活动期间的体积描记图。
图4A示出了杓状软骨随时间的移动的曲线图,以及图4B示出了癫痫发作期间的平均声门打开随时间的曲线图,其表明了在癫痫发作期间示出了不规则的声带运动。
图5示出了在癫痫发作期间的阻塞性和中枢性呼吸暂停。
图6示出了在阻塞性和中枢性呼吸暂停期间的喉返神经活动。
图7示出了在基线状态(左)、偏瘫状态(中)和喉痉挛(右)状态下的喉镜视图、体积描记图迹线、ECG和EEG(x2)描记。
图8示出了在上呼吸道闭塞期间ECG(顶部)、脉搏血氧计(从顶部起第二条)、气道压力(从底部起第二条)和血压(底部)的同时描记。
图9示出了受控气道闭塞期间的超声波心动描记图。
图10示出了在试图抵抗上呼吸道阻塞吸气期间生物标记1的人类受试者中的初步测试的曲线图(ECG记录的背景活动的增加的峰间幅度,这是由于ECG信号中包含的胸肌EMG增加所致)。
图11示出了受控气道闭塞期间心脏参数和呼吸参数的汇总。
图12和图13示出了各种现有技术的ECG采集系统。
图14示出了现有技术的ECG模拟采集和无线发射器系统。
图15和图16示出了图14的现有技术ECG无线发射器系统和ECG模拟采集系统的半示意图。
图17示出了根据图14的现有技术ECG模拟采集和无线发射器系统的算法实现的现有技术流程图。
图18示出了根据US 2016/0128209的现有技术电子设备的框图。
图19是示出根据US 2016/0128209的包括电子设备的网络环境的图。
具体实施方式
示例1
肠胃外的红藻氨酸用于诱发氨基甲酸酯麻醉的斯泼累格·多雷(SpragueDawley)大鼠的复发性癫痫发作。在有气管内插管或没有气管内插管的情况下,在复发性喉神经(RLN)活动的多单元记录或躯体(head-out)体积描记图中进行EEG记录和心肺监测的组合(包括视频喉镜检查)。气管导管的受控闭塞用于研究突然阻塞后心脏和呼吸变化的动力学。癫痫发作活动导致显著的RLN发作增加,这与声带的异常高频运动有关。喉痉挛引起的部分气道阻塞在体积描记图中是很明显的,并且通过插管来预防。完全的声门闭合(通过喉镜检查确认)发生在一部分非插管动物中,其伴随着RLN活动的最大增加,并且通过ST段抬高、心动过缓和死亡,随后在数十秒内在所有阻塞的动物中停止气流。
在癫痫发作期间插管大鼠和非插管大鼠均发生中枢性呼吸暂停的时间长达33秒,并且这与适度增加的RLN活动、最小的心脏紊乱和喉镜检查时开放的气道相关联。
对于受控的气道闭塞,将T形导管插入氨基甲酸酯麻醉的大鼠的远端气管中。将T形导管侧臂的EEG、ECG和吸气压力从1Hz到1kHz进行带通滤波。将T形导管的开口部分闭塞100秒或直至呼吸停止。EEG记录和EEG记录中的吸气伪影通过数字高通滤波器(转角频率367Hz,滚降-3dB/倍频程)隔离,并通过全波整流进行量化。吸气伪像在气道闭塞期间与吸气压力极值相匹配。在动物内比较中峰值吸气压力与伪影幅度的相关性(r)为-0.88(ECG)和-0.75(EEG),其表明从ECG记录中提取的伪像可能比从EEG记录导出的伪像更好。伪影量级(ECG)与峰值吸气压力的平均相关性为-0.89+0.04(N=5只大鼠)。结果表明,EEG记录和ECG记录中吸气伪影的幅度的突然增加表明闭塞的气道,并且观察到增加的吸气伪影大小与增加的吸气努力的非常高的相关性。这种伪影模式可以在两个重要方面用作生物标记:首先,查阅阻塞性呼吸暂停对记录的SUDEP案例的可能影响的现有记录。其次,警告实时监测患者的阻塞性呼吸暂停。通过标记癫痫发作活动和心率的降低,可以进一步提高生物标记的特异性。为了最大化生物标记的灵敏度,应该以尽可能高的带宽(在可用设备的能力范围内,例如,高达10kHz带宽)记录EEG和ECG。该生物标记的最明显的特征是其可以来自癫痫监测单元并且甚至可能是医院外的潜在便携式设备中常用的措施。
使用允许同时进行自主神经、心血管和呼吸监测的大鼠模型,证明癫痫发作诱发的喉痉挛引起了阻塞性呼吸暂停,其阻止癫痫发作并持续至呼吸停止,随后是心脏骤停。MORTEMUS研究使用EEG记录中的伪影作为呼吸的证据。本文的一个重要发现是,在阻塞期间尝试呼吸在EEG记录和ECG记录中产生了伪像,该伪像类似于与实际呼吸相关联的伪像。
在气道阻塞期间尝试吸气的电伪影可以用作阻塞性呼吸暂停的实际生物标记。在图1A中,结合气管压力示出了与ECG记录和EEG记录中的呼吸相关的伪影。高通滤波的伪影大小与峰值吸气压力高度相关(r2=0.85;n=14只动物)。伪影本身的大小不可以区分有效呼吸和尝试呼吸。特定生物标记是在气道阻塞期间作为增加努力的标记的伪影大小的上升趋势。
大多数患者[Ryvlin等人]和动物[Nakase等人;Hotta等人,Epilepsia 50:923,2009]中都存在缓慢心律失常。ECG RR间期变异性(SDNN;ECG和滤波的ECG)的突然变化以及在吸气期间RR间期的正常延长可以在晚期闭塞期间反转。该模式表示气道阻塞的第二种生物标记,即使是在短时间样本的情况下。在基线时没有动物、在早期闭塞期间有4只动物(共16只动物)以及在晚期闭塞期间有15只动物(共16只动物)发生与吸气相关的异常短RR间期。
图1A至图1E示出了在阻塞期间作为阻塞性呼吸暂停的生物标记的与吸气相关联的伪影和RR间期长度的变化的示例。
图1A示出了通过高通滤波在EEG和ECG中增强的伪像。箭头表示最后一次呼吸尝试。
图1B示出了ECG伪影和EEG伪影与峰值吸气压力(PIP)的相关性。
图1C示出了RR随时间(黑色)、阻塞期间的PIP(蓝色)和PIP峰值标记(红色)的图。闭塞后期RR的变化增加。在极端吸气努力期间,RR间期的相对最小值仅比基线短。箭头指向正好在错过呼吸前呼吸最小的伪影或RR图。在图的底部处的粗黑线是插图中示出的时间。
图1D示出了RR间期的标准偏差(n=16只动物)。
图1E示出了相对于PIP随时间的作为时间函数的RR间期的图(n=16只动物)。基线和发作的拟合曲线使用右侧纵坐标。注意RR与吸气峰值的反向关系。
示例2
在旨在表征正常安静呼吸(基线)期间和在由红藻氨酸诱发的癫痫发作期间的RLN活性的一组实验中研究了癫痫发作活动在喉部的主要运动神经RLN上的扩散。使用双侧保留RLN的气管开口或T形气管导管来保护动物免受喉痉挛。在带有气管导管的动物中,可以用喉镜检查研究完全声门闭合的时段而不用担心氧饱和度下降。也在其它实验期间进行RLN记录,其目的是在特定事件(诸如中枢性和阻塞性呼吸暂停)期间捕获RLN活动。在所有动物中记录EEG、多单元RLN活动和ECG。在实验期间间期进行喉镜检查。
在第二组实验中,通过躯体体积描记图评估喉痉挛和癫痫发作活动对通气的影响。在诱发癫痫发作之前,利用气管内导管对一组动物进行插管,并且将这些动物与非插管动物进行比较。非插管动物包括两个亚组:一组没有使用红藻酸以外的治疗,从而诱发癫痫发作,另一组利用双侧喉上神经横断来防止在癫痫病症发作前进行反射性喉痉挛。
癫痫发作活动与RLN活动的增加和声带的异常高频运动相关联。在单次癫痫发作中,RLN活性逐渐增加,其中最为通常的是在癫痫发作快结束时观察到最高水平的活动。当通过气管导管或视窗保护气道时,可以观察到单次癫痫发作期间RLN活动的完整模式增加,并且其在癫痫发作结束时降至基线(图2)。癫痫发作活动期间的喉痉挛对呼吸有显著的影响。
图2示出了癫痫发作期间RLN活性的极端增加。完整癫痫发作的节段示出为RLN上的正常呼吸急促(左上方,偶数行)让位于显著增加的发作(顶部迹线的右侧,其中在第二迹线的右侧上具有最大值),最终发作减少(底部迹线)。EEG显示在奇数行上。用箭头标记出癫痫发作和偏移的估计(基于低频活动和尖峰的变化)。在这些动物中,通过气管植入物或通过气管软骨切开的开口保护气道,使得可以捕获个体癫痫发作期间RLN活动的整个概况。
在氨基甲酸酯麻醉下的正常潮式呼吸期间,大鼠的早期呼气峰值类似于人类呼吸(Arito等人,1997)。14只非插管大鼠中的3只大鼠和6只插管大鼠中的1只大鼠具有癫痫发作活动,其主要表征在于低频率的重复性喘气呼吸,并且未包括在汇总数据中。在该亚组中SLN病变前和病变后以及插管动物插管前和插管后进行体积描记图记录。由于SLN病变或插管,所测量的参数均未显示出差异。用于与癫痫发作值比较的癫痫发作前的值是仅KA癫动物的基线病况、插管动物的插管后病况和SLN损伤动物的损伤后病况。非插管大鼠的两个亚组之间没有差异,并且它们的测量结果汇总用于统计,除非将这两个组相互比较。在图3中示出了非插管大鼠和插管大鼠的流量-体积循环的示例。
图3示出了红藻氨酸诱发的癫痫发作活动期间的体积描记图。来自一个非插管大鼠(图组A1、图组C1)和一个插管大鼠(图组B1、图组D1)的头部体积描记图示例。在顶行(图组A1、图组B1)示出每只动物的癫痫发作前基线病症,以及在下面(图组C1、图组D1)示出相应的癫痫发作相关病症。对于每个图组,分析5分钟的连续呼吸以在每种情况下产生流量-体积循环。每个流量-体积图上的上部水平红线是平均峰值呼气流量,下部水平红线是平均峰值吸气流量,以及垂直红线是平均潮气体积。几个关键特征是明显的:1)两种动物的癫痫发作期间的潮气体积均较低;2)两种动物的癫痫发作期间呼吸流量和体积的变化均增大;3)非插管大鼠的峰值吸气流量与峰值呼气流量的比率降低,而插管大鼠的峰值吸气流量与峰值呼气流量的比率增大(在每个流量-体积曲线图的右上方处显示计算的平均值)。
癫痫发作活动与所有剩余大鼠(11只非插管大鼠和5只插管大鼠)的呼吸率大幅增加有关联,而与治疗无关,从分别为85+11次呼吸/分钟(非插管大鼠)和98+17次呼吸/分钟(插管大鼠)的平均癫痫发作前速率至371+54次呼吸/分钟和295+43次呼吸/分钟的癫痫发作相关率。对多变量ANOVA进行Scheffe事后校正后,增加更为明显(p<0.0001)。在5只仅KA癫大鼠和6只非插管的SLN病变动物中观察到89和81次呼吸/分钟的癫痫发作前平均速率,其中两个组的癫痫发作相关平均速率为371次呼吸/分钟(两个比较的p<0.0001)。
在表1中给出其它细节,该表显示了一阶和二阶体积描记图变量的汇总。测量的全套体积描记图变量显示基线、术后操作(插管或SLN病变)和癫痫发作期间的详细信息。操作(插管或SLN病变)没有显著地改变任何参数的基线值,但是癫痫发作活动改变了与所有动物的持续时间和体积相关的许多参数。区分非插管动物和插管动物的主要措施是吸气峰值流量与呼气峰值流量的比率。Scheffe事后校正应用于单向ANOVA。将p值为0用于表示p<0.0001。
非插管大鼠的潮气体积显著下降。平均癫痫发作前的潮气体积从1.50+0.36毫升/次呼吸降低至0.46±0.14毫升/次呼吸(p<0.0001)。亚组潮气体积均显著下降:对于仅KA癫大鼠,从1.2降低至0.46,p=0.008,以及对于SLN病变大鼠,从1.7降低至0.46,p<0.0001。在插管动物中,潮气体积在癫痫发作前(1.03+0.69毫升/次呼吸)与癫痫发作期间(0.53+0.26毫升/次呼吸)的差异没有达到统计显著性。
考虑到癫痫发作期间通气率增加约3倍且潮气体积减少约3倍,癫痫发作活动期间的平均每分钟通气与基线没有显著差异,但倾向于更低的值。平均癫痫发作前值124.8+27.3毫升/分钟(非插管大鼠)和124.2+61.8毫升/次呼吸(插管大鼠)与平均癫痫发作值100.8+35.7毫升/分钟和93.2+42.3毫升/分钟(NS,NS)相关。只有SLN病变的亚组显示出每分钟通气从138.8+13.2毫升/次呼吸显著降低至106+22.4毫升/分钟(p<0.0001)。仅KA癫大鼠的平均癫痫发作前值和癫痫发作值没有显著差异(108.0+25.0毫升/分钟与94.4+49.7毫升/分钟;NS)。
在吸气期间峰值流量与呼气期间峰值流量的比率中观察到最显著的差异。该参数用于识别上呼吸道阻塞。通常,该比率>1,并且值<1表示胸腔外(例如,上呼吸道)阻塞(Blitzer和Meyer,2006;Miller等人,1987)。非插管大鼠的平均癫痫发作前比率为1.04+0.25,而插管大鼠为1.02±0.10。对于插管大鼠(增加至1.56+0.38;p=0.011)和非插管的大鼠(降低至0.52+0.32;p<0.001),这些值在相反方向上改变。非插管动物的各个亚组各自显示了吸气期间和呼气期间的峰值流量的比率下降:仅KA癫大鼠(NS)从0.95降低至0.60,以及SLN病变大鼠从1.11降低至0.46(p=0.001)。尽管PF(i)/PF(e)的减少与喉痉挛引起的部分气道阻塞一致,但PF(i)/PF(e)的增加显然不是可变胸内阻塞的典型原因中的一种原因。由于在插管动物中没有阻塞,因此插管动物的流量-体积特征反映了癫痫发作诱发的无序通气而没有气道狭窄的影响。如果这为真,则非插管大鼠中观察到的PF(i)/PF(e)降低应该被认为是低估的,与插管大鼠的癫痫发作状况相比,这与其自身的癫痫发作前状况相比更为合适。
在表2中对值进行汇总,其显示了体积描记图数据的汇总统计。为了补偿多个ANOVA,在从体积描记图得到的4个变量(呼吸率、潮气体积、每分钟通气以及吸气峰值流量与呼气峰值流量的比率)上计算每只动物的差异评分(癫痫发作状况与癫痫发作前状况)。对插管和汇集的非插管研究分组之间的这些变化分数的分布差异进行双尾曼-惠特尼检验。基于对排名分数进行的独立样本双尾t检验,使用自举(20,000次重复)(SAS 9.4ProcMulttest)来获得四个测量结果的校正p值。
图4A和图4B示出了癫痫发作活动期间的不规则的声带运动。在癫痫发作活动期间的喉镜检查显示杓状软骨的“晃动”运动与来自体积描记图和RLN活动异常的部分阻塞的发现一致。在分析喉部声带和杓状软骨运动的视频记录时,左杓状软骨和右杓状软骨的高度相关运动部分脱离了-0.95+0.04至-0.79+0.11(n=10;p=0.0007)的平均Pearson相关性,如图4A所示。在喉镜检查的视频记录期间,声带和杓状软骨位置的逐帧分析示出了在呼吸期间声带的典型协调的外扩和内收(图4A的上部图的周期性低频迹线)。在上图中,左杓状软骨相对于中线的位置显示为向上偏转,以及右杓状软骨位置显示为向下偏转。相关性高(0.98)。在癫痫发作活动期间(高频迹线),总位移较小,频率较高,以及相关性降低(0.75)。
在图4B中示出了在峰间声门打开的五分位数中的时间分布(在基线处测量)。声门打开的时间跨度分布(频点大小=基线条件下最小打开至最大打开的20%)朝向较大的打开移动,但是其中声门打开的变化较小。实际上,10秒内的平均总标准化声门打开在癫痫发作活动期间比在基线期间更大(0.36+0.03基线,0.47+0.06癫痫发作;p=0.00005)。在基线(正方形)处,最大的时间分数处于闭合位置,其中通过打开角度快速循环。示出了正弦波的时间分布以供参考(虚线)。在癫痫发作活动期间,轮廓在相对打开的状态下以较大的时间分数显著改变(圆圈),这似乎减轻了相对静止的打开。数据示出为平均值+标准偏差。
尽管常规地观察到由于喉痉挛引起的部分气道阻塞的明确证据,但每分钟通气的适度减少表明癫痫发作期间的呼吸紊乱得到了充分补偿。然而,在离散性癫痫发作期间,一部分非插管动物中发生了完全的声门闭合(通过喉镜检查确认),其伴随着RLN活动的最大增加,并且随着ECG中的ST段抬高、心动过缓和最终死亡,随后所有动物在数十秒内停止气流。在11只非插管大鼠中的7只大鼠和5只插管大鼠中的0只大鼠中发生完全阻塞性呼吸暂停(p=0.03,Fisher精确检验,双尾)。所有7只动物均死亡。阻塞性呼吸暂停期的起点被视为从峰间气流达到小于呼吸暂停前峰间气流的10%的时间点,以及终点是记录停止并且动物从体积描记室中取出的时间,其中ECG上有严重心动过缓的证据是,在从体积描记室取出后,与明显的心肺停搏相关联。只有当存在人工气道时才会出现声门完全闭合期间,因为喉痉挛可以自行终止,其中每次呼吸都会恢复正常的打开和闭合模式。
图5示出了在癫痫发作期间的阻塞性和中枢性呼吸暂停。顶部图组例示了由于喉痉挛伴缺氧性心律失常引起的阻塞性呼吸暂停发作。每组迹线包括体积描记图(顶部);ECG(中间);EEG(底部)。阻塞性呼吸暂停发展为每次呼吸的空气量快速但连续(几秒)的减少,直到该量可忽略不计。在指示为完全阻塞时(通过同时喉镜检查确认-右侧示出的单帧),ECG发展为明显的心律失常,其中低氧血症引起ST段抬高。在癫痫发作结束时进行记录;例示数据的起点开始癫痫发作活动,并且用箭头标记癫痫发作偏移的估计(基于完整的EEG平坦内层(flat-lining))。相比之下,中枢性呼吸暂停的发作表征为呼吸和气流突然停止,但声带在打开位置(右侧视频帧)停止。在同一时段不存在心脏紊乱。从癫痫发作的中间取得的整个记录显示了癫痫发作活动。
在体积描记图记录中,气流迅速下降至零或接近零的流量(图5,顶部)。在每种情况下,ECG记录的ST段抬高是低氧血症的明显证据。喉镜检查显示了完全的声门闭合。阻塞性呼吸暂停产生明显的心肺停搏的最短持续时间为56秒。用喉镜检查确认声门闭合时记录的RLN活动(n=2)显示与喉痉挛相关联的强烈发作和低氧的ECG证据(图5,顶部)。SLN病变动物中发生喉痉挛进一步证明了喉痉挛不是由咽喉镜或唾液激活的咽/喉反射介导的。
图6示出了在阻塞性和中枢性呼吸暂停期间的喉返神经活动。在阻塞性呼吸暂停(顶部图组)和中枢性呼吸暂停(底部图组)期间的RLN发作(每个图组的中间迹线)显示RLN在两种类型的呼吸暂停期间都是活跃的。RLN为喉部外扩肌和内收肌承载运动输出。多单元记录不允许区分外扩肌或内收肌的神经活动,但在阻塞性呼吸暂停期间内收主导,以及在中枢性呼吸暂停期间外扩主导。视频帧显示在右侧。右侧还显示了针对每种类型呼吸暂停的三次ECG扫描以说明在阻塞性呼吸暂停期间明显的ST段抬高和减慢以及在中枢性呼吸暂停期间均匀的PQRST组合。在癫痫发作结束时进行示出阻塞性呼吸暂停的记录;例示数据的起点开始癫痫发作活动,并且用箭头标记癫痫发作偏移的估计(基于完整的EEG平坦内层)。
与阻塞性呼吸暂停的系统性影响相反,中枢性呼吸暂停(其表征为呼吸努力的突然停止)、完全打开的声门、中度RLN发作以及体积描记图上不含气流的期间从未与ECG中的ST段抬高或表明这些发作可能危及生命的任何其它证据相关联(图5底部和图6底部;表3)。
表3示出了阻塞性呼吸暂停和中枢性呼吸暂停之间的对比。在非插管大鼠和插管大鼠中捕获了阻塞性呼吸暂停期和中枢性呼吸暂停期的细节。阻塞性呼吸暂停仅出现在非插管大鼠中,其差异显著(p=0.034)。中枢性呼吸暂停时段的平均持续时间<10秒,但有些时段的持续时间超过30秒。为了比较任何一种类型的呼吸暂停对心脏活动的影响,基于体积描记图记录,在呼吸暂停发作的相当于10秒的时间段内将HR与ST段抬高的存在或不存在进行比较。仅在阻塞性呼吸暂停期观察到ST段改变。在此期间与基线相比采用最小HR,阻塞性呼吸暂停期和中枢性呼吸暂停期与显著的心动过缓相关联,但与阻塞性呼吸暂停相关联的变化更大。所有比较都是双尾非配对t检验。
作为声门闭合是主动而非被动的进一步证据(例如,类似于声带麻痹(Mor等人,2014)),进行体积描记图,并记录其中右侧声带因RLN损伤而瘫痪的动物的声带运动(图7,偏瘫)。在癫痫发作诱发的阻塞性呼吸暂停期间,ECG显示ST段抬高,并且体积描记图显示没有空气运动。在没有来自右声带的阻力的情况下,左声带的收缩力实际上将杓状软骨推动越过中线。
图7还示出了喉痉挛期间的收缩力。在该示例中,在基线图组(左)中示出杓状软骨的正常打开和闭合状态,并且同时进行体积描记图、ECG和EEG记录。体积描记图记录上的刻度标记表示视频快照的时间。请注意,即使在杓状突起与中线距离最小时,声门也不会完全闭合。在中间图组中,通过粉碎右RLN以导致偏瘫来使右侧声带瘫痪。呼吸从常规的较大呼吸转变为更频繁的较小呼吸与较大喘息混合。最右边的图组显示了在癫痫发作诱发的喉痉挛期间从同一只大鼠取得的足以产生阻塞性呼吸暂停的片段。声门是完全闭合的,但请注意当不与主动右侧(视频快照中的白色箭头)相对时,喉的左侧实际上是如何越过中线的。还请注意,与其它两种状态相比,ST段抬高是明显的(ECG迹线上的星号)。(校准:0.5秒,0.25毫升(体积描记),0.5毫伏(ECG)以及0.1毫伏(EEG))。
阻塞性呼吸暂停期的致死率与同一动物中的中枢性呼吸暂停期的最小影响形成对比。中枢性呼吸暂停的这些瞬态时段与表征呼吸停止的中枢性呼吸暂停是分开的。中枢性呼吸暂停的时段由长于1秒的呼吸突然停止的时段定义,如体积描记图记录所示。这些在所有组的动物的癫痫发作活动期间记录时段,其中组之间的中枢性呼吸暂停期的频率或持续时间没有差异。在基线状况、癫痫发作前/插管后状况或癫痫发作前/SLN横断后状况中均未观察见中枢性呼吸暂停期。与5只SLN病变动物中的3只动物和5只插管动物中的5只动物相比,6只仅KA癫动物中的3只动物显示出中枢性呼吸暂停期。记录中枢性呼吸暂停期时间长达33秒。表3详细描述了中枢呼吸暂停期长于1s的平均持续时间和计数,以及持续时间长于5s的时段子集。
两项发现突出了阻塞性和中枢性呼吸暂停之间的对比。首先,在中枢性呼吸暂停期间的喉镜检查中,声带外扩并且不能移动,并且在整个呼吸暂停期间将声门保持在完全打开的构型中(图5、图6)。喉部的打开状态是主动状态,如中枢性呼吸暂停期间的RLN活动所示。第二,心动过缓发展到更大程度,另外ST段抬高在阻塞性呼吸暂停期间而不是中枢性呼吸暂停期间显著。尽管阻塞性呼吸暂停期持续时间长于中枢性呼吸暂停期(所有中枢性呼吸暂停期自发地终止并恢复到呼吸暂停前呼吸模式),但同时从呼吸暂停开始,只有阻塞性呼吸暂停影响心脏功能。将来自所有组的时长为15秒或更长的所有中枢性呼吸暂停期放入单个汇总中(n=来自6只动物的9个呼吸暂停期),检查5至15秒的时间视窗内的心率变化以与呼吸暂停前平均心率进行比较。与呼吸暂停前的速率相比,阻塞性呼吸暂停的5至15秒的时间视窗内的平均心率测量值和最小心率测量值显著降低。对于中枢性呼吸暂停期,5至15秒期间的最小心率显著降低,但不是10秒时期的平均速率未显著降低。在比较相对变化时,阻塞性呼吸暂停期间的心率降低(-31.4+13.9%变化,n=7)在相同的时间帧(表3)内明显大于中枢性呼吸暂停(-17.3+9.7%变化,n=9)。在停止记录前,阻塞性呼吸暂停期间的平均最低心率为0.86±0.38次心跳/秒(低于基线时的>6次心跳/秒)。
进行一系列实验,其中气道的受控完全闭塞用于在没有癫痫发作活动期间何时会发生完全阻塞的不确定性的情况下研究反应动力学。在双侧解剖RLN后植入T形气管导管。这使得能够将气管导管固定到位而不会干扰正常的喉功能。气管导管侧臂上的压力传感器记录在气管导管朝向大气开放的正常呼吸期间或在开口端口通过气密帽完全闭合期间产生的力。完全阻塞气道持续100秒或直至发生呼吸停止后20秒,以较早者为准。除了气管侧臂压力之外,还连续记录ECG和脉搏血氧饱和度。在动物亚组中,进行超声心动描记图和/或连续动脉血压监测。
在闭塞期间,呼吸努力以逐渐增加吸气,然后在不到1分钟(60.4+24.0秒;中位数=54.4秒;n=16)的时间内停止。呼吸停止与心脏扩张和心搏停止有关,全身性血压升高(其在没有复苏的情况下收缩),并且喉痉挛足以完全闭合声门。这是一种中枢性呼吸暂停,其不同于早先报道的与主动打开气道相关联的中枢性呼吸暂停发作。LV舒张腔大小扩张了约40%(基线时的0.47+0.07到呼吸停止后10秒时的0.64±0.22cm),以及末期收缩LV腔大小扩张了近300%(基线时的0.12+0.03和呼吸停止后10秒时的0.44+0.23cm)。LV射血分数从94+2降至49+23%。
图7中例示了示例性实验,并且图8和图9总结了心脏和呼吸功能参数,其示出了受控气道闭塞期间的超声波心动描记图。图8示出了在气管闭塞100秒期间的ECG、脉搏血氧饱和度、气道压力传感器和动脉血压记录(用箭头标记开始和结束)。可以清晰的看到缓慢性心律失常和渐进式吸气努力的发展。吸气努力足以显著地影响血流,其通过与每次呼吸尝试相关联的较大脉搏血氧测量波来证明。图9示出了一系列M模式超声心动图图组,每个图组表示相应的2秒时段,其具有对应于图8的ECG迹线中的标记的附图标记。在闭塞前记录中可见正常的心脏功能(图9的图组0)。图9的图组1至图组6发生在闭塞期间的点处,并且其示出了节律异常和渐进式左心室扩张。当呼吸停止时(图9的回声图组5),心脏几乎无动力。恢复图组示出了气道阻塞消除并且呼吸恢复后的心脏功能的突然恢复。顶部图组中每个图的主要刻度:ECG=0.25mV;脉冲ox=5%变化(高通滤波);气道传感器=25mmHg;BP=10mmHg。
示例3
图10示出了试验性人体试验的结果,其示出了使用生物标记1(ECG记录的背景活动的增加的峰间幅度,这是由于ECG信号中包含的胸肌EMG增加所致)以检测阻塞性呼吸暂停。初步的人类受试者数据示出了生物标记物1出现在简单的环境中,其中患者试图通过从封闭的500ml容器中吸出空气来吸气。在吸气努力期间,出现了ECG背景幅度相对于QRS幅度的显著增加(峰值间ECG信号与QRS复合波的峰间幅度的简单比率)。
这表明了生物标记1在可以增加与吸气努力相关联的EMG的任何状况下具有效用。
在图10中,显示了对结果的统计分析:
ANOVA:F(1.487,43.13)=22.42P<0.0001
多重比较:
之前与期间,p=0.0001
之前与之后,p=0.0128
示例4
将气管导管放置在四只大鼠中,并且用红藻氨酸诱导强烈的癫痫发作。在三只大鼠中,监测系统变量以描述导致死亡的事件顺序。在连续癫痫发作(癫痫持续状态)期间,较浅且不规则呼吸与喘气呼吸混合,该呼吸以1/s的速率发生,但突然下降至1/15s,然后明显地完全停止。尽管气道完全打开,但54或77%的氧饱和度(第3只大鼠没有数据)开始过渡到非常缓慢或停止的呼吸。氧饱和度随时间的变化率较好地拟合了直线(斜率=-0.07+0.05脉搏血氧饱和度百分点/秒,R2v=0.93+0.04)。从这些值来看,与喉痉挛诱发的阻塞性呼吸暂停或受控闭塞发作后短于10秒的时间相比,氧饱和度平均下降10%需要135秒(2.25分钟)。尽管这些动物证明在持续的癫痫发作活动期间可能在完整的气道中发生非常低的氧饱和度和死亡,但是去饱和的时间太长以至于这种机制不太可能是离散癫痫发作期间去饱和的主要机制。相反,这种机制可能是癫痫持续状态的明显特征。
图11示出了受控气道闭塞期间心脏参数和呼吸参数的汇总。来自ECG的心率变化、基于脉搏血氧饱和度的动脉血氧饱和度、来自气管植入物的侧臂上的压力传感器的呼吸率和峰值吸气压力、以及来自超声心动图的左心室腔大小和射血分数。在受控气道闭塞(发病后15秒、呼吸停止时和呼吸停止后10秒)和恢复(复苏努力结束后60秒)期间,将闭塞前基线点与三个时间点进行比较。每个点示出为其平均值和标准偏差。对于一些措施,还将阻塞的动物(正方形)与无阻塞的对照动物(圆圈)进行比较。通常,呼吸参数和氧饱和度的变化比心脏参数的变化发生得早,这可以通过这些参数在气道闭塞发作后的15秒的统计学显著降低来证明。到呼吸停止时,左心室表现明显受损,如明显的扩张(扩大的末期收缩大小)和减少的射血分数所示。绘图单位:HR(心跳/秒)、氧饱和度(%饱和度)、呼吸率(次呼吸/秒)、峰值吸气压力(mmHg/100)、心室腔大小(cm)和射血分数(%心脏收缩期间射出的舒张体积)。
与声带连续内收的喉痉挛介导的阻塞不同,在阻塞期间,每次尝试的吸气与通过声带运动打开和闭合气道相关联,使得打开程度随着吸气努力的增加而增大。由于完全并列的杓状软骨和声带,每个声门打开之后是气道的完全闭合。与27.6±4.6°的基线值相比,最后一次呼气尝试期间的最大打开角度为56.7±5.3°(p<0.00001)。在最后一次呼气尝试之后,气道在此闭合位置保持额外的20至60秒,然后在复苏后恢复正常呼吸和声带运动,或者当声带在没有复苏的动物中出现放松时,较小的声门打开变得明显。
从最后一次明显呼吸的点来看,在30、70或140秒内达到心率的最小值。在两只动物中,仅在出现心动过缓后记录喉痉挛,因为没有连续地监测喉部。对于第三只大鼠,视频中捕获了喉痉挛的第一证据。这表明呼吸似乎在喉痉挛和癫痫发作获得停止前停止18秒,这可以通过EEG平坦化来证明。尽管诸如在受控的闭塞实验中描述的缺氧诱导的喉痉挛可能说明了在前两只大鼠中观察到的喉痉挛,但是第三只大鼠的喉痉挛与呼吸模式脱离,并且显然地仍然由癫痫发作活动驱动。
这些研究的主要发现是:1)癫痫发作活动导致RLN活性大量增加;2)癫痫发作活动改变呼吸频率、幅度、变异性,并且可能引起中枢性呼吸暂停;3)癫痫发作活动导致喉痉挛,其可能导致部分或完全气道闭塞(阻塞性呼吸暂停);4)只有阻塞性呼吸暂停与快速、严重的动脉血氧饱和度降低、心动过缓、呼吸停止和死亡相关联;5)低氧血症本身可能引起喉痉挛,显著地延长完全气道闭合;以及6)猝死是气道阻塞期间呼吸停止和几乎同时地左心室扩张和心搏停止的结果。从这组发现来看,可得出结论,经历癫痫发作的任何动物或人的猝死都可能是癫痫发作诱发的喉痉挛足以导致阻塞性呼吸暂停的结果,阻塞性呼吸暂停导致在数十秒内呼吸停止和心脏停搏,并且其只能通过心肺复苏来逆转(即,自发性恢复是极不可能的)。
癫痫发作明显扰乱了正常呼吸。呼吸频率、潮气体积和周期变化全部由癫痫发作活动进行了改变。更严重的结果标志着根本没有气流的时段,这或者是因为在声门完全打开时停止呼吸的驱动(中枢性呼吸暂停),又或者是因为由喉痉挛导致声门闭合(阻塞性呼吸暂停)。对氧气状态和心脏和呼吸功能的最显著的影响来自继发于癫痫诱发的喉痉挛的阻塞性呼吸暂停。对这些观察结果的直接解释是癫痫发作活动沿着从下丘脑的下托至室旁核(PVN)(Canteras和Swanson,1992)以及从PVN至髓质区域(例如(Geerling等人,2010))的途径扩散,其中它影响髓质自主神经核、呼吸中枢和喉运动神经元。
癫痫发作诱发的阻塞性呼吸暂停导致如此快速和严重的心肺功能障碍是关于什么的?气流不足不足以成为问题,因为中枢性呼吸暂停时段不会引起同样的恶化。阻塞性呼吸暂停的显著特征是气道完全关闭。癫痫发作诱发的喉痉挛期间声带的收缩力可以通过以下事实说明:即当主动的声带不与瘫痪的声带相对时实际越过中线;以及在尝试喘息期间未发生声带的惯常打开。相比之下,在中枢性呼吸暂停期间,声带总是处于完全打开的位置。可以想象,喉痉挛的发生仅仅反映了通过独立于阻塞性呼吸暂停的机制引起心肺功能障碍的癫痫发作活动水平。然而,当通过关闭未用红藻氨酸治疗并且未发生癫痫发作的大鼠的气管导管手动闭塞气道时,观察到相同的序列和时间过程:在数秒内氧饱和度降低、心动过缓和ST段抬,在约一分钟内呼吸停止和严重心脏机械性衰竭,以及在几分钟内心脏骤停。这些发现的组合表明,气道闭塞会引发心肺功能萎陷和死亡。
中枢性呼吸暂停和阻塞性呼吸暂停之间的主要差异与抵抗闭合气道尝试呼吸或窒息期间出现的强烈自主反应有关(例如(Brostrom等人,2007;Hotta等人,2009;Weiss等人,2015)),但不会在没有呼吸驱动的情况下发生。呼吸的保持可以持续很长时间而不会有损害;目前人类的世界纪录超过11分钟,或者在用纯氧过度通气后超过22分钟(自由潜水者组织(AIDA);www.aidainternational.org/)。它涉及自愿减少呼吸的驱动,但不需要关闭声门(Donzelli和Brady,2004;Mendelsohn和Martin,1993)并且不会显著地激活自主神经系统。癫痫发作诱发的中枢性呼吸暂停通常是无害的,因为它们在没有呼吸驱动的情况下仅诱发最小的自主反应和全身性反应。相反,癫痫发作诱发的阻塞性呼吸暂停是致命的,因为在抵抗闭合的气道尝试呼吸触发了强烈的自主共同激活,除了由于癫痫发作本身引起的已升高的自主紧张度之外,最终导致心肺功能萎陷。
考虑到心脏系统、呼吸系统和神经系统的复杂性和相互依赖性,问题在于喉痉挛是否对于猝死是必要和充分的。首先,癫痫发作诱发的喉痉挛不是由唾液或其它咽部刺激反射驱动的,因为非插管大鼠的亚组具有双侧上喉神经损伤,其会消除反射的传入肢以驱动喉痉挛。在体积描记图实验中观察到的所有死亡都伴有一系列癫痫发作诱发的喉痉挛,然后是呼吸以及心脏骤停,其中在气管植入物的受控闭塞期间观察到完全相同的时间分布。因此,闭合气道本身会超过临界阈值,并且癫痫发作诱发的喉痉挛足以导致猝死。
MORTEMUS心率数据显示,在癫痫发作结束时的明显呼吸阶段(图3,Ryvlin等人,2013)和末端呼吸暂停发作之前,10个患者中的9个患者经历最大幅度的心率下降。在目前的大鼠实验中心率急剧下降的计时对应于阻塞期后期的点,在癫痫发作终止后(Stewart,2008)但在呼吸停止之前,这被认为是对应于MORTEMUS研究中末端呼吸暂停的发作(Ryvlin等人,2013)。这不仅是可能的,并且可能的是MORTEMUS研究的SUDEP病例经历了阻塞性呼吸暂停,这可以通过导致大鼠中发现的呼吸停止和死亡的相同末端序列事件来证明。
即使在不是初始触发的情况下,喉痉挛也可能导致猝死。在手动气道闭塞实验中,在呼吸停止后观察到喉痉挛。这使得临床病例报告的解释变得复杂,因为发作后喉痉挛的存在可能表明喉痉挛介导的缺氧或缺氧介导的喉痉挛。更为不祥的是,无论喉痉挛是开始去饱和还是去饱和后发生喉痉挛,它都能保证死亡的发生,除非在呼吸停止后不久开始进行心肺复苏(当不存在努力呼吸并且心脏严重扩张时)。
定义了一系列事件,其将癫痫发作与猝死联系起来。特别是,癫痫发作诱发的喉痉挛导致气流停止,随后在数十秒内出现ST段抬高、心动过缓和呼吸停止。这些数据是在用于癫痫发作实验的已建立的动物模型(用红藻氨酸处理的氨基甲酸酯麻醉的大鼠)中获得的,而不是在人类中获得的,但这些数据证明了该大鼠模型用于研究喉痉挛和阻塞性呼吸暂停的效用。
图12和图13示出了现有技术的ECG采集电路。参见www.electro-tech-online.com/attachments/untitled-gif.26911/;www.electro-tech-online.com/attachments/ecg-circuit-png.26416/;以及gasstationwithoutpumps.files.wordpress.com/2012/08/dobrev-amp.jpg,其中的每一个均由此全文以引用方式并入本文。
图14、图15和图16示出了现有技术的ECG模拟采集和无线发射器系统的各个方面,参见,Fen Miao、Yayu Cheng、Yi He、Qingyun He和Ye Li,“A Wearable Context-AwareECG Monitoring System Integrated with Built-in Kinematic Sensors of theSmartphone”,Sensors 2015,15(5),11465-11484;doi:10.3390/sl50511465,www.mdpi.com/1424-8220/15/5/11465/htm,其由此全文以引用方式并入本文。整体上。
图14示出了可穿戴ECG采集传感器与智能电话相结合的建议的ECG监测系统的框图。ECG传感器遵循YYl 139-2000标准(用于单通道和多通道电极图的中国制药行业标准,其由EC 13国家标准演变而来)。在ECG采集传感器中,信号由AFE模块的单个芯片进行放大和滤波,然后在MCU模块中,来自AFE的模拟信号被转换为数字信号。在利用压缩算法处理后,数字信号记录在SD卡中或传输到智能电话以进行实时显示。同时,设备中配备USB端口以用于将保存在SD卡中的信号传输到个人计算机,并且然后传输到云平台以进行进一步分析。传输到智能电话的ECG信号以及通过软件中的自动分析方法提供的简要报告或远程服务器提供的专业建议实时显示在屏幕上。智能电话的内置运动传感器用于识别个人的身体活动,并且因此有助于提高检测异常模式的诊断准确性。
在图15中示出了ECG采集设备的传统实现的框图,其中该电路由传统的仪器放大器和Sallen-Key或Nyquist低通滤波器组成,以及一些外部功能电路用于实际的ECG检测。该系统采用占据电路板面积的各种离散组件。
Miao等人提出了一种采用全定制、完全集成和低功耗AFE的架构,其集成了所有的功能电路,如现有技术的图16所示,架构具有输入/输出缓冲器、具有高通功能的全差分放大器(DA)、第二Gm-C低通滤波器、附加放大级、DRL电路、导联检测电路、快速恢复功能以及电源管理模块以提供稳定的工作电压和电流。
由此全文以引用方式明确地并入本文的US 2016/0128209公开了一种示例性硬件平台,其可以用于实现本技术,如图17和图18所示。
参考US 2016/0128209的图17,电子设备100可以构成以下中的至少一个:至少一个AP(应用处理器)910、通信模块920、SIM(用户识别模块)卡924、存储器930、传感器模块940、输入设备950、显示器960(例如显示设备13)、接口970、音频模块980、相机模块991、电源管理模块995、电池996、指示器997和电动机998。AP 910通过驱动操作系统或应用程序来控制连接到AP 910的多个硬件或软件组件,处理包括多媒体数据的各种数据,并且执行计算。AP 910可以实现为例如片上系统(SoC)。根据实施例,AP 910还包括图形处理单元(GPU)。通信模块920(例如,通信接口160)可以结合与经由网络连接到电子设备100的其它电子设备的通信来执行数据发送/接收。根据一个实施例,通信模块920包括以下中的至少一个:蜂窝模块921、Wi-Fi模块923、BT模块925、GPS模块927、NFC模块928和射频(RF)模块929。蜂窝模块921通过通信网络(例如,LTE、LTE-A、CDMA、WCDMA、UMTS、WiMax、GSM、3G、4G或5G等)提供语音呼叫、视频呼叫、文本消息服务或互联网服务。此外,蜂窝模块921通过使用用户识别模块(例如,SIM卡924)来区分和认证通信网络内的电子设备。根据实施例,蜂窝模块921执行AP 910提供的功能中的至少一些。例如,蜂窝模块921可以执行多媒体控制功能中的至少一部分。
蜂窝模块921可以包括通信处理器(CP)。此外,可以通过例如SoC实现蜂窝模块921。尽管诸如蜂窝模块921(例如,通信处理器)、存储器930或电源管理模块995的组件被示出为与图17中的AP 910分离,但是AP 910可以实现为包括上述组件中的至少一些组件(例如,蜂窝模块921)。AP 910或蜂窝模块921(例如,通信处理器)可以将从非易失性存储器和连接到它们中的每一个的其它组件中的至少一个接收的命令或数据加载到易失性存储器并处理所加载的命令或数据。此外,AP 910或蜂窝模块921可以将从其它组件中的至少一个组件接收的数据或由该至少一个组件生成的数据存储在非易失性存储器中。
Wi-Fi模块923、BT模块925、GPS模块927和NFC模块928中的每一个都可以包括例如用于处理通过相应模块发送/接收的数据的处理器。在图17中,蜂窝模块921、WiFi模块923、BT模块925、GPS模块927和NFC模块928示出为彼此分离的块,但是,根据实施例,蜂窝模块921、WiFi模块923、BT模块925、GPS模块927和NFC模块928中的至少一些(例如,两个或更多个)可以包括在一个集成芯片(IC)或者一个IC封装中。例如,可以由单个SoC实现分别对应于蜂窝模块921、Wi-Fi模块923、BT模块925,GPS模块927和NFC模块928的处理器中的至少一些处理器(例如,对应于蜂窝模块921的通信处理器和对应于Wi-Fi模块923的Wi-Fi处理器)。
RF模块929发送和接收数据,例如RF信号。尽管未示出,但是RF模块929包括例如收发器、功率放大器模块(PAM)、频率滤波器或低噪声放大器(LNA)等。此外,RF模块929还包括用于在无线电通信期间在自由空间中发送/接收电磁波的组件,诸如导体或导线。尽管蜂窝模块921、Wi-Fi模块923、BT模块925、GPS模块927和NFC模块928示出为共享图17中的一个RF模块929,但是蜂窝模块921、Wi-Fi模块923、BT模块925、GPS模块927和NFC模块928中的至少一个模块通过单独的RF模块发送和接收RF信号。
SIM卡924是包括用户识别模块的卡,并且可以插入在电子设备的特定部分中形成的槽中。SIM卡924包括唯一的标识信息(例如,集成电路卡标识符(ICCID))或用户信息(例如,国际移动用户识别码(IMSI))。
存储器930(例如,存储器130)包括内部存储器932或外部存储器934。内部存储器932包括以下中的至少一个:易失性存储器(例如,动态RAM(DRAM)、静态RAM(SRAM)和同步动态RAM(SDRAM)等)和非易失性存储器(例如,一次性可编程ROM(OTPROM)、可编程ROM(PROM)、可擦除和可编程ROM(EPROM)、电可擦除和可编程ROM(EEPROM)、掩模型ROM、快闪ROM、NAND闪存存储器和NOR闪存存储器等)。
根据实施例,内部存储器932是固态驱动器(SSD)。外部存储器934还可以包括闪存驱动器,例如紧凑型闪存((CF)、安全数字(SD)、微型安全数字(Micro-SD)、迷你安全数字(Mini-SD)、极限数字(xD)和记忆棒等。外部存储器934可以通过各种接口在功能上连接到电子设备100。根据实施例,电子设备100还可以包括存储设备(或存储介质),诸如硬盘驱动器。
传感器模块940测量物理量或检测电子设备100的操作状态,并且将测量的或检测到的信息转换为电信号。传感器模块940包括例如以下中的至少一个:手势传感器940A、陀螺仪传感器940B、大气压力传感器940C、磁性传感器940D、加速度传感器940E、握持传感器940F、接近传感器940G、颜色传感器940H(例如,红、绿、蓝(RGB)传感器器)、生物测定传感器940I、温度/湿度传感器940J、照明传感器940K以及紫外线(UV)传感器940M。附加地或替代地,传感器模块940包括例如E-nose传感器(未示出)、肌电图(EMG)传感器(未示出)、脑电图(EEG)传感器(未示出)、心电图(ECG)传感器(未示出)、红外(IR)传感器、虹膜传感器(未示出)和指纹传感器(未示出)等。传感器模块940还包括用于控制包含有一个或多个传感器的控制电路。
输入设备950包括触摸面板952、(数字)笔传感器954、键956或超声波输入设备958。触摸面板952通过例如电容方案、电阻方案、红外方案和超声方案中的至少一种来识别触摸输入。触摸面板952还包括控制电路。电容方案触摸面板识别物理接触或接近。触摸面板952还包括触觉层。在这种情况下,触摸面板952向用户提供触觉反应。
可以例如使用与接收用户的触摸输入的方法相同或类似的方法或使用单独的识别表来实现(数字)笔传感器954。键956包括例如物理按钮、光学键或键盘。超声输入设备958具有输入工具,其产生超声信号,使得电子设备100使用麦克风988感测声波并识别数据,并且能够进行无线识别。根据实施例,电子设备100通过使用通信模块920从与其连接的外部设备(例如,计算机或服务器)接收用户输入。
显示器960(例如,显示设备13)包括面板962、全息图设备964或投影仪966。面板962可以是例如液晶显示器(LCD)或有源矩阵有机发光二极管(AM-OLED)等。面板962可以被实施为例如是柔性的、透明的或可穿戴的。面板962还可以与触摸面板952一起被配置为一个模块。全息图964可以通过使用光的干涉在空中显示立体图像。投影仪966可以将光投射到屏幕上以显示图像。例如,屏幕可以位于电子设备100的内部或外部。根据一个实施例,显示器960还可以包括用于控制面板962、全息图设备964或投影仪966的控制电路。
接口970包括例如高清晰多媒体接口(HDMI)972、通用串行总线(USB)974、光接口976或D超小型(D-sub)978。另外地或另选地,接口970包括例如移动高清链路(MHL)接口,安全数字(SD)卡/多媒体卡(MMC)接口或红外数据协会(IrDA)标准接口。
音频模块980双向转换声音和电信号。音频模块980的组件中的至少一些组件可以包括在输入/输出接口中。音频模块980处理通过例如扬声器982、接收器984、耳机986或麦克风988等输入或输出的语音信息。
相机模块991是可以拍摄图像和动态图像的设备。根据实施例,相机模块291包括一个或多个图像传感器(例如,前传感器或后传感器)、镜头(未示出)、图像信号处理器(ISP)(未示出)或闪光灯(未示出)(例如,LED或氙灯)。
电源管理模块995管理电子设备100的电源。尽管未示出,但是电源管理模块995包括例如电源管理集成电路(PMIC)、充电器集成电路(IC)、或电池量表或燃料量表。PMIC可以安装到例如集成电路或SoC半导体。充电方法可以分为有线充电方法和无线充电方法。充电器IC为电池充电,并防止过电压或过电流从充电器流出。根据实施例,充电器IC包括用于有线充电方法和无线充电方法中的至少一种方法的充电器IC。磁共振方案、磁感应方案或电磁方案可以例示为无线充电方法,并且可以加入用于无线充电的附加电路,诸如线圈回路电路、谐振电路和整流电路等。电池燃料量表测量例如电池996的剩余量,或充电期间的电压、电流或温度。电池996存储或产生电力,并且使用存储的或产生的电力向电子设备100供电。电池996可以包括例如可充电电池或太阳能电池。
指示器997指示电子设备100或电子设备900的一部分(例如,AP 910)的特定状态(例如,启动状态、消息状态、充电状态等)。电动机998将电信号转换为机械振动。尽管未示出,但是电子设备100包括用于支持移动TV的处理单元(例如,GPU)。用于支持移动TV的处理单元根据数字多媒体广播(DMB)、数字视频广播(DVB)和媒体流等标准处理媒体数据。
根据本公开各种实施例的电子设备的上述组件可以由一个或多个组件形成,并且可以基于电子设备的类型来改变对应组件元件的名称。根据本公开的电子设备可以包括前述组件中的一个或多个,或者还可以包括其它附加组件,或者可以省略前述组件中的一些。此外,根据本公开的各种实施例的电子设备的组件中的一些可以组合以形成单个实体,并且因此可以在组合之前等效地执行相应元件的功能。
本公开的各种实施例中所使用的“模块”可以意指例如包括硬件、软件和固件中的一个或者硬件、软件和固件中的两个或更多个的组合的“单元”。“模块”可以与术语互换,诸如单元、逻辑组(例如,体现在非暂时性计算机可读介质中)、逻辑块、组件或电路。“模块”可以是集成组件元件或其一部分的最小单位。“模块”可以是用于执行一个或多个功能或其一部分的最小单位。“模块”可以机械地或电子地实现。例如,根据本公开的各种实施例的“模块”可以包括专用集成电路(ASIC)芯片、现场可编程门阵列(FPGA)和可编程逻辑设备中的至少一个以执行以下已知或将开发的操作。
US 2016/0128209的图18是示出包括电子设备100的网络环境的图,该电子设备100包括总线110、处理器120、存储器130、输入/输出接口140、显示器150、通信接口160和应用操作模块170。总线110是将上述组件彼此连接并且在上述组件之间传送通信(例如,控制消息)的电路。例如,处理器120可以通过总线110从前述其它元件(例如,存储器130、输入/输出接口140、显示器150、通信接口160和应用操作模块170)接收指令,解密所接收的指令,以及根据解密的指令执行计算或数据处理。
存储器130存储从处理器120或其它元件(例如,输入/输出接口140、显示器150、通信接口160或应用操作模块170等)接收的指令或数据或由处理器120或其它元件生成的指令或数据。存储器130包括编程模块,诸如内核130a、中间件130b、API(应用程序编程接口)130c或应用程序130d。上述编程模块中的每个编程模块可以由软件、固件和硬件或其组合形成。
内核130a控制或管理用于执行由其它编程模块(例如,中间件130b、API 130c或应用程序130d)实现的操作或功能的系统资源(例如,总线110、处理器120或存储器130等)。此外,内核130a提供接口,其中中间件130b、API 130c或应用程序130d可以通过该接口访问和控制或管理电子设备100的各个组件。
中间件130b用作中介,其允许API 130c或应用程序130d与内核130a通信并与内核130a交换数据。此外,关于从应用程序130d接收操作的请求,中间件130b通过使用例如一种确定关于应用程序130d中的至少一个应用程序使用电子设备100的系统资源(例如,总线110、处理器120或存储器130等)的序列的方法来控制(例如,调度或负载平衡)操作请求。
API 130c是应用程序130d控制从内核130a或中间件130b提供的功能的接口,并且包括例如用于文件控制、窗口控制、图像处理或文本控制的至少一个接口或功能(例如,指令)。
根据各种实施例,应用程序130d包括短消息服务(SMS)/多媒体消息服务(MMS)应用程序、电子邮件应用程序、日历应用程序、警报应用程序、健康护理应用程序(例如,用于测量运动量或血糖量的应用程序)或环境信息应用程序(例如,用于提供大气压力、湿度或温度的应用程序)等。附加地或替代地,应用程序130d可以是与电子设备100和外部电子设备104之间的信息交换有关的应用程序。与信息交换相关的应用程序可以包括例如用于将特定信息发送到外部电子设备的通知中继应用程序,或者用于管理外部电子设备的设备管理应用程序。
例如,通知中继应用程序可以包括将在电子设备100的其它应用程序(例如,SMS/MMS应用程序、电子邮件应用程序、健康护理应用程序或环境信息应用程序)中生成的通知信息传送到外部电子设备104的功能。附加地或替代地,通知中继应用程序可以从例如外部电子设备104接收通知信息,并且可以将接收的通知信息提供给用户。设备管理应用程序管理(例如,安装、删除或更新)例如与电子设备100通信的外部电子设备104的至少一些功能(例如,打开或关闭外部电子设备(或某些元件),或调整显示器的亮度(或分辨率))、在外部电子设备中执行的应用程序、或者由外部电子设备提供的服务(例如,电话呼叫服务或消息服务)。
根据各种实施例,应用程序130d包括根据外部电子设备104的属性(例如,设备类型)指定的应用程序。例如,在外部电子设备是MP3播放器的情况下,应用程序130d包括与音乐的重放有关的应用程序。类似地,当外部电子设备是移动医疗设备时,应用程序130d包括与保健相关的应用程序。根据实施例,应用程序130d包括为电子设备100指定的应用程序或从不同电子设备(例如,服务器106或外部电子设备104)接收的应用程序中的至少一个应用程序。
输入/输出接口140将通过输入/输出设备(例如,传感器、键盘或触摸屏)从用户输入的命令或数据通过例如总线110发送到处理器120、存储器130、通信接口160或应用程序操作模块170。例如,输入/输出接口140向处理器120提供通过触摸屏输入的用户触摸的数据。此外,通过输入/输出设备(例如,扬声器或显示器),输入/输出接口140输出通过总线110从处理器120、存储器130、通信接口160或应用操作模块170接收的命令或数据。例如,输入/输出接口140通过扬声器将通过处理器120处理的语音数据输出给用户。
显示器150为用户显示各种信息(例如,多媒体数据或文本数据)。
通信接口160在电子设备100和不同的电子设备(例如,外部电子设备104或服务器106)之间建立通信连接。例如,通信接口160通过无线或有线通信连接到网络162,以与外部电子设备通信。无线通信包括例如以下中的至少一个:Wi-Fi、Wi-Fi直连、蓝牙(BT)、近场通信(NFC)、全球定位系统(GPS)或蜂窝通信(例如,LTE、LTE-A、CDMA、WCDMA、UMTS、WiMax、GSM、3G、4G、5G等)。有线通信包括例如以下中的至少一个:通用串行总线(USB、USB 2.0、USB3.0、USB 3.1等)、高清晰多媒体接口(HDMI)、以太网(802.3等)、推荐标准232(RS-232)和普通老式电话服务(POTS)端口/接口。
根据实施例,网络162可以是电信网络。通信网络可以包括计算机网络、互联网、物联网和电话网络中的至少一个。根据实施例,用于电子设备100和外部电子设备之间的通信的协议(例如,传输层协议、数据链路层协议或物理层协议)可以由应用程序130d、API130c、中间件130b、内核130a和通信接口160中的至少一个来支持。
根据实施例,应用程序操作模块170通过执行由电子设备100实现的操作(或功能)中的至少一个来支持电子设备100的驱动。例如,服务器106可以包括能够支持在电子设备100中实现的应用程序操作模块170的通信控制服务器模块108。例如,通信控制服务器模块108可以包括应用程序操作模块170的至少一个组件,并且可以执行(例如,执行作为代理)由应用程序操作模块170执行的操作中的至少一个操作。
应用程序操作模块170处理从其它组件(例如,处理器120、存储器130、输入/输出接口140或通信接口160)获得的信息中的至少一些信息,并且以各种方式利用它们。例如,应用程序操作模块170通过使用处理器120或其独立地控制电子设备100的至少一些功能,使得电子设备100可以与不同的电子设备(例如,外部电子设备104或服务器106)互通。连接控制模块170可以集成到处理器120中。根据实施例,应用程序操作模块170的至少一个组件可以包括在服务器106中(例如,通信控制服务器模块108)并且可以具有由服务器106支持的至少一个操作,该操作由应用程序操作模块170执行。
虽然已经利用示例性实施例描述了本公开,但是可以向本领域技术人员建议各种改变和修改。本公开旨在涵盖落入所附权利要求的范围内的此类改变和修改。
参考文献
本文引用的每篇参考文献(包括前述那些参考文献)均由此全文以引用方式并入本文。
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Claims (21)
1.一种用于检测阻塞性呼吸暂停的方法,包括:
接收来自哺乳动物的包括呼吸肌肉的肌电活动的生物电信号;
处理所述生物电信号以分离肌电活动;
基于所分离的肌电活动确定吸气努力的计时和幅度;
确定吸气努力的基线幅度;
将吸气努力的幅度与吸气努力的所确定的基线幅度进行比较;以及
如果一系列吸气努力具有大于所述基线幅度的随时间增加的幅度,则确定发生阻塞性呼吸暂停。
2.根据权利要求1所述的方法,还包括:确定吸气努力的基线计时范围;以及将吸气努力的所述计时与吸气努力的所确定的基线计时进行比较,其中如果一系列吸气努力具有大于所述基线幅度的随时间增加的幅度以及在所述基线计时范围内的计时,则确定发生阻塞性呼吸暂停。
3.根据权利要求1所述的方法,其中所述生物电信号是心电图信号。
4.根据权利要求3所述的方法,其中在确定发生阻塞性呼吸暂停之前,通过一系列至少三次吸气努力确定吸气努力的所述计时和幅度。
5.根据权利要求1所述的方法,其中所述生物电信号是脑电图信号。
6.根据权利要求1所述的方法,其中所述生物电信号是从单个末端获取的。
7.根据权利要求1所述的方法,还包括:响应于确定发生阻塞性呼吸暂停而产生听觉警报。
8.根据权利要求1所述的方法,还包括:响应于确定发生阻塞性呼吸暂停而选择性地无线传送信号。
9.根据权利要求1所述的方法,其中:
所述接收来自哺乳动物的包括肌电活动的生物电信号包括:接收心电图信号、脑电图信号和肌电信号中的至少一种;以及
所述处理所述生物电信号以分离肌电活动包括至少使所述生物电信号经受带通滤波器,所述带通滤波器具有在约300Hz和1kHz之间的通带。
10.根据权利要求1所述的方法,其中所述处理所述生物电信号以分离肌电活动包括确定通带内的信号功率随时间的变化。
11.根据权利要求1所述的方法,其中所述将吸气努力的幅度与吸气努力的所确定的基线幅度进行比较包括将吸气努力的一系列幅度和计时与表示吸气努力的幅度和计时的正常范围的基线视窗进行比较。
12.根据权利要求1所述的方法,其中如果一系列吸气努力具有大于所述基线幅度的随着时间增加的幅度,则确定发生阻塞性呼吸暂停包括:确定三次连续吸气努力是否具有大于阈值的幅度,所述阈值具有稳定幅度和增加的幅度中的至少一个,而吸气努力之间的间期在正常范围内。
13.一种确定阻塞性呼吸暂停的方法,包括:
确定呼吸间期内相应呼吸率的基线心跳间间期和正常变化范围;
确定患者的心跳间间期和呼吸率;
确定一系列至少一个心跳间间期的开始,所述一系列至少一个心跳间间期超出所述正常变化范围,并低于所述相应的呼吸率的所述基线心跳间间期;以及
如果所述一系列至少一个心跳间间隔的多次开始在所述呼吸间期内大于阈值,则确定阻塞性呼吸暂停的开始,所述一系列至少一个心跳间期超出所述正常变化范围,并低于所述相应的呼吸率的所述基线心跳间间期。
14.根据权利要求12所述的方法,其中所述阈值是三。
15.根据权利要求12所述的方法,其中基于生物电信号确定所述心跳间间期和所述呼吸率。
16.根据权利要求14所述的方法,其中所述生物电信号是心电图信号、脑电图信号和肌电信号中的至少一种。
17.根据权利要求14所述的方法,其中所述生物电信号是从单个末端获取的。
18.根据权利要求12所述的方法,还包括:响应于确定所述阻塞性呼吸暂停的开始而选择性地产生听觉警报和无线通信中的至少一种。
19.根据权利要求12所述的方法,还包括:响应于确定所述阻塞性呼吸暂停的开始而通过电话网络自动生成e911(增强型911)呼叫。
20.根据权利要求12所述的方法,其中通过确定心电图的R-R间期来确定所述心跳间间期,所述方法还包括:
建立视窗,所述视窗区分所述相应呼吸率的正常心跳间间期和短心跳间间期;以及
记录超出所述相应呼吸率的所述视窗的心跳间间期的时间。
21.一种用于检测阻塞性呼吸暂停的系统,包括:输入,所述输入被配置为接收来自哺乳动物的生物电信号以及定义心跳间间期的信息,所述生物电信号包括呼吸肌肉的肌电活动中的至少一种;输出,所述输出用于根据确定发生阻塞性呼吸暂停来传递信号;以及至少一个处理器,所述至少一个处理器被配置为以下中的至少之种:(a)(1)处理所述生物电信号以分离肌电活动;(2)基于所分离的肌电活动来确定吸气努力的基线幅度;以及(3)如果一系列吸气努力具有随时间增加的幅度,并大于根据所分离的肌电活动确定的吸气努力的所述基线幅度,则确定发生阻塞性呼吸暂停;以及(b)(1)确定呼吸间期内相应呼吸率的基线心跳间间期和正常变化范围;(2)确定患者的心跳间间期和呼吸率;(3)确定一系列心跳间间期的开始,所述一系列心跳间期超出所述正常变化范围,并低于所述相应呼吸率的所述基线心跳间间期;以及(4)如果在所述呼吸间期内低于所述相应呼吸率的所述基线心跳间间期的所述一系列至少一个心跳间间期的多次开始超过阈值,则确定阻塞性呼吸暂停的开始。
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