CN103635130A - 使用多层分析的远程数据监控和收集系统 - Google Patents
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Abstract
系统在高分辨率和/或高数据速率下从源收集和存储数据（“更详细的数据”）并且通过无线网络将低分辨率和/或下采样版本的数据（“不太详细的数据”）发送到远程服务器。服务器自动分析不太详细的数据以检测异常，例如，心律失常、地震或结构构件的损坏。使用双层分析方案，其中第一层比第二层具有更少特异性。如果第一层分析检测或怀疑异常，那么服务器向数据收集器发信号以发送对应于与异常相关联的时段的更详细的数据。更多特异性的第二层分析更详细的数据以验证异常。服务器也可以存储接收数据并且例如通过图形或表格显示将接收数据提供给用户。
Description
技术领域
本发明涉及远程数据监控和数据收集系统，更具体来说，涉及使用多层分析的远程控制的数据监控和收集系统。
背景技术
远程数据监控异常行为，例如，远程监控地震传感器、火山传感器、油井或天然气井、气象站、海洋浮标等，造成数据通信挑战，特别是在监控项目位于远离电信基础设施或常规的电力来源的时候。例如，远程监控非卧床病人使医生能够检测或诊断心脏问题（例如，心律失常），这些心脏问题可能只产生一过性症状，并且因此在病人拜访医生、办公室时可能并不明显。已使用几种形式的心血管事件监控器。
“霍尔特（Holter）”监控器由病人佩戴并且在一段时间内（通常至少24小时，并且在一些情况下多达两个星期）收集和存储数据。在已收集数据后，通常将霍尔特监控器带到或送到医生的办公室、实验室等，并且从监控器检索数据并进行分析。霍尔特监控器价格相对低廉，但是其不能用于病人数据的实时分析，这是因为数据是分析几小时、几天或几周后才被收集。
前驱症状（循环记忆）事件监控器使心脏数据的更及时的分析变得可能。此设备在“循环”存储设备中收集和存储病人数据。事件监控器不断地用新收集的数据覆盖先前存储数据。事件监控器可以包括按钮，如果病人觉得不舒服或以其它方式检测到与心脏有关的异常，那么病人被指示启动按钮。作为响应，事件监控器继续在很短的一段时间内记录数据，然后停止记录，由此在跨越按钮启动的时段内保留数据，即，保留数据代表从用户启动按钮前的（通常）几分钟扩展到用户启动按钮后的（通常）几分钟的时段。然后，可以通过调制解调器和电话连接将保留数据发送到医生的办公室或实验室进行分析。尽管此事件监控器可以促进在时间上更接近于病人检测异常来分析病人数据，但是依靠病人启动设备然后发送数据可能是有问题的。
一些事件监控器自动检测某些心律失常，并且作为响应，记录心电图（ECG）数据。对于显著的心律失常，自动事件监控器被认为比手动触发的心血管事件监控器更灵敏但具更少特异性。然而，这些设备仍然依靠病人发送记录数据进行分析，并且在疑似心律失常的检测与数据传输之间仍然存在延迟。
移动心血管遥测（MCT）指的是涉及能够在几天内连续测量心率和心律的无创性动态心血管事件监控器的技术。例如，宾夕法尼亚州费城的CardioNet提供商标名为“Mobile Cardiac Outpatient Telemetry”（MCOT）的MCT设备。MCOT设备包括自动ECG心律失常检测器。MCOT设备耦合到蜂窝电话设备以将自动检测的异常ECG波形立即传输到远程监控中心，然后远程监控中心可以向医师报警。MCOT设备也包括能够存储多达96小时的ECG波形数据的存储器，可以在每一天结束时通过标准电话线将ECG波形数据传输到远程监控中心。尽管将关于自动检测的心律失常的数据立即发送到远程监控中心而无需病人行动，但是用于执行MCOT设备中的自动ECG分析所需的计算资源和相应的电力（电池）是重要的。
一些MCT设备将所有收集的ECG数据不断发送到远程监控中心进行分析。这些MCT设备通常不执行自己的任何ECG分析。尽管不需要病人启动的行动，但是由MCT无线设备传输的大量的数据使用于传送数据的无线信道拥塞。此外，在远程监控中心需要大量的计算资源来分析接收数据的连续流，尤其是在单个数据中心监控许多病人的时候。
美国专利公布号2010/0298664公开一种无线ECG数据收集和分析系统。
美国专利号7,996,187公开一种个人健康监控器，其收集和处理生理数据并且将被处理的数据无线传输到远程实体。
美国专利公布号2009/0076405公开一种无线呼吸监控系统。在收到通知后，医疗服务提供方、远程监控系统或医学治疗设备可以在病人佩戴的监控设备中触发较高的数据采样率，并且使用此后收集的较高的采样率数据来验证警戒状态。
美国专利号7,801,591公开一种医疗信息管理系统，其基于用户需要和复杂程度以不同层次的分析显示病人信息。
发明内容
本发明的实施方案提供一种用于远程服务器的多层数据收集系统。系统包括数字数据输入源和收发器总成。收发器总成包括存储器、控制器和无线收发器。收发器总成通信耦合到数字数据输入源。收发器总成被配置成从数字数据输入源接收数据。收发器总成也被配置成在存储器中存储接收数据。存储数据被称为“更详细的数据”。收发器总成被配置成通过无线收发器将接收数据的子集（被称为“不太详细的数据”）发送到远程服务器。被发送到远程服务器的不太详细的数据的特征在于：比在相应的时段内存储在存储器中的更详细的数据具有更低的分辨率，和/或比在相应的时段内存储在存储器中的更详细的数据具有更低的采样率，和/或从与在相应的时段内存储在存储器中的更详细的数据不同的一组传感器被接收。响应于来自远程服务器的信号，收发器总成被配置成从存储器提取更详细的数据的至少一部分。另外，响应于来自远程服务器的信号，收发器总成被配置成将提取的更详细的数据发送到远程服务器。
被发送到远程服务器的不太详细的数据的特征在于：比在相应的时段内存储在存储器中的更详细的数据具有更低的分辨率，和/或比在相应的时段内存储在存储器中的更详细的数据具有更低的采样率。
远程服务器可以被配置成接收由收发器总成发送的不太详细的数据并且自动分析接收的不太详细的数据以指示异常。如果指示异常，那么远程服务器可以被配置成将信号自动发送到收发器总成。
异常可以是或包括地震；海啸；天然气井、油井或矿井内的不安全条件；恶劣天气；建筑物的结构构件中的不安全的机械条件；建筑物的结构构件的损坏；地质结构内的不安全条件；超过预定值的核辐射水平；或爆炸；减压。
远程服务器也可以被配置成接收更详细的数据并且自动分析接收的更详细的数据以验证指示的异常。
远程服务器可以被配置成根据第一分析技术分析不太详细的数据并且根据第二分析技术分析更详细的数据。第二分析技术可以比第一分析技术具有异常的更高特异性。
远程服务器可以被配置成显示第一用户界面，第一用户界面被配置成接受至少一个用户指定的标准。远程服务器可以被配置成基于满足用户指定的标准的不太详细的数据的至少一部分而自动分析接收的不太详细的数据以指示异常。
远程服务器可以被配置成显示第一用户界面，第一用户界面被配置成接受至少一个用户指定的标准，并且基于满足用户指定的标准的更详细的数据的至少一部分而自动分析接收的更详细的数据以验证指示的异常。
无线收发器可以包括蜂窝电话。
无线收发器总成可以包括通过短距离无线链路耦合到无线收发器的蜂窝电话。蜂窝电话可以被配置成：在存储器中存储更详细的数据；将不太详细的数据发送到远程服务器；响应于信号，从存储器提取更详细的数据的至少部分并且通过无线载波网络将提取的更详细的数据发送到远程服务器。
系统也可以包括被配置成通信耦合到无线载波网络的蜂窝电话。蜂窝电话可以被配置成通过无线收发器接收由收发器总成发送的数据并且通过无线载波网络将接收数据发送到远程服务器。
系统也可以包括被配置成由蜂窝电话执行的应用程序，蜂窝电话被配置成通信耦合到无线载波网络。应用程序可以被配置成通过无线收发器接收由收发器总成发送的数据并且通过无线载波网络将接收数据发送到远程服务器。
远程服务器可以被配置成通过第一用户界面接受用户指定的数据收集参数。响应于接受用户指定的数据收集参数，远程服务器可以被配置成将数据收集参数发送到收发器总成。收发器总成可以被配置成接收数据收集参数，并且响应于接收到数据收集参数而改变此后发送到远程服务器的不太详细的数据的分辨率和/或采样率。
远程服务器可以被配置成根据从收发器总成接收的不太详细的数据在第一用户界面中生成第一显示区。响应于用户输入，远程服务器可以被配置成根据从收发器总成接收并且对应于与在第一显示区中显示的数据相关联的时间的更详细的数据的至少一部分，在第一用户界面中生成第二显示区。
响应于用户输入，远程服务器可以进一步被配置成将信号发送到收发器总成。
本发明的另一实施方案提供一种用于远程监控数据的多层方法。根据方法，接收数据。在存储器中存储接收数据。存储数据被称为“更详细的数据”。将接收数据的子集（被称为“不太详细的数据”）无线发送到远程服务器。被发送到远程服务器的不太详细的数据的特征在于：比在相应的时段内存储在存储器中的更详细的数据具有更低的分辨率，和/或比在相应的时段内存储在存储器中的更详细的数据具有更低的采样率，和/或从与在相应的时段内存储在存储器中的更详细的数据不同的一组传感器被接收。响应于来自远程服务器的信号，从存储器提取更详细的数据的至少一部分。将提取的更详细的数据发送到远程服务器。
被发送到远程服务器的不太详细的数据的特征在于：比在相应的时段内存储在存储器中的更详细的数据具有更低的分辨率，和/或比在相应的时段内存储在存储器中的更详细的数据具有更低的采样率。
另外，可以在远程服务器上接收不太详细的数据。可以在远程服务器上自动分析接收的不太详细的数据以指示异常。如果指示异常，那么可以自动发送信号。
远程服务器可以接收更详细的数据，并且可以在远程服务器上自动分析接收的更详细的数据以验证指示的异常。
分析不太详细的数据可以包括根据第一分析技术分析不太详细的数据。分析更详细的数据可以包括根据第二分析技术分析更详细的数据。第二分析技术可以比第一分析技术具有异常的更高特异性。
本发明的又一实施方案提供一种用于远程服务器的多层数据收集系统。系统包括数字数据输入源和传输器总成。传输器总成包括存储器、控制器和无线传输器。传输器总成通信耦合到数字数据输入源。传输器总成被配置成从数字数据输入源接收数据并且在存储器中存储接收数据。存储数据被称为“更详细的数据”。传输器总成也被配置成自动分析接收数据的子集（被称为“不太详细的数据”）以指示异常。不太详细的数据的特征在于：比在相应的时段内存储在存储器中的更详细的数据具有更低的分辨率，和/或比在相应的时段内存储在存储器中的更详细的数据具有更低的采样率，和/或从与在相应的时段内存储在存储器中的更详细的数据不同的一组传感器被接收。如果指示异常，那么传输器总成被配置成从存储器自动提取更详细的数据的至少一部分并且将提取的更详细的数据发送到远程服务器。
不太详细的数据的特征在于以下至少一个：比在相应的时段内存储在存储器中的更详细的数据具有更低的分辨率，和/或比在相应的时段内存储在存储器中的更详细的数据具有更低的采样率。
远程服务器可以被配置成接收更详细的数据并且自动分析接收的更详细的数据以验证指示的异常。
传输器总成可以被配置成根据第一分析技术分析不太详细的数据，并且远程服务器可以被配置成根据第二分析技术分析更详细的数据。第二分析技术可以比第一分析技术具有异常的更高特异性。
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通过结合附图参看具体实施方案的以下详细描述，将更充分地理解本发明，其中：
图1为本发明的实施方案的示意性方框图。
图2为本发明的实施方案的更详细的示意性方框图。
图3为图示根据本发明的实施方案的生理传感器的一种可能的组合和传感器在病人的躯干上的可能放置的示意图。
图4含有根据本发明的实施方案的代表从图3的传感器收集并且存储在存储器中的详细数据的假设的ECG波形。
图5含有根据本发明的实施方案的代表从图3的传感器收集并且发送到远程服务器的数据的不太详细的版本的波形。
图6含有根据本发明的实施方案的代表收发器总成响应于来自服务器的请求而发送到远程服务器的更详细的数据的波形。
图7含有根据本发明的实施方案的示例性分辨率、采样率和传输工作周期的表。
图8含有根据本发明的实施方案的列出几个病人的活动水平的示例性阈值的表。
图9为图示根据本发明的实施方案的用于计算呼吸率的过程的流程图。
图10为本发明的实施方案的示意性方框图。
具体实施方式
根据本发明的实施方案，公开方法和装置，其用于从监控项目（例如，非卧床病人）本地收集和本地存储数据、只将收集的数据的适当的子集无线发送到远程中心服务器，以及实时地自动分析发送的数据。收集的数据的发送的子集不如由本地数据收集器收集和存储的数据详细。
中心服务器使用双层分析方法。如果执行高灵敏度但低特异性分析的第一层在收集的数据的接收的子集中检测到可能的异常（例如，心律失常），那么服务器请求数据收集器追溯发送收集器先前存储的更详细的数据，即，大约在疑似异常时的更详细的数据。
第二层执行更详细的数据的高特异性分析以确认或反驳（“验证”）疑似异常。因此，通过只在需要验证疑似异常时发送详细数据，使用于发送数据的无线信道的整体利用率保持在较低水平。此外，因为数据收集器不执行数据分析，所以使数据收集器的电力（电池）和计算资源需求保持在较低水平。
因此，明显地，本发明的实施方案使远程服务器能够主要对收集的数据的不太详细的子集操作并且在需要验证疑似异常时追溯获得更详细的数据。相比之下，没有已知的现有技术数据监控器在本地存储详细收集的数据并且只将收集的数据的子集发送到远程服务器。没有已知的现有技术远程服务器响应于检测到疑似异常而请求较早时段的更详细的数据（“追溯请求数据”），然后使用更详细的数据来验证疑似异常。
收集的数据的“子集”意指少于所有收集的数据。例如，子集可以为收集的数据的下采样（较低采样率）或量化（不太准确的样本）版本。子集可以包括来自一个或多个传感器的数据或一个或多个类型的数据，例如，地震活动性、地震倾斜、温度、压力、风速、风向、水温、流率、波高、心率、ECG波形、呼吸率、SpO2、血压、身体运动（例如，由加速计提供）。更详细的数据可以包括来自所有相同、一些相同或不同的传感器的数据或不同类型的数据。SpO2为附着到循环血液系统中的血红蛋白细胞的氧含量的测量。SpO2通常是作为百分比给出，正常是96%左右。SpO2中的“S”代表“饱和度”。
图1为本发明的实施方案的示意性方框图。公开的实施方案涉及远程监控非卧床病人，更具体来说，涉及远程监控和检测心律失常或其它与健康相关的问题。然而，本文公开的原理适用于许多其它领域，例如，石油和天然气勘探、天气预报、地震或龙卷风预警等。本文公开的原理有利地适用于以下情形，即，需要异常数据或行为（统称为异常）的检测，但是远程收集足够的数据以用高灵敏度（几个假阴性）和高选择性（几个假阳性）准确地检测异常是困难的。在图1中，将数据收集器和一组生理传感器（共同识别为100）分配给每个监控病人。将生理传感器附着到病人，并且将从传感器收集的数据存储在数据收集器100内的存储器103中。也将对应于收集数据所在的时间的时间戳，或其它适合的数据定时信息存储在存储器103中。如果存储器103已满或达到预定的充满度，那么数据收集器100开始覆盖先前存储的数据（从最旧的数据开始）。因此，存储器103以滚动方式存储最近收集的数据。
数据收集器100包括或耦合到适合的无线收发器104，例如，蜂窝电话。例如，通过蜂窝电话网络108将包括关于何时收集数据的信息的收集的数据的子集（识别为“不太详细的数据”106）无线发送到中心远程服务器107。不太详细的数据106可以为收集的数据的下采样版本。即，不太详细的数据106可以具有比收集和存储的数据更低的采样率。例如，只有收集的数据的每第N个样本可以包括在不太详细的数据106中，其中N为提供足够用于第一层分析的采样率的整数或有理分式。可选地或替代地，不太详细的数据106可以为收集的数据的量化版本。即，尽管不太详细的数据106足够用于第一层分析，但是不太详细的数据106可能被四舍五入或另外包括比收集的数据更少数字的准确性。
中心服务器107可以服务于许多每个病人的数据收集器100。中心服务器107执行不太详细的数据106的高灵敏度分析109。高灵敏度分析109被配置，使得其具有生成假阴性结果的低概率。即，高灵敏度分析109不可能没有检测到实际心律失常。然而，为了实现这个高水平的灵敏度，高灵敏度分析109可能生成相对大量的假阳性结果，即，第一分析层可能具有低特异性。
然而，由于一些原因，相对大量的假阳性结果是可接受的，这些原因包括通过无线信道108只发送收集的生理数据的相对较小子集，由此保存无线信道的载运能力。保存无线信道的载运能力可能对于通过无线信道108支持大量的每个病人的数据收集器100和/或使无线信道108能够载运其它类型的通信量（例如，正文消息、视频流和语音电话呼叫）很重要，其中大多数或所有的通信量可能与这里描述的生理监控无关。因此，至少在概念上，假阳性至少部分地被用来交换增加的无线信道容量。此外，如下所述，第二层的分析滤除大部分或全部的假阳性。
如果高灵敏度分析109检测到疑似心律失常，那么高灵敏度分析109将请求112发送到数据收集器100。请求112识别感兴趣的时段，例如，与收集导致怀疑的数据所在的时间紧密相关的时段。响应于请求112，数据收集器100在被请求的时段内从存储器103提取更详细的数据并且将更详细的数据115发送到中心服务器107，然后对更详细的数据115执行高特异性分析118。优选地，因为第二分析层118也具有高灵敏度，所以其具有生成假阴性结果的低概率。
高特异性分析118被配置，使得其具有生成假阳性结果的低概率。即，在没有实际发生心律失常时，高特异性分析118不可能指示心律失常。如果高特异性分析118验证发生心律失常，那么可能提出警报或可能显示信息（121），例如，以向医师或技师报警。
为了提供具有高特异性和高灵敏度的结果，高特异性分析118需要更详细的数据115，也通常比高灵敏度分析109消耗更多的计算资源。请求112和发送115更详细的数据利用无线信道容量的一部分。然而，只是相对很少发生这个利用，即，在高灵敏度分析109检测到疑似心律失常时。另外，高特异性分析118消耗相对大量的计算资源。此外，然而，只是相对很少发生这个消耗。
因此，至少在概念上，双层分析109和118可以被看作一方面涉及两个单独的分析层和偶尔的高无线信道以及计算资源利用率的复杂性与另一方面无线信道和计算资源利用率的整体减少之间的权衡。本文公开的总方案比现有技术方案需要在每个病人的数据收集器100上的更少的计算资源和相应更少的功率（电池），现有技术方案试图在每个病人的设备上分析收集的数据并且只在检测到心律失常时通知中心系统。另外，总方案比现有技术系统使用更少的无线信道容量和更少的中心分析服务器资源，现有技术系统将所有收集的数据的恒流发送到中心服务器进行分析。
此外，总方案非常适合于在按需提供计算资源的“云计算”环境中实施。因此，在一些实施方案中，高特异性分析118所需的额外的计算资源不需要被预分配，并且因此使大部分时间闲置。作为替代，每当需要计算资源时，可以动态和自动利用、请求或调度高特异性分析118的计算资源。此云计算环境可购自商标名为Amazon Elastic Compute Cloud（Amazon EC2）的Amazon Web Services LLC和来自RightScale,Inc.的RightScale云管理。
图2为本发明的实施方案的示意性方框图，其示出比图1更多的细节。一个或多个生理传感器200耦合到收发器总成203。可以通过短距离无线系统（例如，蓝牙收发器）提供耦合。或者，可以通过导线或光缆提供耦合。如上所述，收发器总成203包括存储器103和长距离无线收发器104（例如，蜂窝电话收发器）。可以用任何适合的无线收发器（例如，WiFi收发器（未示出））代替长距离无线收发器104。
控制器206指导收发器总成203的操作。控制器206可以由执行存储在存储器（例如，存储器103或另一存储器）中的指令的微处理器实施。控制器206从传感器200接收数据并且将接收数据存储在存储器103中。控制器206也将传感器数据的不太详细的版本106提供到长距离无线收发器104，以通过无线网络108传输到远程服务器107。控制器206也可以通过导线、光缆或短距离无线系统（例如，蓝牙）耦合到长距离无线收发器104。
可选地或替代地，控制器206和存储器103的部分或全部的功能可以由长距离无线收发器104内的处理器和存储器实施。例如，“智能电话”可以存储和执行应用程序（软件）207，其被配置成从传感器200接收数据、将接收的传感器数据存储在智能电话的存储器中，以及将收集的数据的子集传输到远程服务器107。响应于来自远程服务器107的请求112，应用程序207可以提取更详细的数据115并且将其发送到远程服务器107。此外，应用程序207可以例如响应于来自远程服务器107的命令而改变数据收集参数（例如，采样率和采样精度）和数据传输参数（例如，不太详细的数据106和更详细的数据115的采样率和采样精度），以及传输数据包的大小、数据包传输率、每个数据包的样本数等。
控制器206和长距离无线收发器104应在进行实质通信、传感器数据的传输、控制等之前，检查对方的真实性和权威以接收数据和被对方控制。此外，数据和控制通信，特别是在实施方案的组件之间的无线通信应被加密。例如，传感器200与控制器206之间、控制器206与长距离无线收发器104之间，以及长距离无线收发器104与远程服务器107之间的无线数据通信应被适当加密，例如以保护病人隐私。
收发器总成203可以实施为一个物理总成。或者，收发器总成203可以实施为两个物理上可分离的组件，一个组件包括控制器206和存储器103，并且另一个组件包括长距离无线收发器104。这种由两部分组成的分隔由虚线208指示。两个组件可以通过短距离无线系统，例如，蓝牙（未示出）彼此通信。可以在控制器206与智能电话之间分割或分配从传感器200接收数据、在存储器103中或在智能电话中的存储器中存储接收数据，以及从收集的数据中生成不太详细的数据106的任务。
适合的网关209，以及其它众所周知的计算机网络装备（例如，网络交换机、路由器、防火墙等）可以用于将远程服务器107耦合到无线网络108。远程服务器107包括生理数据分析仪212，生理数据分析仪212被配置成执行如上文参照图1所述的高灵敏度分析109和高特异性分析118。远程服务器107可以包括数据库215，并且数据分析仪212可以被配置成在数据库215中存储接收的不太详细的数据106和/或接收的更详细的数据115，或其部分。数据可以用加密的形式存储在数据库215中以增加数据免受未经授权的访问的安全性。
医师应用程序218允许医师控制系统的参数，例如，由数据分析仪212使用的阈值，以执行高灵敏度分析109和/或高特异性分析118。可选地，医师应用程序218也允许医师设置收发器总成203的操作参数，例如，对不太详细的数据下采样、量化等的量。
医师应用程序218也向医师显示数据并且允许医师选择要显示的数据的类型、要显示的数据的时段、要显示的数据细节的等级和系统的其它操作参数。例如，例如，医师可以选择与疑似或验证的心律失常紧密相关的开始和结束时间进行显示。响应于医师的查询，医师应用程序218可以从数据库215提取和显示数据。如果被请求的数据无法在数据库215中使用，或如果被请求的数据无法以医师请求的细节的等级在数据库215中使用，那么医师应用程序218可以与收发器总成203自动通信以在适量细节中提取适当的数据。
医师应用程序218可以实施适当的安全协议，例如，需要医师输入登录凭证，以便适当限制访问病人数据并且遵守法规，例如，健康保险携带和责任法案（HIPAA）。
用户界面/网络服务器221接受用户（医师、病人或管理员）输入并且生成适当的显示以促进用户与医师应用程序218和类似的病人应用程序214互动，如下文所述。用户界面/网络服务器221可以在耦合到远程服务器107的屏幕（未示出）上生成基于窗口隐喻的计算机用户界面，或用户界面/网络服务器218可以生成由单独的用户计算机（未示出）执行的浏览器227所呈现的网页。网络服务器221和网络浏览器227可以使用适当的加密协议，例如，安全超文本传输协议（HTTPS）彼此通信。
病人应用程序224使用适当的病人登录凭据和适当的安全浏览器连接提供病人访问其自己的数据。
图3为图示生理传感器300、303和309的一种可能的组合和传感器在病人的躯干312上的可能放置的示意图。一个传感器309可以附着在病人的横膈抬高附近。可以使用众所周知的凝胶垫或其它常规的附着技术将每个传感器300-309附着到躯干312。众所周知的生理电极的任何组合可以用于传感器300-309。例如，传感器300-309可以包括SpO2传感器、血压传感器、心脏电极、呼吸传感器、运动和活动传感器等的任何组合。可以使用适当的加速计或陀螺仪（例如，微机电系统（MEMS）设备）感测运动或活动。可以通过导线或光缆315和318或通过无线链路（例如，蓝牙链路）连接传感器300-309。如本领域技术人员已知，呼吸数据可以源自于ECG基线数据。
收发器总成203（图2）或其部分可以附着到一个传感器309并且由一个传感器309支撑，如在321处指示。可选地，其它传感器（例如，病人重量测量设备、血压表套袖等）可以通过导线、光缆可断开耦合或无线耦合到收发器总成203。
如上所述，收发器总成203收集生理数据、在存储器103中存储收集的数据，并且将数据的不太详细的版本106发送到远程服务器107。在检测到疑似心律失常后，远程服务器107请求112更详细的数据。图4含有假设的ECG波形400，其代表从传感器200收集并且存储在存储器103中的详细数据。即，收集的数据具有相对较高的采样率和相对较高的分辨率。假定波形400包括部分403，在此期间波形为异常的。
图5含有波形500，其代表收集的数据的不太详细的版本106。将不太详细的数据106传输到远程服务器107。由数据分析仪212（图2）执行的高灵敏度分析109（图1）检测到作为疑似心律失常的异常403。响应于这个检测，数据分析仪212（图2）在异常403前后的时段503内将关于更详细的数据的请求112发送到收发器总成203。时段503的长度可以取决于由数据分析仪212检测的异常的类型。各种类型的异常和相应的时段503可以由医师通过医师应用程序218指定。
图6含有波形600，其代表收发器总成203发送到远程服务器107的更详细的数据115（图2）。更详细的数据115比不太详细的数据106具有更高的采样率、更高的分辨率和/或含有来自更多传感器的数据。使用更详细的数据115，由数据分析仪212执行的高特异性分析验证疑似心律失常603。
图7含有示例性分辨率、采样率和传输工作周期（从收发器总成203到远程服务器107的数据传输之间的时间）的表700。表700的每一行代表这些参数的不同组合。例如，基于病人的病情的相对严重性，用指示从收发器总成203馈送的数据的相对及时性的“设置”标示每一行。因此，收发器总成203可以比将数据发送到远程服务器107存储更高分辨率的数据（以每个样本的比特数为单位）、更多的数据样本（以每秒的样本数为单位）和/或来自更多传感器或更多类型的传感器的数据。此外，在将代表某个时段的数据发送到远程服务器107后，收发器总成203可以在这个时段内存储数据。表700中的具体设置只是医师可能从一系列可能的值确定的内容的实例。
远程服务器107可以被配置成手动地（例如，响应于通过医师应用程序218接收的输入）或自动地（例如，响应于满足一个或多个预定标准的收集的数据，例如，检测到收集的数据中的异常）确定数据收集参数。医师可以通过医师应用程序218选择表700中所示的数据收集参数集中的一个，或医师可以通过医师应用程序218输入值来指定自定义值（例如，针对每个病人的值）。医师可以通过医师应用程序218在一天的不同时段、不同的天或任何其它指定的时段内指定不同的数据收集参数。类似地，通过医师应用程序218，医师可以改变阈值，数据分析仪212比较收集的数据与这些阈值。可选地或替代地，使用哪个数据收集参数集（即，表700的哪一行）可能部分或全部取决于在供电收发器总成203、传感器200（如果传感器有单独的电池）和/或长距离无线收发器104的电池中剩余的电荷量。较少剩余的电荷可以引起选择表700中的较低的设置。
在一些实施方案中，可以响应于自动检测到测量的生理数据值超过或低于预定阈值而自动改变数据收集和/或传输参数。例如，如果呼吸率、SpO2或血压超过上限阈值或低于下限阈值，那么远程服务器107可以指示收发器总成203增加从传感器200采样数据和/或将数据作为不太详细的数据106或更详细的数据115传输到远程服务器107的速率。类似地，可以增加数据采样分辨率和数据传输率（来自收发器总成203）或其它参数（在本文中统称为“数据收集参数”）。
一些或所有的阈值可以被预定或其可以基于每个病人由医师通过医师应用程序218指定。可选地或替代地，可以基于收集的数据自动确定一些或所有的阈值。例如，如果从病人收集的数据向远程服务器107指示病人在锻炼，即，如果例如来自加速计的数据指示与病人一致的执行跳跃或仰卧起坐的身体运动，那么呼吸和心率的阈值可能自动增加直到检测到这些运动停止后，外加可选的一段休息时间。图8含有列出几个病人的活动水平的示例性阈值的表800。
可选地，在使数据收集参数增加的度量在至少预定时段内恢复正常后，数据收集参数可以返回到其原始值或在增加值与其原始值中间的值。数据收集参数可以基于测量的数据值在一个或多个定时阶段中返回到其原始值。
触发追溯数据或数据收集参数的变化的请求112的异常可能比超过或低于阈值的测量值更复杂。在一些实施方案中，测量的ECG中的自动检测的异常会自动触发追溯数据或改变一个或多个数据收集参数的请求112。例如，ECG数据可以由数据分析仪212处理以使用形态学和心跳间隔特征自动分类心跳，如Philip deChazal等人在“Automatic Classification of Heartbeats Using ECG Morphology andHeartbeat Interval Features”（IEEE Transactions on Biomedical Engineering，第51卷，第7号，2004年7月）中所述，其内容以引用的方式并入本文。换句话说，可以在确定是否已检测到异常之前处理收集的数据。
如上所述，可以使用ECG数据、非ECG数据或其组合怀疑或验证（或两者）心律失常。例如，可以全部或部分基于呼吸率怀疑或验证心律失常。例如在图3中所示，可以基于附着到病人的躯干的传感器中一个或多个加速计的数据确定呼吸率。可以例如在预期的频率和振幅内滤除由加速计检测的胸部运动，以导出呼吸率。例如，可以在位于邻近病人的横膈的传感器309（图3）中包括一个加速计，并且可以在传感器300或303中包括另一个加速计。由两个加速计表示的躯干312上的两个位置之间的相对运动准确地表示横膈运动，并且因此表示呼吸。
如本领域中众所周知的，呼吸率也可以或替代地源自于ECG基线数据。这些呼吸率中的任何一个可以由数据分析仪212使用。然而，如在图9中的流程图中所示，一些实施方案使用两个导出的速率。在900，收集ECG和加速计数据。在903，基于ECG基线数据计算第一候选呼吸率，并且在906，基于加速计数据计算第二候选呼吸率。在909比较这两个候选速率。如果两个候选速率之间的差小于预定值（例如，约10%），那么在912计算两个候选速率的平均值，并且数据分析仪212在915使用这个平均值。可选地，医师可以通过医师应用程序218指定两个候选速率之间的最大允许差值（即，909中的极限）。
然而，如果两个候选速率相差超过预定值，那么控制传递到918。如果两个候选速率超出正常呼吸率的预定范围，那么在921废除这两个候选速率，并且程序返回到900。如果两个候选速率不超出正常呼吸率的预定范围，即，如果至少一个候选速率在范围内，那么控制传递到924。
在924，如果两个候选速率在预定的正常范围内，那么在927使用基于ECG的候选呼吸率。然而，如果只有一个候选速率在预定的正常范围内，那么控制传递到930。
在930，如果只有基于ECG的候选呼吸率在预定的正常范围内，那么在933使用基于ECG的候选呼吸率。然而，在930，如果基于ECG的候选呼吸率不在预定的正常范围内，那么在936使用基于加速计的候选呼吸率。
尽管已描述所有数据分析由远程服务器107（图2）执行的实施方案，但是高灵敏度分析109（图1）可以可选地或替代地由控制器206或蜂窝收发器104执行，即，在病人处而不是在远程服务器107中，如在图10中示意地所示。在这种情况下，如果高灵敏度分析1000怀疑心律失常，那么不需要将请求信号发送到每个病人的生理传感器和数据收集器1003。作为替代，控制器206（参见图2）或蜂窝收发器104（参见图2）将更详细的数据自动发送到远程服务器1006，并且远程服务器1006执行如上所述的高特异性分析118。在此实施方案中，收发器总成203（参见图2）可以被称为传输器总成，这是因为其主要或排他性地将数据发送到远程服务器1006并且未必从远程服务器1006接收任何请求112（参见图1和图2）。
尽管本发明的实施方案被描述为检测和验证疑似心律失常，但是其它实施方案可以被类似地配置和用于检测和验证其它健康或健身状况，例如，不当的胰岛素水平、呼吸、血压、SpO2、身体运动、劳累等。此外，其它实施方案可以被配置和用于检测和验证与非健康和非健身相关的状况，例如，油井或天然气井中的不安全的压力或流率、矿井中的可燃气体的不安全水平、龙卷风、暴雨或其它恶劣天气、地震、泥石流、海啸、地质特征（例如，断层）内的过度应力或运动、爆炸、减压、吊桥张力或摇摆、水坝内的过度应力、飞机或航天器的翼或其它结构构件的过度应力或运动、结构构件的损坏、核辐射泄漏等。包括至少一个结构构件的人造项目在本文中被称为“建筑物”。示例性建筑物包括井、桥、水坝、房屋（例如，办公楼、住宅、剧院等）、雕像、飞机和航天器。另外，尽管已描述双层系统，但是本文所述的原理可以适用于使用三层或更多层分析的系统。在此系统中，在每一层执行的分析通常比在其先前层中执行的分析更具特异性，并且每一层（除了最后一层）从远程数据监控器触发发送比被发送到请求层的数据更详细的数据的请求。每一层的分析可能比前一层的分析消耗更多的计算资源。
远程健康或其它监控系统包括由存储在存储器中的指令控制的处理器。例如，收发器总成可以包括此处理器并且由此处理器控制，并且远程服务器可以由另一个此处理器控制。存储器可以为适合于存储控制软件或其它指令和数据的随机访问存储器（RAM）、只读存储器（ROM）、快闪存储器或任何其它存储器，或上述组合。
已参照流程图和/或方框图描述由远程健康或其它监控系统执行的一些功能。本领域技术人员应容易地了解，流程图或方框图的每个方框的部分或全部或方框的组合的功能、操作、决策等可以实施为计算机程序指令、软件、硬件、固件或上述组合。
本领域技术人员也应容易地了解，定义本发明的功能的指令或程序可以用许多形式被递送到处理器，包括（但不限于）永久存储在非可写存储介质（例如，在计算机内的只读存储设备（例如，ROM），或由计算机I/O附件可读的设备（例如，CD-ROM或DVD光盘）上的信息、可变地存储在可写存储介质（例如，软盘、可移动快闪存储器和硬盘驱动器）上的信息，或通过通信介质（包括有线或无线计算机网络）传送到计算机的信息。
另外，尽管本发明可以用软件来实施，但是实施本发明需要的功能可以可选地或替代地部分或全部使用固件和/或硬件组件来实施，例如，组合逻辑、专用集成电路（ASIC）、现场可编程门阵列（FPGA）或其它硬件，或硬件、软件和/或固件组件的某一组合。
上文所述的本发明的实施方案意图只是示例性的。尽管通过上述示例性实施方案描述本发明，但是本领域普通技术人员将理解，在不脱离本文公开的发明概念的情况下，可以对说明性实施方案进行修改和变化。例如，尽管已参照流程图描述远程健康监控系统的一些方面，但是本领域技术人员应容易地了解，流程图的每个方框的部分或全部或方框的组合的功能、操作、决策等可以被组合、分离成单独的操作或以其它顺序被执行。此外，可以用上文未列出的方式组合公开的方面或这些方面的部分。因此，本发明不应被看作限于公开的实施方案。
Claims (33)
1.一种用于远程服务器的多层数据收集系统，所述系统包括：
数字数据输入源；
收发器总成，其包括存储器、控制器和无线收发器，所述收发器总成通信耦合到所述数字数据输入源并且被配置成：
从所述数字数据输入源接收数据；
在所述存储器中存储所述接收数据（“更详细的数据”）；
通过所述无线收发器将所述接收数据的子集（“不太详细的数据”）发送到所述远程服务器，其中被发送到所述远程服务器的所述不太详细的数据的特征在于以下至少一个：比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的分辨率、比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的采样率，以及从与在相应的时段内存储在所述存储器中的所述更详细的数据不同的一组传感器被接收；以及
响应于来自所述远程服务器的信号，从所述存储器提取所述更详细的数据的至少部分并且将所述提取的更详细的数据发送到所述远程服务器。
2.如权利要求1所述的系统，其中被发送到所述远程服务器的所述不太详细的数据的特征在于以下至少一个：比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的分辨率，以及比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的采样率。
3.如权利要求1所述的系统，其中所述远程服务器被配置成：
接收由所述收发器总成发送的所述不太详细的数据；
自动分析所述接收的不太详细的数据以指示异常；以及
如果指示所述异常，那么将所述信号自动发送到所述收发器总成。
4.如权利要求3所述的系统，其中所述异常包括地震。
5.如权利要求3所述的系统，其中所述异常包括海啸。
6.如权利要求3所述的系统，其中所述异常包括在天然气井、油井和矿井的至少一个内的不安全条件。
7.如权利要求3所述的系统，其中所述异常包括恶劣天气。
8.如权利要求3所述的系统，其中所述异常包括建筑物的结构构件中的不安全的机械条件。
9.如权利要求3所述的系统，其中所述异常包括建筑物的结构构件的损坏。
10.如权利要求3所述的系统，其中所述异常包括在地质结构内的不安全条件。
11.如权利要求3所述的系统，其中所述异常包括超过预定值的核辐射水平。
12.如权利要求3所述的系统，其中所述异常包括爆炸。
13.如权利要求3所述的系统，其中所述异常包括减压。
14.如权利要求3所述的系统，其中所述远程服务器进一步被配置成：
接收所述更详细的数据；以及
自动分析所述接收的更详细的数据以验证所述指示的异常。
15.如权利要求14所述的系统，其中所述远程服务器被配置成：
根据第一分析技术分析所述不太详细的数据；以及
根据第二分析技术分析所述更详细的数据；
其中所述第二分析技术比所述第一分析技术具有所述异常的更高特异性。
16.如权利要求14所述的系统，其中所述远程服务器被配置成：
显示第一用户界面，所述第一用户界面被配置成接受至少一个用户指定的标准；以及
基于满足所述用户指定的标准的所述不太详细的数据的至少部分而自动分析所述接收的不太详细的数据以指示所述异常。
17.如权利要求14所述的系统，其中所述远程服务器被配置成：
显示第一用户界面，所述第一用户界面被配置成接受至少一个用户指定的标准；以及
基于满足所述用户指定的标准的所述更详细的数据的至少部分而自动分析所述接收的更详细的数据以验证所述指示的异常。
18.如权利要求1所述的系统，其中所述无线收发器包括蜂窝电话。
19.如权利要求1所述的系统，其中所述无线收发器总成包括蜂窝电话，其通过短距离无线链路耦合到所述无线收发器并且被配置成：在所述存储器中存储所述更详细的数据；将所述不太详细的数据发送到所述远程服务器；响应于所述信号，从所述存储器提取所述更详细的数据的所述至少部分并且通过无线载波网络将所述提取的更详细的数据发送到所述远程服务器。
20.如权利要求1所述的系统，其进一步包括蜂窝电话，所述蜂窝电话被配置成通信耦合到无线载波网络并且：
通过所述无线收发器接收由所述收发器总成发送的所述数据；以及
通过所述无线载波网络将所述接收数据发送到所述远程服务器。
21.如权利要求1所述的系统，其进一步包括被配置成由蜂窝电话执行的应用程序，所述蜂窝电话被配置成通信耦合到无线载波网络，所述应用程序被配置成：
通过所述无线收发器接收由所述收发器总成发送的所述数据；以及
通过所述无线载波网络将所述接收数据发送到所述远程服务器。
22.如权利要求1所述的系统，其中：
所述远程服务器被配置成：
通过第一用户界面接受用户指定的数据收集参数；以及
响应于接受所述用户指定的数据收集参数，将所述数据收集参数发送到所述收发器总成；以及
所述收发器总成被配置成：
接收所述数据收集参数；以及
响应于接收到所述数据收集参数，改变此后发送到所述远程服务器的所述不太详细的数据的所述分辨率和采样率中的至少一个。
23.如权利要求1所述的系统，其中所述远程服务器被配置成：
根据从所述收发器总成接收的所述不太详细的数据在第一用户界面中生成第一显示区；
响应于用户输入，根据从所述收发器总成接收并且对应于与在所述第一显示区中显示的所述数据相关联的时间的所述更详细的数据的至少部分，在所述第一用户界面中生成第二显示区。
24.如权利要求23所述的系统，其中所述远程服务器进一步被配置成响应于所述用户输入而将所述信号发送到所述收发器总成。
25.一种用于远程监控数据的多层方法，所述方法包括：
接收数据；
在存储器中存储所述接收数据（“更详细的数据”）；
将所述接收数据的子集（“不太详细的数据”）无线发送到远程服务器，其中被发送到所述远程服务器的所述不太详细的数据的特征在于以下至少一个：比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的分辨率、比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的采样率，以及从与在相应的时段内存储在所述存储器中的所述更详细的数据不同的一组传感器被接收；以及
响应于来自所述远程服务器的信号，从所述存储器提取所述更详细的数据的至少部分并且将所述提取的更详细的数据发送到所述远程服务器。
26.如权利要求25所述的方法，其中被发送到所述远程服务器的所述不太详细的数据的特征在于以下至少一个：比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的分辨率，以及比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的采样率。
27.如权利要求25所述的方法，其进一步包括：
在所述远程服务器上接收所述不太详细的数据；
在所述远程服务器上自动分析所述接收的不太详细的数据以指示异常；以及
如果指示所述异常，那么自动发送所述信号。
28.如权利要求27所述的方法，其进一步包括：
所述远程服务器接收所述更详细的数据；以及
在所述远程服务器上自动分析所述接收的更详细的数据以验证所述指示的异常。
29.如权利要求28所述的方法，其中：
分析所述不太详细的数据包括根据第一分析技术分析所述不太详细的数据；
分析所述更详细的数据包括根据第二分析技术分析所述更详细的数据；以及
所述第二分析技术比所述第一分析技术具有所述异常的更高特异性。
30.一种用于远程服务器的多层数据收集系统，所述系统包括：
数字数据输入源；
传输器总成，其包括存储器、控制器和无线传输器，所述传输器总成通信耦合到所述数字数据输入源并且被配置成：
从所述数字输入源接收数据；
在所述存储器中存储所述接收数据（“更详细的数据”）；
自动分析所述接收数据的子集（“不太详细的数据”）以指示异常，其中所述不太详细的数据的特征在于以下至少一个：比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的分辨率、比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的采样率，以及从与在相应的时段内存储在所述存储器中的所述更详细的数据不同的一组传感器被接收；以及
如果指示所述异常，那么从所述存储器自动提取所述更详细的数据的至少部分并且将所述提取的更详细的数据发送到所述远程服务器。
31.如权利要求30所述的系统，其中所述不太详细的数据的特征在于以下至少一个：比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的分辨率，以及比在相应的时段内存储在所述存储器中的所述更详细的数据具有更低的采样率。
32.如权利要求30所述的系统，其中所述远程服务器被配置成：
接收所述更详细的数据；以及
自动分析所述接收的更详细的数据以验证所述指示的异常。
33.如权利要求32所述的系统，其中：
所述传输器总成被配置成根据第一分析技术分析所述不太详细的数据；以及
所述远程服务器被配置成根据第二分析技术分析所述更详细的数据；
其中所述第二分析技术比所述第一分析技术具有所述异常的更高特异性。
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2013
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| CN106659411A (zh) * | 2014-08-11 | 2017-05-10 | 日本电信电话株式会社 | 生物信号测量系统、生物信息测量装置和生物信息提取算法改变方法 |
| US10881315B2 (en) | 2014-08-11 | 2021-01-05 | Nippon Telegraph And Telephone Corporation | Biological signal measurement system, biological information measurement apparatus, and biological information extraction algorithm changing method |
| CN106998827A (zh) * | 2014-12-23 | 2017-08-01 | 英特尔公司 | 可穿戴设备的深度接近度分层 |
| CN106998827B (zh) * | 2014-12-23 | 2020-01-07 | 英特尔公司 | 可穿戴设备的深度接近度分层 |
| CN114096190A (zh) * | 2019-07-01 | 2022-02-25 | 深圳迈瑞生物医疗电子股份有限公司 | 一种中央监护系统、监护设备、移动终端和病人监护方法 |
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| EP2696750B1 (en) | 2016-08-10 |
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| US8478418B2 (en) | 2013-07-02 |
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| US20120265029A1 (en) | 2012-10-18 |
| US20190304285A1 (en) | 2019-10-03 |
| WO2012142462A1 (en) | 2012-10-18 |
| US20160180684A1 (en) | 2016-06-23 |
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