WO2019073288A1 - Remote ecg monitoring and alerting methods and sensing device - Google Patents

Remote ecg monitoring and alerting methods and sensing device Download PDF

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Publication number
WO2019073288A1
WO2019073288A1 PCT/IB2017/056325 IB2017056325W WO2019073288A1 WO 2019073288 A1 WO2019073288 A1 WO 2019073288A1 IB 2017056325 W IB2017056325 W IB 2017056325W WO 2019073288 A1 WO2019073288 A1 WO 2019073288A1
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Prior art keywords
ecg
data
monitoring
files
server
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PCT/IB2017/056325
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French (fr)
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Marjan GUSHEV
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Gushev Marjan
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Priority to PCT/IB2017/056325 priority Critical patent/WO2019073288A1/en
Publication of WO2019073288A1 publication Critical patent/WO2019073288A1/en

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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0004Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
    • A61B5/0006ECG or EEG signals
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/25Bioelectric electrodes therefor
    • A61B5/271Arrangements of electrodes with cords, cables or leads, e.g. single leads or patient cord assemblies
    • A61B5/273Connection of cords, cables or leads to electrodes
    • A61B5/274Connection of cords, cables or leads to electrodes using snap or button fasteners
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/30Input circuits therefor
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • A61B5/318Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346Analysis of electrocardiograms
    • A61B5/349Detecting specific parameters of the electrocardiograph cycle
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/74Details of notification to user or communication with user or patient ; user input means
    • A61B5/7465Arrangements for interactive communication between patient and care services, e.g. by using a telephone network
    • A61B5/747Arrangements for interactive communication between patient and care services, e.g. by using a telephone network in case of emergency, i.e. alerting emergency services
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/63ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7225Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems

Definitions

  • Timely alerting of heart arrhythmia or heart dysfunction at a patient based on continuous real-time remote non-invasive sensing of heart activity for longer of 48h.
  • the present invention refers to the methods of measuring ECG by wearable sensors, communication of wireless sensors to the main module with computing and monitoring capabilities, methods of managing the treatment of heart condition based on ECG, methods for cardio-physiological mathematical modelling.
  • the invention relates to a realization of a system that monitors and alerts abnormal heart function and onset of a heart attack by means of wireless communication.
  • the invention relates to an integrated system that provides continuous real-time remote ECG monitoring for non-hospitalized patients and describes algorithms that detect changes in cardiac function in order to alert the monitoring centre with urgent arrhythmias.
  • ECG monitoring systems have been invented, developed and marketed over the years with a goal to provide to the physician a higher accuracy in the assessment of a patient's risk of sudden death from arrhythmia and other life-threatening abnormalities.
  • the homecare (non-stationary) setting environment ECG equipment is divided into:
  • Holter devices The conventional wired Holter devices and ECG patches with wireless transmission; Belt/vest/garment solutions that use sensors that directly make contact to the human skin, without ECG electrode and gel; and Fingertip ECG solutions that are inexpensive measuring devices and often used for on-demand approach for short-term measurement.
  • Wireless ECG patches are classified in several types: Cardiac Event Recorders (CER), Mobile Cardiac Telemetry (MCT), Continuous Real-time Cardiac Monitoring (CRCM), Continuous Remote Real-time Cardiac Monitoring (CRRCM).
  • CER Cardiac Event Recorders
  • MCT Mobile Cardiac Telemetry
  • CRCM Continuous Real-time Cardiac Monitoring
  • CRCM Continuous Remote Real-time Cardiac Monitoring
  • the CRCM class of wireless patches is intended for hospitalized patients, where the device wirelessly streams data to the master unit, which communicates to the hospital's health information system, such as the Philips wearable biosensor, Isansys Lifetouch HRV011 and Patient Status Engine (PSE).
  • PSE Patient Status Engine
  • the overall idea is to replace conventional Holter devices with small wearable sensors that stream data to the hospital's server and updates personal health information system.
  • the technology behind them consists of a master node device that plays the role of a transmission and monitoring device, but does not stream data and share data with authorized users on the cloud.
  • Continuous streaming data to the cloud server, as used in presented, invention prevents them from engaging in continuous real-time remote monitoring.
  • the CRRCM class combines the telemetry and continuous monitoring with real-time remote access to authorized users.
  • the solutions which belong to this class can be divided into subclasses.
  • the CRRCM-A class is a wireless patch for one use only, such as ZIO XT patch and Medtronic SEEQ
  • CRRCM-B class is a wireless patch that uses specialized ECG electrode strips that occupy a larger surface and can be reused, such as Lifewatch MCT 1 Lead Patch.
  • the CRRCM-C class uses a wireless patch that is attached with conventional ECG electrodes and reused for as long as the patient needs.
  • US20110125040 Includes a wireless transceiver that receives the ECG signal from the sensor through three electrodes.
  • the wireless transceiver is used as a local monitoring device. It processes the ECG signal, and in the case of detecting an abnormality sends an alert to the smartphone, and then to the monitoring center. This is different from the solution disclosed in this specification since it measures two channels with a bigger patch and it, then, introduces an unnecessary transceiver device because the smartphone can perform these functions.
  • the concept of only selecting and sending problematic issues through an on-demand approach is replaced with continuous ECG data streaming and remote real-time monitoring in the disclosed design.
  • US 8290574 is an extension of the previous patent with configurable alarm limits. This approach is still different from the solution disclosed below since it only sends ECG strips on-demand when an alarm is detected, while the subject invention includes on/line steaming of ECG data.
  • Patent application US20170164855 reveals an ECG monitor, and cellphone as a transceiver that relays the event information to a monitoring center by using an on-demand approach.
  • the wearable device disclosed in US20150257644 specification acquires signals wirelessly and processes the patient's condition but the general solution does not consider streaming of ECG signals or monitoring of the results by a third party.
  • US6987965 reveals a programmable system and includes several electrodes and a wireless multiplexer to transmit signals to the base monitoring unit, which is different from the subject invention, which uses a one-channel ECG sensor, intermediate device, and cloud server to share data for continuous monitoring.
  • the approach of the subject invention upgrades currently available prior art by optimizing the used sensor, defining the most efficient method of data transfer and storage, specifying the communication between devices and enabling continuous analysis, real-time monitoring and alerting.
  • the invention subject of this specification enables a caregiver, doctor, and patient to continuously remotely monitor the heart's function in real-time.
  • this invention describes a system that analyses the heart's condition, and alerts in case of heart abnormality, so a doctor can make a proper decision and recommend corresponding therapy.
  • the senor records the ECG signal and transmit the recorded ECG data samples to the nearby device in the personal area network. All other functions to store and process data are designed for the nearby intermediate dew server device, which has greater computing capabilities and can transmit data to the Internet server. This design allows for the sensor to be of smaller size and operate longer without having to be recharged.
  • the intermediate device is a server in the dew computing scenario, where the processing is brought closer to the user, by an independent and collaborative server.
  • the intermediate dew server needs also to be a moveable device close to the user using a low power radio connection, such as Bluetooth Low Energy, to the sensor and long-distance radio communication, such as 3G/4G communication to the mobile operator or LAN/WAN wireless connection integrating an Internet protocol.
  • a low power radio connection such as Bluetooth Low Energy
  • long-distance radio communication such as 3G/4G communication to the mobile operator or LAN/WAN wireless connection integrating an Internet protocol.
  • the sensor is a wearable light device that is patched on the human's chest and does not restrict everyday activities of the patient.
  • the invention defines a complete system that consists of a wearable ECG sensor, intermediate device, cloud server and monitoring device.
  • the system may use any already available ECG sensor or use the new design of the sensor described in this invention.
  • the role of the ECG sensor, as a first aspect of the invention, is to sense the electrical signal generated by heart's function, to transform it to digital data and to transmit the corresponding data values to the nearby intermediate dew server device.
  • the sensor is very light (at most 20 gr.) and uses standard ECG electrodes that are attached by the corresponding silver-plated garment snaps.
  • the ECG electrodes use adhesive pads and sponges saturated with electrolyte gel to make a better contact with the human's chest and enable a signal with sufficient quality to be sensed by the sensor.
  • the female snap connectors in the ECG sensor need to be on at least 8 cm distance to allow sensing a higher voltage level that corresponds to heart's function.
  • the design of the sensor assumes two body parts connected by a special cable.
  • the cable uses a spiral like wired protection and allows the position of two parts to be flexible from one side and also to be resistant to a tearing force up to 10 kg.
  • the main part can be executed in different shapes, including the banana or plate (disc) versions.
  • the connector part is a small part that holds just the snap connector.
  • the internal sensor contains: ADC converter, microprocessor, memory, radio communication chip, motherboard, battery and internal LED indicator.
  • the sensor hardware uses an analog amplifier and analog low pass filter to suppress the noise and extract a quality electrical signal brought to the ADC converter which outputs ECG data samples on a regular sampling interval defined by a sampling frequency of 125 Hz in a working mode or 500 Hz in a diagnostic mode.
  • the resolution can be 10 bit for normal operation or up to 16 bit for high resolution.
  • the data samples are written in a small memory buffer and used by the processor to form data chunks adding a timer identification to each data chunk.
  • the processor sends these data chunks to the wireless radio communication unit to transmit them to the nearby intermediate device.
  • the processor and the wireless radio communication unit need to establish a connection to the intermediate device prior to data sending. After establishing the connection, the data is transmitted with no acknowledgement of acceptance by the intermediate device.
  • the sensor enters hibernation mode. Whenever the sensor is positioned for charging in the docking station, a reset function is applied to the sensor's processor. A LED indicator blinks whenever a reset is initiated.
  • the wireless radio communication unit works in low power mode and when the sensor is in hibernate mode, it checks for a nearby device to be connected in a regular time interval (30 seconds). Once a connection is established it sends data chunks in regular time intervals of at least 8 times per minute.
  • the radio communication protocol can be a standard Bluetooth Low Energy or similar personal area network protocol.
  • the second aspect of the invention is the intermediate device as a dew server whose role it is to establish communication with the ECG sensor, to receive data chunks from the ECG sensor, temporarily store data, process data by applying efficient DSP filters, execute QRS detection algorithms, make beat classification, manage Internet communication to the cloud server, transmit to the cloud server system, visualize the ECG signal on the display, alert in case of detected heart's abnormal function, control the ECG sensor, and interface with a user.
  • This device unit is, at the same time, a monitoring unit and intermediate device that receives ECG data chunks and transmits ECG data files to the cloud server system.
  • the intermediate device can be any portable and mobile computing device, such as a smartphone, tablet, laptop or a similar device.
  • the requirements for this device are to be equipped with hardware parts to establish a connection and communicate via a personal area network (using the same protocol used by the previously described sensor), to establish a connection and communicate to cloud server via an Internet communication network, to display monitoring information and accept user commands, to process data and temporarily store ECG data.
  • Its power supply must be independent of fixed wired connection, so it is a battery-operated device that enables mobility and independence.
  • the intermediate device consists of the following five software modules: device controller, communication manager, streaming processor, data processor and U/I processor. It does data collection, pre-processing, storing, and transmitting to higher-level servers.
  • the intermediate device also performs the function of a digital repeater since it buffers the received data stream on a low power radio connection, and then generates and transmits a higher-power signal to the higher-level servers hosted on the Internet.
  • the sensor sends its status to the nearby intermediate device and provides relevant information for further processing, including information about the signal level of the connected device, battery level etc. Since the intermediate device controls the ECG sensor, it can set up a specific variable to initiate more accurate sensing and measuring the signal. The intermediate device is able to reset the sensor and, for example, start a new measurement.
  • the intermediate device is intended to work autonomously in the background, as a typical dew server, users can control its function, which gives them an advantage of monitoring the visualized data and activating various parameters or actions on the sensor.
  • the cloud server does data collection and processing features via more complex data analysis for diagnosis and monitoring purposes.
  • the web application needs user administration, and user interface to communicate with doctors and end-users.
  • This invention specifies an efficient distribution of cloud servers to enable scalable architecture, which supports thousands of concurrent ECG streams.
  • the cloud does not provide device control because all of the data is sent by the intermediate device, and the only communication that might happen is alerting via standard voice communication. All the functions of the cloud server system are distributed to perform essential tasks and enable high scalability and elasticity of the solution.
  • the cloud server is organized as a set of several units of the following types: streaming collection unit (SC), file storage unit (FS), processing unit (PU), database (DB) and web server (WS).
  • the SC unit is responsible for communication and receipt of ECG files and to align their size and location according to the requirements for easier further processing as 30-second ECG files. All files are stored locally in the FS unit to enable efficient processing and receipt of incoming streams.
  • the FS unit does initial processing and creates annotation files, which are used for visualization.
  • Each streaming collection unit works independently with a limited number of sensors. If there is a severe decrease in performances then the FS unit releases the SC unit by porting the communication and stored data of some sensors to another SC unit. In case of satisfactory performance, the SC unit is loaded with more sensor streams, depending on the velocity of the data streams.
  • This architecture requires a porting mechanism that will transfer the stored data from a given collection unit to another.
  • the PU has a role to update the dashboard information in DB, and also administer the users, sensors and all system parts.
  • a WS requires the PU to process information in order to prepare a web page to send it to the end-user.
  • ECG files are standard 30-second recordings of a one channel ECG.
  • the system can perform as an event recorder in such a way that the user initiates the marking of an event marking when they feel a problem.
  • the beat detection and classification software modules can also generate events.
  • the system generates ECG event files with a length of 60, 120, 180 or 240 seconds, so that they contain information where half of the length is generated prior the onset of the event, and half after it. Events are used as alerts and the system signals those events to doctors, so they can use the diagnosis information from the system to make a final decision about the diagnosis given the broader patient and, in case of an emergency, trigger an intermediate intervention.
  • Non-invasive continuous real-time remote monitoring of ECG data for non-hospitalized patients by a caregiver or doctor is a caregiver or doctor.
  • this invention specifies the sensor without data storing features and all measured data is buffered and transmitted to the intermediate device.
  • the specification of the sensor is sole to sense, convert and transmit ECG data samples. This will preserve the sensor's battery for a longer period.
  • Deep sleep mode enables the sensor's battery to last up to 6 months without recharging.
  • the solution does not need a special reset button since the system is reset when connected to the charger. Keeping data sampling frequency low (to the value of 120 Hz) and 8-bit data conversion preserves the battery with sufficient quality for the ECG signal.
  • Using a distant external body part for the second electrode enables a relatively good distance for quality ECG measurement on one hand and flexibility in movement on the other hand. All the designs that use a single patch occupy a larger surface on the human's chest and provoke uneasiness and feel uncomfortable.
  • the intermediate device acts as a dew server, so it can function locally or in combination with the cloud server. It acts as a digital repeater that transmits the ECG signals to the cloud and, also, as a monitoring device.
  • the intermediate device runs pipelined algorithms for QRS detection and beat classification to save the battery as much as possible.
  • the intermediate device receives data chunks, processes them and stores 30-second ECG files that are transmitted to the cloud.
  • the user can record an event by activating a command on the intermediate device, and an ECG file will be created with samples 30 seconds prior to activation and 30 seconds after activation. This file can be transmitted to the cloud or a doctor for further analysis.
  • the cloud consists of different hardware modules, which can be multiplied to allow an elastic and scalable solution.
  • the streaming collection unit has the role of accepting incoming ECG files, buffering and processing them, and storing relevant information in the file storage unit. This particular grouping (as files with 30-second ECG files and lh annotation files) makes for faster- distributed access and a smaller and faster database.
  • the database only stores information about users and a dashboard summary.
  • the personal specific data in the database is encrypted for higher security.
  • the ECG files in the file storage unit are anonymized (without identification) to enable data protection security.
  • the communication between the intermediate device and the cloud is through a secure Internet protocol.
  • the communication in the personal area network between the sensor and the intermediate device consists of sending raw data without any identification. Also, the protocol enables only one pair of devices to be paired and protects others to intercept the communication.
  • the system acts as an automated monitoring software agent. It checks the ECG signal for abnormalities, classifies the beats and alerts in the case of detected arrhythmia or a similar cardiac disorder. The doctor in the monitoring centre decides on the urgency and reacts correspondingly.
  • the system works continuously, unlike systems with on-demand approaches, or those that store the recorded data and unload it for diagnosis only after the measurement is finished.
  • the caregiver and doctor can remotely monitor the patient's heart function with a delay of, at most, 30 seconds.
  • Fig.l is a schematic diagram of the remote ECG monitoring and alerting service system according to one embodiment of the invention.
  • Fig.2 is a design diagram of the wearable ECG sensor used in the system of Fig. l.
  • Fig.3 is a hardware architectural design of the wearable ECG sensor used in the system of Fig. l.
  • Fig.4 is a software functional diagram of the wearable ECG sensor used in the system of Fig. l.
  • Fig.5 is a software functional diagram of the intermediate dew server used in the system of Fig. l.
  • Fig.6 is a software functional diagram of the cloud server used in the system of Fig. l.
  • Fig.7 is an algorithm design of the processing unit used by the intermediate dew or cloud server used in the system of Fig. l.
  • Fig.8 is a hardware organization of the cloud server units for the system of Fig. l.
  • FIG.l A system for real-time online remote ECG monitoring and alerting is shown in Fig.l in a block functional diagram.
  • a patient [1] wears an ECG sensor [2], of a type to be described below. It communicates the intermediate device [12] and monitoring centre [13] to enable remote monitoring [14].
  • the sensor is connected to the human chest through ECG electrode patches to sense an ECG signal and then the sensor processes the electrical signal and sends digital ECG samples through a radio communication link [3] in a personal area network to the nearby intermediate device [4], which is a portable wireless device with computing capabilities and can communicate with a cloud server [6] via a WiFi or other radio communication link [5] that implements Internet protocols.
  • a personal monitoring device [8] can access the cloud server via conventional radio communication links [7] that implement Internet protocol. This design provides real-time remote ECG monitoring for a caregiver and doctor.
  • the intermediate dew server device [4] can be also used as a monitoring device [8], although in a general sense it can be any computing device connected to the Internet with display capabilities.
  • the cloud server [6] processes data and sends an alert to the doctor [9] in the monitoring centre [13], which uses a monitoring device [8] to visualize necessary information.
  • the doctor in the monitoring centre responds to the alerts, defines the urgency level and sends an intelligent message to the user with a recommendation.
  • the caregiver [10] can remotely monitor the patient and access the alerts and recommendation by the monitoring centre. In case of emergency, the patient or caregiver can consult their doctor [11] for detailed therapy and further actions.
  • the sensor Fig.2 consists of three parts: the main body part [17], connection link [19] and external body part [18].
  • the main and external body parts embed female snap connectors for ECG electrodes [20] to attach standard ECG electrodes.
  • the electrodes contain a male silver plated garment snap from one side and can be patched on the user's chest by an adhesive pad on the other side. They contain sponge saturated with an electrolyte gel to enable a better contact with the skin and sense the electrical signal generated by heart's function.
  • the internal design of the sensor Fig.3 consists of an ECG electrode snap connector [26] (to enable a good contact to measure electrical potential), analog amplifier and filter [21] (for processing of electrical signals), ADC converter [22] (to generate ECG samples), memory [24] (to temporary buffer ECG samples), processor [25] (for digital processing) and wireless radio communication unit [23] (to establish a communication and transfer data samples).
  • the whole system is operated on an internal battery [27], and an internal LED indicator [28] blinks on a reset function of the processor.
  • the wireless radio communication unit also contains a small antenna to transmit the corresponding radio waves.
  • the sensor functions are based on two parts: the analog and digital processing.
  • the analog part senses micro-electrical signals on the human skin, amplifies them, filters the electrical signal to extract the unnecessary noise and converts from analog to digital.
  • the digital part consists of temporal data sample storage in small buffers, their organization in small data chunks and then their dispatching via a radio communication unit, using a standard protocol, such as the Bluetooth Low Energy.
  • the sensed electrical signal via ECG electrodes is transferred from a cable [29] (analog link - dashed line) to the analog amplifier and filter and this analog signal is then transferred to the ADC converter via a link [29] (analog link - dashed line) located on a motherboard.
  • the generated ECG samples are transferred to the memory via a direct link [31] (one directional link - full line) on the motherboard.
  • the processors can access the memory and the radio communication unit via bidirectional links [32] (bidirectional digital links - full line) on the motherboard.
  • a set of controlling signals [30] (dotted lines) are also built on the motherboard to enable the processor to control the ADC converter, memory, and wireless radio communication unit.
  • the sensor does the following functions Fig.4: signal sensing [32] (to sense electrical potential in range of mV), analog signal filtering [33] (to suppress the higher frequency noise), analog signal amplification [34] (to amplify the signal and prepare it for ADC conversion), ADC conversion [35] (to sample the analog signal on a regular sampling frequency), temporal data storage [39] (to buffer the generated data samples), data chunk processing [38] (to produce data chunks with ECG data samples and timestamp), data dispatch [37] (to transfer data chunks via the radio communication unit) and customization and control [36] (to control execution of the sensor parts, including reset, selecting a data sampling frequency, data sampling resolution, and data chunk size).
  • the sensor's radio communication unit [23] senses radio frequencies and pairs with the personal area network device in order to establish a wireless connection via a standard communication protocol. It also uses a protocol for connecting once the paired device is within the accepted range and disconnecting in case the radio signal is too low. A fixed pairing PIN code is written in the fixed memory of the sensor and this needs to be matched for the pairing purpose. Once the sensor is paired with a device it is not discoverable to other devices and therefore cannot be paired with another device.
  • the intermediate device Fig.5 consists of five software modules: streaming processor [40] (to receive data chunks from a personal area network and send data files to the cloud server by a long-distance radio communication), storage manager [41] (to store data chunks, extracts ECG data streams, construct and store ECG data files and event files), data processor 42 (to filter data and extract noise, detect and classify beats, diagnose and alert in case of a detected abnormal function and visualize ECG data), UI processor [43] (to enable interface to the user for monitoring, activation and control of the devices) and device controller [44] (to pair and connect to the nearby device or establish an Internet connection and send customization and control operations to the intermediate dew server).
  • streaming processor [40] to receive data chunks from a personal area network and send data files to the cloud server by a long-distance radio communication
  • storage manager [41] to store data chunks, extracts ECG data streams, construct and store ECG data files and event files
  • data processor 42 to filter data and extract noise, detect and classify
  • the device controller [44] of the intermediate device is used to control the sensor device status [55] and also as a communication manager to the sensor for pairing and connecting [56] and a communication manager to higher level servers by managing a TCP connection [57].
  • the process of pairing is required for low power radio communication protocols, such as Bluetooth Low Energy, and a process of authorizing and acknowledgement for the TCP connection for the long-distance radio communication.
  • the pairing to the intermediate device is not the only function to be implemented, but also connecting, disconnecting and reconnecting after the pairing done in the initialization process. For example, whenever the device is in close proximity it automatically starts the connection, while, if the signal is weak it starts disconnects.
  • Device control function is needed to monitor the intermediate dew server device status and control its features, including the features to: get sensor status, such as the signal strength of the connected device, and battery level; set a specific variable parameter in the sensor, such as sampling frequency and resolution; trigger specific actions, such as set an operational mode; and reset function.
  • the streaming data processor [40] collects data chunks [45] from the sensor and transmits the ECG files [46] to cloud server. Data collection process from the sensor does not acknowledge receipt as in the ECG file transfer to the high-level servers with a TCP connection. This enables the ECG sensor to be built with essential basic operations only and save the battery resources as much as possible.
  • the storage manager module [41] consists of a data chunk storage processor [48] (to buffer incoming data chunks and create an ECG stream to be further processed and visualized), data manager [49] (to generate and store 30 second ECG files to be transmitted to high-level servers) and event file manager [59] (to store ECG file recordings of marked or generated events). Data chunks contain tens of data samples and time stamps to synchronize the unacknowledged data collection, while the ECG data files contain 30-second records of ECG data.
  • Data processor performs pre-processing [50], beat detection and classification [51], visualization [52] and alerting [58].
  • the pre-processing includes DSP filtering to eliminate baseline wander and higher frequency noise, and also, to extract features for further detection of QRS complexes, P and T waves.
  • the beat detection and classification module includes determination of heart rate, and any abnormality and arrhythmia. In case of abnormality, it triggers an event recorder and creates an event file marking.
  • the visualization module creates an animation of the incoming ECG signal with time stamps, and also can reproduce a 30 second ECG of a historical record or event.
  • the alerting module is in tight connection to the beat detection and classifier module and also with the UI processor [43], since the user can create a marked event.
  • ECG monitoring consists of three visualization forms generated by the data visualization module [52], including live stream animation for real-time monitoring, 30- second file presentation with zoom and navigation functions of a historical recording or an event, and a multiline page presentation intended for pdf file generation.
  • the human- computer interface as a part of the control functions module [54] does, at least, the following functions: command activation (via menu options and control buttons), parameter setting, real-time visualization, and navigation through recorded data.
  • the cloud server [6], Fig.8 consists of six independent server units: a streaming collection (SC) unit [90] (to receive ECG data files, initially pre-process and prepare final storage versions), buffer [95] to buffer received elements, file storage (FS) unit [91] (for long-term storage of ECG files), processing unit (PU) [92] (to enable further data analysis and diagnostics, dashboard info and prepare visualization cache files), database (DB) [93] (to store and organize dashboard summary results and admin users, devices etc.), and web server (WS) [94] (to serve other clients with ECG data, alerts and visualization features).
  • SC streaming collection
  • FS file storage
  • PU processing unit
  • DB database
  • DB database
  • DB database
  • WS web server
  • the pre- processing done by the SC unit [90] is used for feature extraction [68], Fig.6, including QRS detection and initial beat classification, while the data analysis and diagnosis [69] Fig.6 is done by PU [92] is used for further preparation of diagnosis information so the doctor can make a final decision. To enable cloud scalability and elasticity, each of these units may be multiplied.
  • the SC unit [90] is a streaming reception that can receive a limited number of registered data streams from intermediate dew servers, dedicated for stream processing with a purpose to store the input ECG files. It establishes a secure communication to an intermediate dew server device, accepts a stream transfer, and starts a sequential disk write to a temporary buffer in a specified format.
  • the file storage unit [91] stores files by organizing a separate folder for each user.
  • the processing unit analyses ECG files in the specified file folder and creates an annotation file with an identification of detected and classified beats based on sophisticated algorithms for QRS detection and beat classification.
  • These files are input for the processing unit [92] with a role to process them and extract relevant info and prepare a diagnosis related information, which will be written in the database to enable a faster access to dashboard information.
  • the dashboard presents a summary of diagnosis related information for each patient.
  • the web server is the interface to other computers to serve all incoming requests.
  • the software modules (Fig.6) communication manager [61], streaming processor [62], data processor [63] and UI processor [64] are deployed in the cloud hardware parts (Fig.8).
  • the data file reception module [65] in the communication manager [61] communicates with the intermediate dew server and receives the data files.
  • the file manager [67] in the streaming processor [62] stores them locally and initiates the feature extraction module [68] in the data processor [63] to perform DSP filtering and feature extraction writing the annotation files to be stored locally.
  • the summary information is stored by the database manager [66] in the streaming processor [62] used to display dashboard when a web page is requested by other computers from the web server [74] in the communication manager [61].
  • the analysis and diagnosis module [69] and extended visualization module [70] in the data processor continues to process data and store additional diagnosis information and visualization cache information in the file manager [67].
  • the UI processor [64] contains modules for user administration module [71] to communicate with users, dashboard and reporting module [72] to create reports by the doctors in the monitoring center [13] (Fig. l) and monitoring and alerting [73] to enable interface for doctors in the monitoring center and authorized users for remote monitoring [14] (Fig. l).
  • the algorithm Fig.7 performed by the cloud server system executes the feature extraction phase [68] in Fig.6 with two sets of DSP filters on two different paths.
  • the first path [88] uses a DSP bandpass filter [80] to eliminate the noise and reduce feature space in the range between 5-20Hz, and the other path [89] aims at eliminating the baseline wander and high- frequency noise by a DSP bandpass filter [81] within the range 0.5Hz - 30Hz.
  • Efficient DSP filters can be FIR or IIR filters or filters based on wavelets, which are implemented to perform as a pipelined solution.
  • the feature extraction pipeline [88] continues with a QRS complex detection algorithm [82], which can be executed with an adaptive differential technique to compare the slope and adapt its magnitude to the signal energy using a pattern matching or other technique.
  • the processing pipeline [88] continues with rhythm analysis 84 and then with beat classification [85].
  • the second processing pipeline [89] uses the detected R peak and continues with a P and T waves detection [83].
  • the detected R peak, P and T waves are used to processing unit [85] with a purpose of determining the length of the QRS complex, PQ and ST segments and their relative elevation. This information is used for beat classification [86] and preparation of diagnosis information [87].
  • this algorithm will output a diagnosed arrhythmia types and determination of possible heart malfunction diagnosis and eventually an onset of heart attack detected by ST segment elevation in the morphological analysis. All the results are just alerts to be sent to doctor and can serve as information for diagnosis, which the doctor will consider and analyse within the given context in order to reach a final decision.
  • the monitoring device [8] can be any computing device with display capabilities and Internet connection, such as smartphone, tablet, laptop or any other computer. These devices can access a web page created by the cloud web server and display it locally to monitor real time live ECG measurement (a 30-second delay is expected in order to align ECG files in the cloud) and can also be used to analyse historical measurement, and marked or alerted events. Any of these 30 seconds recorded ECG measurements, or 60-240 second marked or alerted events can be prepared as pdf files for easier printing or sent to a compatible computer for further analysis.

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Abstract

A system for remote ECG monitoring and alerting, based on a wearable ECG patch, intermediate device, cloud server and a monitoring device. Configuration of the sensing device allows transmission of ECG samples via personal area network to the nearby intermediate dew server. The intermediate device is realized by a small mobile device (smartphone, smart watch, tablet or other device), with an application that accepts the sensed signals, displays the ECG data in a user-friendly manner, transmit captured data to a cloud server and alerts in case of a detected abnormal heart function. The cloud server is used for further processing and data sharing and a monitoring device is used to visualize the ECG data. A caregiver and/or doctor can analyse the ECG data for reference and personalized medical advice, based on relevant data, can be provided.

Description

REMOTE ECG MONITORING AND ALERTING METHODS AND SENSING DEVICE
Technical problem to be solved
Timely alerting of heart arrhythmia or heart dysfunction at a patient, based on continuous real-time remote non-invasive sensing of heart activity for longer of 48h.
Field of invention
The present invention refers to the methods of measuring ECG by wearable sensors, communication of wireless sensors to the main module with computing and monitoring capabilities, methods of managing the treatment of heart condition based on ECG, methods for cardio-physiological mathematical modelling. Overall, the invention relates to a realization of a system that monitors and alerts abnormal heart function and onset of a heart attack by means of wireless communication.
The invention relates to an integrated system that provides continuous real-time remote ECG monitoring for non-hospitalized patients and describes algorithms that detect changes in cardiac function in order to alert the monitoring centre with urgent arrhythmias.
Many ECG monitoring systems have been invented, developed and marketed over the years with a goal to provide to the physician a higher accuracy in the assessment of a patient's risk of sudden death from arrhythmia and other life-threatening abnormalities. In general, there are several types of monitoring systems classified according to the following criteria: measurement activation, measurement length, durability, ECG data accessibility, monitoring and analysis timing, communication to sensor, wireless transmission, patient freedom to move, sensing method and contact type, weight (heavy vs. light if weight <25 gr), size, battery life, battery type, durability, monitoring capacity, location of the monitoring device, event marking, alerting and ownership.
The homecare (non-stationary) setting environment ECG equipment is divided into:
Contact Implantable event recorders that are in fact an invasive measuring method; Holter devices: The conventional wired Holter devices and ECG patches with wireless transmission; Belt/vest/garment solutions that use sensors that directly make contact to the human skin, without ECG electrode and gel; and Fingertip ECG solutions that are inexpensive measuring devices and often used for on-demand approach for short-term measurement.
Wireless ECG patches are classified in several types: Cardiac Event Recorders (CER), Mobile Cardiac Telemetry (MCT), Continuous Real-time Cardiac Monitoring (CRCM), Continuous Remote Real-time Cardiac Monitoring (CRRCM). The CRCM class of wireless patches is intended for hospitalized patients, where the device wirelessly streams data to the master unit, which communicates to the hospital's health information system, such as the Philips wearable biosensor, Isansys Lifetouch HRV011 and Patient Status Engine (PSE). The overall idea is to replace conventional Holter devices with small wearable sensors that stream data to the hospital's server and updates personal health information system. The technology behind them consists of a master node device that plays the role of a transmission and monitoring device, but does not stream data and share data with authorized users on the cloud. Continuous streaming data to the cloud server, as used in presented, invention prevents them from engaging in continuous real-time remote monitoring. Finally, the CRRCM class combines the telemetry and continuous monitoring with real-time remote access to authorized users. The solutions which belong to this class can be divided into subclasses.
The CRRCM-A class is a wireless patch for one use only, such as ZIO XT patch and Medtronic SEEQ, and CRRCM-B class is a wireless patch that uses specialized ECG electrode strips that occupy a larger surface and can be reused, such as Lifewatch MCT 1 Lead Patch. The CRRCM-C class uses a wireless patch that is attached with conventional ECG electrodes and reused for as long as the patient needs.
The invention, that is part of this description, can be categorised in the CRRCM-C class. Prior Art
Some of the present patents are important for understanding the specification and relate to a similar or identical problem but solve it in a different manner. US20110125040 Includes a wireless transceiver that receives the ECG signal from the sensor through three electrodes. The wireless transceiver is used as a local monitoring device. It processes the ECG signal, and in the case of detecting an abnormality sends an alert to the smartphone, and then to the monitoring center. This is different from the solution disclosed in this specification since it measures two channels with a bigger patch and it, then, introduces an unnecessary transceiver device because the smartphone can perform these functions. Also, the concept of only selecting and sending problematic issues through an on-demand approach is replaced with continuous ECG data streaming and remote real-time monitoring in the disclosed design. US 8290574 is an extension of the previous patent with configurable alarm limits. This approach is still different from the solution disclosed below since it only sends ECG strips on-demand when an alarm is detected, while the subject invention includes on/line steaming of ECG data. Patent application US20170164855 reveals an ECG monitor, and cellphone as a transceiver that relays the event information to a monitoring center by using an on-demand approach. The wearable device disclosed in US20150257644 specification acquires signals wirelessly and processes the patient's condition but the general solution does not consider streaming of ECG signals or monitoring of the results by a third party. US6987965, reveals a programmable system and includes several electrodes and a wireless multiplexer to transmit signals to the base monitoring unit, which is different from the subject invention, which uses a one-channel ECG sensor, intermediate device, and cloud server to share data for continuous monitoring.
The general concepts, without technical explanation, related to the solution included in this specification are already published in journals or at conferences:
1. M. Gusev, A. Stojmenski, and A. Guseva, "ECGalert: A Heart Attack Alerting System", in ICT Innovations 2017, Computer Science and Information Systems, (ed. D. Trajanov and V. Bakeva), Springer Verlag, Berlin Heidelberg, 2017, volume CSIS, pp.27-36.
2. M. Gusev, A. Guseva, "State-Of-The-Art of Cloud Solutions Based on ECG Sensors", Proceedings of the IEEE EuroCon 2017, pp.501-506.
3. M. Gusev, "A Dew Computing Solution for IoT Streaming Devices", in MIPRO 2017, Proceedings of 40h Int. Convention on ICT, Opatija, Croatia, IEEE Conference proceedings, ISBN 978-953-233-087-8, 2017, pp.415-420.
The approach of the subject invention upgrades currently available prior art by optimizing the used sensor, defining the most efficient method of data transfer and storage, specifying the communication between devices and enabling continuous analysis, real-time monitoring and alerting.
All of these referred prior art and documents are relevant to understand the solution but none of them are disclosing steps of realisation of the system that is explained in this specification.
Brief summary of the invention
The invention subject of this specification enables a caregiver, doctor, and patient to continuously remotely monitor the heart's function in real-time. In addition, this invention describes a system that analyses the heart's condition, and alerts in case of heart abnormality, so a doctor can make a proper decision and recommend corresponding therapy.
In this invention, the sensor records the ECG signal and transmit the recorded ECG data samples to the nearby device in the personal area network. All other functions to store and process data are designed for the nearby intermediate dew server device, which has greater computing capabilities and can transmit data to the Internet server. This design allows for the sensor to be of smaller size and operate longer without having to be recharged. The intermediate device is a server in the dew computing scenario, where the processing is brought closer to the user, by an independent and collaborative server. Since the system uses a wearable and wireless sensor, the intermediate dew server needs also to be a moveable device close to the user using a low power radio connection, such as Bluetooth Low Energy, to the sensor and long-distance radio communication, such as 3G/4G communication to the mobile operator or LAN/WAN wireless connection integrating an Internet protocol.
The sensor is a wearable light device that is patched on the human's chest and does not restrict everyday activities of the patient.
The invention defines a complete system that consists of a wearable ECG sensor, intermediate device, cloud server and monitoring device. The system may use any already available ECG sensor or use the new design of the sensor described in this invention. The role of the ECG sensor, as a first aspect of the invention, is to sense the electrical signal generated by heart's function, to transform it to digital data and to transmit the corresponding data values to the nearby intermediate dew server device.
The sensor is very light (at most 20 gr.) and uses standard ECG electrodes that are attached by the corresponding silver-plated garment snaps. The ECG electrodes use adhesive pads and sponges saturated with electrolyte gel to make a better contact with the human's chest and enable a signal with sufficient quality to be sensed by the sensor. The female snap connectors in the ECG sensor need to be on at least 8 cm distance to allow sensing a higher voltage level that corresponds to heart's function. The design of the sensor assumes two body parts connected by a special cable. The cable uses a spiral like wired protection and allows the position of two parts to be flexible from one side and also to be resistant to a tearing force up to 10 kg. The main part can be executed in different shapes, including the banana or plate (disc) versions. The connector part is a small part that holds just the snap connector. The internal sensor contains: ADC converter, microprocessor, memory, radio communication chip, motherboard, battery and internal LED indicator.
The sensor hardware uses an analog amplifier and analog low pass filter to suppress the noise and extract a quality electrical signal brought to the ADC converter which outputs ECG data samples on a regular sampling interval defined by a sampling frequency of 125 Hz in a working mode or 500 Hz in a diagnostic mode. The resolution can be 10 bit for normal operation or up to 16 bit for high resolution. The data samples are written in a small memory buffer and used by the processor to form data chunks adding a timer identification to each data chunk. The processor sends these data chunks to the wireless radio communication unit to transmit them to the nearby intermediate device. The processor and the wireless radio communication unit need to establish a connection to the intermediate device prior to data sending. After establishing the connection, the data is transmitted with no acknowledgement of acceptance by the intermediate device. If a connection is not established the sensor enters hibernation mode. Whenever the sensor is positioned for charging in the docking station, a reset function is applied to the sensor's processor. A LED indicator blinks whenever a reset is initiated. The wireless radio communication unit works in low power mode and when the sensor is in hibernate mode, it checks for a nearby device to be connected in a regular time interval (30 seconds). Once a connection is established it sends data chunks in regular time intervals of at least 8 times per minute. The radio communication protocol can be a standard Bluetooth Low Energy or similar personal area network protocol.
The second aspect of the invention is the intermediate device as a dew server whose role it is to establish communication with the ECG sensor, to receive data chunks from the ECG sensor, temporarily store data, process data by applying efficient DSP filters, execute QRS detection algorithms, make beat classification, manage Internet communication to the cloud server, transmit to the cloud server system, visualize the ECG signal on the display, alert in case of detected heart's abnormal function, control the ECG sensor, and interface with a user. This device unit is, at the same time, a monitoring unit and intermediate device that receives ECG data chunks and transmits ECG data files to the cloud server system.
The intermediate device can be any portable and mobile computing device, such as a smartphone, tablet, laptop or a similar device. The requirements for this device are to be equipped with hardware parts to establish a connection and communicate via a personal area network (using the same protocol used by the previously described sensor), to establish a connection and communicate to cloud server via an Internet communication network, to display monitoring information and accept user commands, to process data and temporarily store ECG data. Its power supply must be independent of fixed wired connection, so it is a battery-operated device that enables mobility and independence. The intermediate device consists of the following five software modules: device controller, communication manager, streaming processor, data processor and U/I processor. It does data collection, pre-processing, storing, and transmitting to higher-level servers.
In some sense, the intermediate device also performs the function of a digital repeater since it buffers the received data stream on a low power radio connection, and then generates and transmits a higher-power signal to the higher-level servers hosted on the Internet.
The sensor sends its status to the nearby intermediate device and provides relevant information for further processing, including information about the signal level of the connected device, battery level etc. Since the intermediate device controls the ECG sensor, it can set up a specific variable to initiate more accurate sensing and measuring the signal. The intermediate device is able to reset the sensor and, for example, start a new measurement.
Although the intermediate device is intended to work autonomously in the background, as a typical dew server, users can control its function, which gives them an advantage of monitoring the visualized data and activating various parameters or actions on the sensor.
The cloud server does data collection and processing features via more complex data analysis for diagnosis and monitoring purposes. In addition, the web application needs user administration, and user interface to communicate with doctors and end-users. This invention specifies an efficient distribution of cloud servers to enable scalable architecture, which supports thousands of concurrent ECG streams. The cloud does not provide device control because all of the data is sent by the intermediate device, and the only communication that might happen is alerting via standard voice communication. All the functions of the cloud server system are distributed to perform essential tasks and enable high scalability and elasticity of the solution. The cloud server is organized as a set of several units of the following types: streaming collection unit (SC), file storage unit (FS), processing unit (PU), database (DB) and web server (WS). The SC unit is responsible for communication and receipt of ECG files and to align their size and location according to the requirements for easier further processing as 30-second ECG files. All files are stored locally in the FS unit to enable efficient processing and receipt of incoming streams. The FS unit does initial processing and creates annotation files, which are used for visualization. Each streaming collection unit works independently with a limited number of sensors. If there is a severe decrease in performances then the FS unit releases the SC unit by porting the communication and stored data of some sensors to another SC unit. In case of satisfactory performance, the SC unit is loaded with more sensor streams, depending on the velocity of the data streams. This architecture requires a porting mechanism that will transfer the stored data from a given collection unit to another. The PU has a role to update the dashboard information in DB, and also administer the users, sensors and all system parts. A WS requires the PU to process information in order to prepare a web page to send it to the end-user.
Both the morphological and rhythm analysis is used to prepare information relevant for diagnosis and support the monitoring and alerting system. Generated ECG files are standard 30-second recordings of a one channel ECG. The system can perform as an event recorder in such a way that the user initiates the marking of an event marking when they feel a problem. The beat detection and classification software modules can also generate events. The system generates ECG event files with a length of 60, 120, 180 or 240 seconds, so that they contain information where half of the length is generated prior the onset of the event, and half after it. Events are used as alerts and the system signals those events to doctors, so they can use the diagnosis information from the system to make a final decision about the diagnosis given the broader patient and, in case of an emergency, trigger an intermediate intervention.
Advantages and benefits of such a system, as the one described in this invention, include:
Non-invasive continuous real-time remote monitoring of ECG data for non-hospitalized patients by a caregiver or doctor.
In order to preserve battery life, this invention specifies the sensor without data storing features and all measured data is buffered and transmitted to the intermediate device.
The specification of the sensor is sole to sense, convert and transmit ECG data samples. This will preserve the sensor's battery for a longer period.
Deep sleep mode enables the sensor's battery to last up to 6 months without recharging.
The solution does not need a special reset button since the system is reset when connected to the charger. Keeping data sampling frequency low (to the value of 120 Hz) and 8-bit data conversion preserves the battery with sufficient quality for the ECG signal.
Using a distant external body part for the second electrode enables a relatively good distance for quality ECG measurement on one hand and flexibility in movement on the other hand. All the designs that use a single patch occupy a larger surface on the human's chest and provoke uneasiness and feel uncomfortable.
The intermediate device acts as a dew server, so it can function locally or in combination with the cloud server. It acts as a digital repeater that transmits the ECG signals to the cloud and, also, as a monitoring device.
The intermediate device runs pipelined algorithms for QRS detection and beat classification to save the battery as much as possible.
The intermediate device receives data chunks, processes them and stores 30-second ECG files that are transmitted to the cloud.
The user can record an event by activating a command on the intermediate device, and an ECG file will be created with samples 30 seconds prior to activation and 30 seconds after activation. This file can be transmitted to the cloud or a doctor for further analysis.
The cloud consists of different hardware modules, which can be multiplied to allow an elastic and scalable solution.
The streaming collection unit has the role of accepting incoming ECG files, buffering and processing them, and storing relevant information in the file storage unit. This particular grouping (as files with 30-second ECG files and lh annotation files) makes for faster- distributed access and a smaller and faster database.
The database only stores information about users and a dashboard summary.
The personal specific data in the database is encrypted for higher security. The ECG files in the file storage unit are anonymized (without identification) to enable data protection security.
The communication between the intermediate device and the cloud is through a secure Internet protocol. The communication in the personal area network between the sensor and the intermediate device consists of sending raw data without any identification. Also, the protocol enables only one pair of devices to be paired and protects others to intercept the communication.
Personal data is encrypted in the database and ECG files are anonymized.
The system acts as an automated monitoring software agent. It checks the ECG signal for abnormalities, classifies the beats and alerts in the case of detected arrhythmia or a similar cardiac disorder. The doctor in the monitoring centre decides on the urgency and reacts correspondingly.
The system works continuously, unlike systems with on-demand approaches, or those that store the recorded data and unload it for diagnosis only after the measurement is finished. The caregiver and doctor can remotely monitor the patient's heart function with a delay of, at most, 30 seconds.
Description of the drawings
Features and advantages of this invention will become apparent from the detailed description of one embodiment of the invention in conjunction with the accompanying drawings, wherein:
Fig.l is a schematic diagram of the remote ECG monitoring and alerting service system according to one embodiment of the invention.
Fig.2 is a design diagram of the wearable ECG sensor used in the system of Fig. l.
Fig.3 is a hardware architectural design of the wearable ECG sensor used in the system of Fig. l.
Fig.4 is a software functional diagram of the wearable ECG sensor used in the system of Fig. l.
Fig.5 is a software functional diagram of the intermediate dew server used in the system of Fig. l.
Fig.6 is a software functional diagram of the cloud server used in the system of Fig. l.
Fig.7 is an algorithm design of the processing unit used by the intermediate dew or cloud server used in the system of Fig. l.
Fig.8 is a hardware organization of the cloud server units for the system of Fig. l.
Detailed description of the illustrative embodiment A system for real-time online remote ECG monitoring and alerting is shown in Fig.l in a block functional diagram. A patient [1] wears an ECG sensor [2], of a type to be described below. It communicates the intermediate device [12] and monitoring centre [13] to enable remote monitoring [14].
The sensor is connected to the human chest through ECG electrode patches to sense an ECG signal and then the sensor processes the electrical signal and sends digital ECG samples through a radio communication link [3] in a personal area network to the nearby intermediate device [4], which is a portable wireless device with computing capabilities and can communicate with a cloud server [6] via a WiFi or other radio communication link [5] that implements Internet protocols. A personal monitoring device [8] can access the cloud server via conventional radio communication links [7] that implement Internet protocol. This design provides real-time remote ECG monitoring for a caregiver and doctor. The intermediate dew server device [4] can be also used as a monitoring device [8], although in a general sense it can be any computing device connected to the Internet with display capabilities.
The cloud server [6] processes data and sends an alert to the doctor [9] in the monitoring centre [13], which uses a monitoring device [8] to visualize necessary information. The doctor in the monitoring centre responds to the alerts, defines the urgency level and sends an intelligent message to the user with a recommendation.
The caregiver [10] can remotely monitor the patient and access the alerts and recommendation by the monitoring centre. In case of emergency, the patient or caregiver can consult their doctor [11] for detailed therapy and further actions.
The sensor Fig.2 consists of three parts: the main body part [17], connection link [19] and external body part [18]. The main and external body parts embed female snap connectors for ECG electrodes [20] to attach standard ECG electrodes. The electrodes contain a male silver plated garment snap from one side and can be patched on the user's chest by an adhesive pad on the other side. They contain sponge saturated with an electrolyte gel to enable a better contact with the skin and sense the electrical signal generated by heart's function.
The internal design of the sensor Fig.3 consists of an ECG electrode snap connector [26] (to enable a good contact to measure electrical potential), analog amplifier and filter [21] (for processing of electrical signals), ADC converter [22] (to generate ECG samples), memory [24] (to temporary buffer ECG samples), processor [25] (for digital processing) and wireless radio communication unit [23] (to establish a communication and transfer data samples). The whole system is operated on an internal battery [27], and an internal LED indicator [28] blinks on a reset function of the processor. The wireless radio communication unit also contains a small antenna to transmit the corresponding radio waves.
The sensor functions are based on two parts: the analog and digital processing. The analog part senses micro-electrical signals on the human skin, amplifies them, filters the electrical signal to extract the unnecessary noise and converts from analog to digital. The digital part consists of temporal data sample storage in small buffers, their organization in small data chunks and then their dispatching via a radio communication unit, using a standard protocol, such as the Bluetooth Low Energy. The sensed electrical signal via ECG electrodes is transferred from a cable [29] (analog link - dashed line) to the analog amplifier and filter and this analog signal is then transferred to the ADC converter via a link [29] (analog link - dashed line) located on a motherboard. The generated ECG samples are transferred to the memory via a direct link [31] (one directional link - full line) on the motherboard. The processors can access the memory and the radio communication unit via bidirectional links [32] (bidirectional digital links - full line) on the motherboard. A set of controlling signals [30] (dotted lines) are also built on the motherboard to enable the processor to control the ADC converter, memory, and wireless radio communication unit.
The sensor does the following functions Fig.4: signal sensing [32] (to sense electrical potential in range of mV), analog signal filtering [33] (to suppress the higher frequency noise), analog signal amplification [34] (to amplify the signal and prepare it for ADC conversion), ADC conversion [35] (to sample the analog signal on a regular sampling frequency), temporal data storage [39] (to buffer the generated data samples), data chunk processing [38] (to produce data chunks with ECG data samples and timestamp), data dispatch [37] (to transfer data chunks via the radio communication unit) and customization and control [36] (to control execution of the sensor parts, including reset, selecting a data sampling frequency, data sampling resolution, and data chunk size). In addition, the sensor's radio communication unit [23] senses radio frequencies and pairs with the personal area network device in order to establish a wireless connection via a standard communication protocol. It also uses a protocol for connecting once the paired device is within the accepted range and disconnecting in case the radio signal is too low. A fixed pairing PIN code is written in the fixed memory of the sensor and this needs to be matched for the pairing purpose. Once the sensor is paired with a device it is not discoverable to other devices and therefore cannot be paired with another device.
The intermediate device, Fig.5 consists of five software modules: streaming processor [40] (to receive data chunks from a personal area network and send data files to the cloud server by a long-distance radio communication), storage manager [41] (to store data chunks, extracts ECG data streams, construct and store ECG data files and event files), data processor 42 (to filter data and extract noise, detect and classify beats, diagnose and alert in case of a detected abnormal function and visualize ECG data), UI processor [43] (to enable interface to the user for monitoring, activation and control of the devices) and device controller [44] (to pair and connect to the nearby device or establish an Internet connection and send customization and control operations to the intermediate dew server).
The device controller [44] of the intermediate device is used to control the sensor device status [55] and also as a communication manager to the sensor for pairing and connecting [56] and a communication manager to higher level servers by managing a TCP connection [57]. The process of pairing is required for low power radio communication protocols, such as Bluetooth Low Energy, and a process of authorizing and acknowledgement for the TCP connection for the long-distance radio communication. The pairing to the intermediate device is not the only function to be implemented, but also connecting, disconnecting and reconnecting after the pairing done in the initialization process. For example, whenever the device is in close proximity it automatically starts the connection, while, if the signal is weak it starts disconnects. If the device is out of the reach of the radio coverage, it disconnects and tries to reconnect and establish communication with the paired device in regular time intervals. Device control function is needed to monitor the intermediate dew server device status and control its features, including the features to: get sensor status, such as the signal strength of the connected device, and battery level; set a specific variable parameter in the sensor, such as sampling frequency and resolution; trigger specific actions, such as set an operational mode; and reset function.
The streaming data processor [40] collects data chunks [45] from the sensor and transmits the ECG files [46] to cloud server. Data collection process from the sensor does not acknowledge receipt as in the ECG file transfer to the high-level servers with a TCP connection. This enables the ECG sensor to be built with essential basic operations only and save the battery resources as much as possible. The storage manager module [41] consists of a data chunk storage processor [48] (to buffer incoming data chunks and create an ECG stream to be further processed and visualized), data manager [49] (to generate and store 30 second ECG files to be transmitted to high-level servers) and event file manager [59] (to store ECG file recordings of marked or generated events). Data chunks contain tens of data samples and time stamps to synchronize the unacknowledged data collection, while the ECG data files contain 30-second records of ECG data.
Data processor performs pre-processing [50], beat detection and classification [51], visualization [52] and alerting [58]. The pre-processing includes DSP filtering to eliminate baseline wander and higher frequency noise, and also, to extract features for further detection of QRS complexes, P and T waves. The beat detection and classification module includes determination of heart rate, and any abnormality and arrhythmia. In case of abnormality, it triggers an event recorder and creates an event file marking. The visualization module creates an animation of the incoming ECG signal with time stamps, and also can reproduce a 30 second ECG of a historical record or event. The alerting module is in tight connection to the beat detection and classifier module and also with the UI processor [43], since the user can create a marked event.
The user interface [43] enables ECG monitoring [53] and activation and control functions [54]. ECG monitoring consists of three visualization forms generated by the data visualization module [52], including live stream animation for real-time monitoring, 30- second file presentation with zoom and navigation functions of a historical recording or an event, and a multiline page presentation intended for pdf file generation. The human- computer interface as a part of the control functions module [54] does, at least, the following functions: command activation (via menu options and control buttons), parameter setting, real-time visualization, and navigation through recorded data.
The cloud server [6], Fig.8 consists of six independent server units: a streaming collection (SC) unit [90] (to receive ECG data files, initially pre-process and prepare final storage versions), buffer [95] to buffer received elements, file storage (FS) unit [91] (for long-term storage of ECG files), processing unit (PU) [92] (to enable further data analysis and diagnostics, dashboard info and prepare visualization cache files), database (DB) [93] (to store and organize dashboard summary results and admin users, devices etc.), and web server (WS) [94] (to serve other clients with ECG data, alerts and visualization features). The pre- processing done by the SC unit [90] is used for feature extraction [68], Fig.6, including QRS detection and initial beat classification, while the data analysis and diagnosis [69] Fig.6 is done by PU [92] is used for further preparation of diagnosis information so the doctor can make a final decision. To enable cloud scalability and elasticity, each of these units may be multiplied. The SC unit [90] is a streaming reception that can receive a limited number of registered data streams from intermediate dew servers, dedicated for stream processing with a purpose to store the input ECG files. It establishes a secure communication to an intermediate dew server device, accepts a stream transfer, and starts a sequential disk write to a temporary buffer in a specified format. It continues with an analysis of the buffer data, and creates ECG files by aligning them to predefined time intervals and saves ECG files by identifying the file name by the sensor input, location and time stamp. To enable efficient file storage system, the file storage unit [91] stores files by organizing a separate folder for each user. The processing unit analyses ECG files in the specified file folder and creates an annotation file with an identification of detected and classified beats based on sophisticated algorithms for QRS detection and beat classification. These files are input for the processing unit [92] with a role to process them and extract relevant info and prepare a diagnosis related information, which will be written in the database to enable a faster access to dashboard information. The dashboard presents a summary of diagnosis related information for each patient. The web server is the interface to other computers to serve all incoming requests. It generates web pages with visualized ECG data from corresponding ECG data files, identification of detected QRS complexes and beats from annotation files and diagnosis related information from the database. A special module is created to generate pdf files so the 30-second recorded ECGs or 60-240 second ECG events can be printed in a predefined format. The database also contains all relevant user and admin info, so the web server should route to the corresponding files.
The software modules: (Fig.6) communication manager [61], streaming processor [62], data processor [63] and UI processor [64] are deployed in the cloud hardware parts (Fig.8). The data file reception module [65] in the communication manager [61] communicates with the intermediate dew server and receives the data files. The file manager [67] in the streaming processor [62] stores them locally and initiates the feature extraction module [68] in the data processor [63] to perform DSP filtering and feature extraction writing the annotation files to be stored locally. The summary information is stored by the database manager [66] in the streaming processor [62] used to display dashboard when a web page is requested by other computers from the web server [74] in the communication manager [61]. The analysis and diagnosis module [69] and extended visualization module [70] in the data processor continues to process data and store additional diagnosis information and visualization cache information in the file manager [67]. The UI processor [64] contains modules for user administration module [71] to communicate with users, dashboard and reporting module [72] to create reports by the doctors in the monitoring center [13] (Fig. l) and monitoring and alerting [73] to enable interface for doctors in the monitoring center and authorized users for remote monitoring [14] (Fig. l).
The algorithm Fig.7 performed by the cloud server system executes the feature extraction phase [68] in Fig.6 with two sets of DSP filters on two different paths. The first path [88] uses a DSP bandpass filter [80] to eliminate the noise and reduce feature space in the range between 5-20Hz, and the other path [89] aims at eliminating the baseline wander and high- frequency noise by a DSP bandpass filter [81] within the range 0.5Hz - 30Hz. Efficient DSP filters can be FIR or IIR filters or filters based on wavelets, which are implemented to perform as a pipelined solution. The feature extraction pipeline [88] continues with a QRS complex detection algorithm [82], which can be executed with an adaptive differential technique to compare the slope and adapt its magnitude to the signal energy using a pattern matching or other technique. The processing pipeline [88] continues with rhythm analysis 84 and then with beat classification [85]. The second processing pipeline [89] uses the detected R peak and continues with a P and T waves detection [83]. The detected R peak, P and T waves are used to processing unit [85] with a purpose of determining the length of the QRS complex, PQ and ST segments and their relative elevation. This information is used for beat classification [86] and preparation of diagnosis information [87]. Finally, this algorithm will output a diagnosed arrhythmia types and determination of possible heart malfunction diagnosis and eventually an onset of heart attack detected by ST segment elevation in the morphological analysis. All the results are just alerts to be sent to doctor and can serve as information for diagnosis, which the doctor will consider and analyse within the given context in order to reach a final decision.
The monitoring device [8] can be any computing device with display capabilities and Internet connection, such as smartphone, tablet, laptop or any other computer. These devices can access a web page created by the cloud web server and display it locally to monitor real time live ECG measurement (a 30-second delay is expected in order to align ECG files in the cloud) and can also be used to analyse historical measurement, and marked or alerted events. Any of these 30 seconds recorded ECG measurements, or 60-240 second marked or alerted events can be prepared as pdf files for easier printing or sent to a compatible computer for further analysis.

Claims

Claims
1. A method for remote monitoring of heart condition of the patients comprising: an ECG wireless sensor [2] attached to patient's [1] chest, intermediate device [12], which is a portable wireless device with computing capabilities and can communicate with monitoring centre [13], that can serve for remote monitoring via a WiFi or other radio communication link with a cloud server [6] coupled with web server [7] and a monitoring device [8] of caregiver [9] or a doctor [8] that can access to web server via conventional communication links, is characterised with that when the cloud server [6] processes data and sends an alert to the doctor in the monitoring centre by means of monitoring device then the doctor is in able to visualize necessary information, to define the urgency level and to send a corresponding message to the user.
2. Sensing device [2], used in the system for monitoring of ECG monitoring, comprising main body part [17], connection link [19] and external body part [18], female snap connectors [20] for ECG electrodes to attach standard ECG electrodes, which contain a male silver plated garment snap, and the internal design of the sensor, which consists of an analog amplifier and filter [21], ADC converter [22], memory [24], processor [25], and an internal battery [27] and indicator [28] for signalizing and wireless radio communication unit [23] that transmits the corresponding radio waves, is characterised by that, the wireless radio communication unit sensor only senses and transmits ECG samples via personal area network to the nearby intermediate dew server.
3. ECG sensor according to the claim 2 that converts sensed analog ECG signal to a digital form is characterized by that a sampling frequency is in the range of 120 Hz or 500 Hz and bit depth of 8, 10 or 12-bits for AD conversion.
4. ECG sensor according to the claim 3 is characterized by that the digital samples are packed in data chunks with time stamp and sent to the nearby personal area network device.
5. A method for monitoring of heart condition of the patients that includes intermediate device [4] consisting of five software modules: streaming processor [40] for collecting data chunks; a long distance radio communication; storage manager [41] to store data chunks, extracts ECG data streams, construct and store ECG data files and event files; data processor [42] to filter data and extract noise, detect and classify beats, diagnose and alert in case of a detected abnormal function and visualize ECG data; UI processor [43], and device controller [44], is characterized by that the intermediate device acts as a dew server or digital repeater that transmits the ECG signals to cloud as well as a monitoring device.
6. A method for remote monitoring of heart condition of the patients that includes a cloud server [6] consisting of six independent server units: a streaming collection unit SC; buffer [95]; file storage FS unit [91]; processing unit PU [92]; database DB, and web server WS [94] is characterized by that the pre-processing operation done by the SC unit [90] that used for feature extraction [68], includes QRS detection and initial beat classification, while the data analysis and diagnosis [69] done by PU [92] is used for further preparation of diagnosis information relevant for doctor or therapist.
7. A method for remote monitoring of heart condition of the patients that includes a cloud server [6] according to claim 7 further comprising of streaming collection (SC) unit [90], that is a streaming reception which receives a limited number of registered data streams from intermediate dew servers determined for stream processing with a purpose to store the input ECG files capable to establish a secure communication to an intermediate dew server device, wherein the SC unit accepts a stream transfer, and start a sequential disk write to a temporary buffer in a specified format.
8. A method for remote monitoring of heart condition of the patients according to the claim 7 is characterized by that the analysis of the buffer data creates ECG files by aligning them to a predefined time intervals and saving ECG files by identifying the file name by the sensor input, location and time stamp and transfer to the processing unit, which analyses ECG files in the specified file folder and creates an annotation file with identification of detected and classified beats.
9. A method according to claims 7, wherein the files from the storage unit [91] are transferred to PU [92] with a purpose to be processed as well as a relevant info to be extracted and written into the database enabling faster access to the web server that can generate web pages with visualized ECG data from corresponding ECG data files, identification of detected QRS complexes and beats from annotation files and diagnosis related information.
10. A method for remote monitoring of heart condition of the patients that includes data extraction phase [68] with two sets of DSP filters on two different paths is characterized by that, the first path [88] uses a DSP bandpass filter [80] to eliminate the noise and reduce feature space in the range between 5Hz and 20Hz, and the second path [89] aims towards eliminating the baseline wander and high frequency noise by a DSP bandpass filter [81] within the range from 0.5Hz to 30Hz.
11. A method for remote monitoring of heart condition of the patients according to claim 9, is characterized by that the feature extraction pipeline [88] continues with a QRS complex detection algorithm [82] for rhythm analysis [84] and beat classification [85], and the second processing pipeline [89] uses the detected R peak and continues with a P and T waves detection to determine the length of the QRS complex, PQ and ST segments and their relative elevation, used for beat classification [86] and preparation of diagnosis information [87].
12. A method for remote monitoring of heart condition of the patients, according to any of previous claims, includes web server [7] as an interface to monitoring device is characterized by that it is generating web pages by visualising ECG, from corresponding ECG data files, that include identification of detected QRS complexes and beats from annotation files and diagnosis related information from the database.
13. A method for monitoring of heart condition of the patients according to any of previous claims is characterized by that the monitoring device [8] can be any computing device with display capabilities and internet connection, such as smartphone, tablet, laptop or any other computer.
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