EP3304375A1 - Messdatenverarbeitungssystem - Google Patents
MessdatenverarbeitungssystemInfo
- Publication number
- EP3304375A1 EP3304375A1 EP16726493.6A EP16726493A EP3304375A1 EP 3304375 A1 EP3304375 A1 EP 3304375A1 EP 16726493 A EP16726493 A EP 16726493A EP 3304375 A1 EP3304375 A1 EP 3304375A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- measurement data
- acquisition device
- calibration information
- calibration
- data acquisition
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT 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
- G16H40/60—ICT 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
- G16H40/67—ICT 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7221—Determining signal validity, reliability or quality
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT 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
- G16H40/40—ICT 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 management of medical equipment or devices, e.g. scheduling maintenance or upgrades
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
Definitions
- the present invention relates to a measuring data processing system and a method for measuring data processing, in particular for measuring data processing of measured data of medical devices that are worn on the body and their data in a "health cloud” (cloud system for processing health data) are merged, especially those for medical Care, including diagnostics, therapy and care can be used.
- a “health cloud” cloud system for processing health data
- Measurement data indicating a health / illness condition of the patient
- Such medical devices have a high accuracy in the measurement data acquisition and are often certified to be used in a medical environment for the collection of vital data such as in the health cloud.
- fitness devices or wellness devices in the form of consumer products for the private sector are now being used to measure vital data.
- consumer products often have lower accuracy than the certified medical gauges and do not meet the standards prescribed for the medical sector, for example, according to the Medical Devices Act or the corresponding
- the health cloud can be used.
- cloud or cloud computing here is the approach to understand abstracted IT infrastructures such as
- the abstracted IT infrastructure is also referred to as cloud or "cloud.”
- cloud refers to a data processing system for processing data from essentially medical devices that meet special requirements for medical data acquisition and data processing.
- the methods and systems presented below can be used for communicating in client-server systems or based on a client-server architecture.
- the client-server architecture is the standard concept for distributing tasks within a network. Tasks are distributed to different computers by means of servers and can be requested by several clients to solve their own tasks or parts thereof. Tasks may be standard tasks, such as e-mail, e-mail, Web access, etc., or specific tasks of a software or program. A task is called a service in the client-server model.
- a server is a program that offers a service. As part of the client-server concept, another program, the client, can use this service. The communication between client and server depends on the service, ie the service determines what data is exchanged between the two. The server is in
- the server behaves passively and waits for requests.
- the rules of communication for a service such as format, call of the server and the meaning of the data exchanged between server and client are determined by a protocol specific to the respective service.
- the measuring data processing system presented below can be based on the client-server concept.
- Messarbaserver represent a server according to the client-server architecture described above and provide its services as a server.
- the first and second measurement data acquisition devices presented below can be used e.g. Represent clients according to the client-server architecture described above and provide their services as clients.
- Metering interfaces and metering interfaces between client and server may be based on wireless networks, such as using Wi-Fi, WiFi, Bluetooth, infrared, or others
- the communication interfaces can also be based on wired networks, for example, using Ethernet, USB, cable, etc.
- VoIP Voice-over-IP
- IPv4 or IPv6 can be used via IPv4 or IPv6.
- the communication channels between the interfaces can be established by means of the public network, for example via the Internet, a telephone network of a telephone operator, eg a wired network, such as a POTS, ISDN, DSL or cable network or a wireless network, such as a mobile network Mobile operator, such as a cellular network, for example, using a mobile standard such as LTE, UMTS, GSM, etc.
- Voice over IP can be used by IPv4 or IPv6 or ATM, STM or others wide area standards.
- the measurement data processing system presented below can acquire and process measurement data with a specific fault tolerance.
- fault tolerance here is an accuracy or quality of the measurement to understand.
- the fault tolerance is a deviation of the detected measured value from the exact measured value, which is usually specified as the ratio of the measured value recorded to the exact measured value in percent or per thousand. A low fault tolerance is thus associated with an accurate reading while a high fault tolerance reflects a less accurate reading.
- the measurement data processing system presented below can be implemented via
- Medical Devices Act contains a number of national regulations, for example for the monitoring and operation and use of medical devices.
- Medical devices are medical devices intended by the manufacturer for human use. These include, for example, implants, products for injection, infusion, transfusion and dialysis, software, pacemakers, x-ray equipment, medical
- the invention relates to a measurement data processing system comprising: a measurement data server for providing first measurement data having a first fault tolerance and second measurement data having a second fault tolerance, the first fault tolerance being smaller than the second fault tolerance; a first measurement data server for providing first measurement data having a first fault tolerance and second measurement data having a second fault tolerance, the first fault tolerance being smaller than the second fault tolerance; a first measurement data server for providing first measurement data having a first fault tolerance and second measurement data having a second fault tolerance, the first fault tolerance being smaller than the second fault tolerance; a first
- the second data acquisition device comprises a second measurement data interface configured to generate the second measurement data and a second calibration information about the calibration
- the measurement data server has a measurement data acquisition interface, which is formed, the first measurement data and the first calibration information from the first
- the measurement data server is further configured, the first measurement data and the second measurement data with reference to the first calibration information and the second calibration information of the corresponding measurement data acquisition devices
- Patients can rely on a very extensive information base, because they can not only on their own the data of medical devices, i. use the very accurate measurement data of the first measurement acquisition device with the low first fault tolerance for the diagnosis, but also patient-generated measurement data from the private environment, i. Include the less accurate measurement data of the second measurement acquisition device with the higher second fault tolerance in the diagnosis.
- the first comprises
- Calibration information information about a quality of the first measurement data and the second calibration information information about a quality of the second measurement data This has the advantage that the doctor or the nursing staff is very well aware of the accuracy of his or her diagnosis based on the measurement data
- Diagnosis since he has the information about the quality of the measurement data available.
- the first one is selected from the measurement data processing system.
- Data acquisition device A medical device for recording vital data with a given first fault tolerance. This has the advantage that the measurement data processing system can be used flexibly in existing infrastructure. If the first data acquisition device is a medical device, such as exists in hospitals, for example, the measurement data processing system can integrate this medical device into the medical device
- the measurement data processing system can thus be used in the hospital to expand the existing information base and create better diagnostic options.
- the first measuring data processing system the first
- the first data acquisition device meets the legal requirements and may be used in a medical environment.
- the first data processing system the first
- Calibration information is based on the calibration stamp.
- the user can inform himself about the accuracy and the environment in which the first Meß stylister executedseinnchtung may be used.
- the second one is the measurement data processing system.
- Vital data a fitness device, a wellness device, a consumer product for the
- a heart rate monitor for example, a heart rate monitor, a pedometer, a sphygmomanometer, a portable device.
- the second one has
- Messrageer executedseinnchtung on an identifier, in particular a serial number indicating a type of the second Meßmers enteredseinnchtung, wherein the second calibration information based on the identifier.
- Messarieser upsetseinnchtung on a quality of the second measurement data, which were recorded by the second data acquisition device, can be closed.
- an automated measurement data processing is possible in which a quality of the measurement data based on the identifier or design can be automatically evaluated and displayed, for example, based on signal colors of a traffic light in red, yellow, green.
- the measurement data server is designed to store the received first measurement data in a first database and store the received second measurement data in a second database, wherein the second database is separated from the first database, and wherein the first stored in the first database Measurement data have an indication of the stored in the second database second measurement data.
- the first, ie very accurate measurement data are stored in a first database, which, for example, meets the legal requirements, and that the second, less accurate measurement data in a separate database can be filed, which does not have to comply with the legal requirements.
- the first measurement data stored in the first database are provided with a reference which refers to the second measurement data stored in the second database.
- Involvement or non-involvement may be made at the request of the physician or nurse.
- the reference comprises the second calibration information of the second measurement data acquisition device.
- the reference comprises a form factor which indicates a quality of the second measurement data with respect to a quality of the first measurement data.
- the invention relates to a method for
- Measurement data processing comprising the following steps: acquisition of first measurement data by a first measurement data acquisition device, wherein the first Measurement data acquisition device for the detection of the first measurement data is calibrated with a first error tolerance and transmitting the first measurement data and a first calibration information on the calibration of the first measurement data acquisition device; Acquisition of second measurement data by a second measurement data acquisition device, wherein the second measurement data acquisition device for the detection of the second
- Measurement data is calibrated with a second error tolerance, wherein the first error tolerance is smaller than the second error tolerance, and transmitting the second measurement data and a second calibration information on the calibration of the second
- Data acquisition device Receiving the first measurement data and the first calibration information from the first measurement data acquisition device and receiving the second measurement data and the second calibration information from the second
- the first calibration information comprises information about a quality of the first measurement data and wherein the second
- Calibration information includes information about a quality of the second measurement data. This has the advantage that the doctor or the nursing staff is very well aware of the accuracy of his or her diagnosis based on the measurement data
- the method further comprises displaying the second one
- the invention relates to a computer program with a program code for carrying out the method according to the second aspect of the invention
- FIG. 1 shows a schematic representation of a measurement data processing system 100 according to an embodiment
- Fig. 2 is a schematic representation of a decentralized system 200 for
- Fig. 3 is a schematic representation of a method 300 for
- Fig. 4 is a schematic representation of a method 400 for
- Claims may be used to include such terms in a manner similar to the term “comprising.”
- the terms “coupled” and “connected” may be used in conjunction with derivatives thereof such terms may be used to indicate that two elements cooperate or interact with each other independently of whether they are in direct physical or electrical contact or are not in direct contact with each other.
- the term “exemplary” is to be considered as an example only, rather than the term of best or optimum, and the following description is therefore not intended to be in a limiting sense.
- the measurement data processing system 100 comprises a measurement data server 101 as well as first 103 and second 105
- the measurement data server 101 serves to provide first measurement data 102 having a first error tolerance 110 and second measurement data 104 having a second error tolerance 112, the first error tolerance 110 being smaller than the second error tolerance 112, for example, the first error tolerance may be in the range of 0.01% while the second can be in the range of 0.1%.
- the first fault tolerance is referred to as low fault tolerance
- the second fault tolerance is referred to as high fault tolerance
- the first measurement data acquisition device 103 is used to acquire the first measurement data 102.
- the first measurement data acquisition device 103 is calibrated to acquire the first measurement data 102 with a first error tolerance 110.
- Measurement data acquisition device 103 has a first
- Measuring data transmission interface 107 with which the first measurement data 102 and a first calibration information 106 about the calibration of the first
- Measurement data acquisition device 103 can be transmitted to the measurement data server 101.
- the second measurement data acquisition device 105 is used for detecting the second
- Measurement data 104 The second measurement data acquisition device 105 is calibrated for the acquisition of the second measurement data 104 with a second error tolerance 1 12.
- the second measurement data acquisition device 105 has a second one
- Measurement data acquisition device 105 can be transmitted to the measurement data server 101.
- the measurement data server 101 has a measurement data acquisition interface 1 1 1, with which the first measurement data 102 and the first calibration information 106 can be received by the first measurement data acquisition device 103 and with which the second measurement data 104 and the second calibration information 108 can be received by the second measurement data acquisition device 105 ,
- the measurement data server 101 also serves to provide the first measurement data 102 and the second measurement data 104 with reference to the first calibration information 106 and the second calibration information 108 of the corresponding measurement data acquisition devices 103, 105.
- the first calibration information 106 may include information about a quality of the first measurement data 102
- the second calibration information 108 may include information about a quality of the second measurement data 104.
- the first measurement data acquisition device 103 can be a medical device for acquiring vital data with a predefined first fault tolerance 110.
- the first measurement data acquisition device 103 may have a conformity to a medical standard, in particular a conformity according to the
- the first measurement data acquisition device 103 may have a calibration stamp, and the first calibration information 106 may be based on the calibration stamp.
- the second measurement data acquisition device 105 may be a device for acquiring vital data, for example a fitness device, a wellness device, a consumer product for home use, in particular a heart rate monitor, a pedometer, a sphygmomanometer or a portable device.
- the second measurement data acquisition device 105 may have an identifier, in particular a serial number, which is a type of the second
- the second calibration information 108 may be based on the identifier.
- the measurement data server 101 can store the received first measurement data 102 in a first database and store the received second measurement data 104 in a second database.
- the second database may be separate from the first database.
- the first measurement data 102 stored in the first database can have an indication of the second measurement data 104 stored in the second database.
- the first measurement data 102 stored in the first database can be provided with a reference which can refer to the second measurement data 104 stored in the second database.
- the reference may be the second calibration information 108 of the second
- Measurement data acquisition device 105 include.
- the reference may include a form factor that may indicate a quality of the second measurement data 104 with respect to a quality of the first measurement data 102.
- the measurement data processing system 100 can be used, for example, in a medical environment, e.g. in a health cloud or a decentralized system 200 for processing vital data, as described below for FIG. In the general form according to FIG. 1, however, the measurement data processing system 100 can also be used in other areas in order to increase the measurement to a larger one
- the measurement data processing system 100 may be used in an automotive environment in which calibrated meters provide high accuracy data, such as rate sensors, pressure sensors, or temperature sensors.
- calibrated meters provide high accuracy data, such as rate sensors, pressure sensors, or temperature sensors.
- other measuring devices can be used from the environment of the driver to achieve a better overall view, such as measurement data that are recorded by mobile subscriber devices, such as voice messages, current Route data from the Internet or also recorded vital data from wellness devices for recognizing the driving ability of the driver.
- the second measurement data acquisition device 105 offers the advantage of greater flexibility. Especially if this does not require any elaborate calibration
- Data acquisition device 105 to replace or load with new software to adapt flexibly to changing environmental situations.
- the measurement data processing system 100 can also be used in a
- Traffic control system can be used, for example, has fixed installations with a low Fault Tolerance for the detection of the location, the speed and the license plate of vehicles.
- this traffic guidance system can also use information from other higher fault tolerance data acquisition systems, such as e.g. mobile devices, for example navigation devices in vehicles or mobile communication devices such as smartphones, notebooks with mobile radio adapters or other devices with mobile radio or Internet connection.
- mobile devices for example navigation devices in vehicles or mobile communication devices such as smartphones, notebooks with mobile radio adapters or other devices with mobile radio or Internet connection.
- the first measurement data 102 having the first fault tolerance 110 may be acquired by such fixedly installed devices, and the second measurement data 104 with the second fault tolerance may be recorded by such mobile devices.
- the second measurement data 104 can also be used to check the first measurement data. Thus, it may happen over time that the calibration of the first measurement data acquisition device 103 no longer meets the requirements. By recording the second measurement data 104 with the second
- FIG. 2 shows a schematic representation of a decentralized system 200 for processing vital data according to an embodiment.
- the distributed system 200 includes one or more decentralized communication devices 201, 203, 205 that are configured to communicate with one or more other decentralized ones
- Communication devices 201, 203, 205 to communicate.
- each of the decentralized communication devices 201, 203, 205 may utilize mobile patient software that may be executed on a communication device having distributed data fusion software.
- the decentralized communication devices 201, 203, 205 may utilize mobile patient software that may be executed on a communication device having distributed data fusion software.
- Communication devices 201, 203, 205 may access data from subscribers in a distributed fashion, such as on the subscriber's communication device 205, without having to store that data on a central server or on a plurality of distributed servers.
- Each of the decentralized communication devices 201, 203, 205 may have a
- the distributed network 102 may perform scaling of services and operations to be performed. For example, upon detection of a task to be performed on the subscriber
- Communication device 205 of this device 205 decide whether a detected event that signals a task to be performed, to be escalated, so that one or more participants devices 205 are informed thereof or whether the nursing service team to be informed. If the subscriber communication device 205 decides that, for example, the caregiver or nurse should be notified, the subscriber communication device 205 may use functionality of the decentralized data merge software to directly send a corresponding event, such as an alert or a message
- Caregiver / nurse communication device 201 to transmit.
- Caregiver / nurse communication device 201 may then receive the message and trigger a corresponding user interface event, eg on the screen, as sound or as a vibration. Furthermore, it can transmit a corresponding response to the subscriber communication device 205, for example, that the task to be fulfilled is taken over.
- the distributed system 200 includes a cloud services server that allows the network 210 to access other networks or components in the cloud.
- the decentralized system 200 includes diagnostic / monitoring systems 207, with which a diagnosis or monitoring of the network 210 and the communication devices 201, 203, 205 can be performed. With the diagnosis / monitoring systems 207, physicians or nurses can diagnose user equipment 205, monitor the effectiveness of interventional measures, and the like. For example, the efficiency of a care plan can be monitored, or diagnostic measures and possible contingency plans can be created and reviewed.
- the decentralized system 200 further includes medical sensor devices 213 for acquiring vital data of the patient, control devices 21 1 for controlling the
- the medical sensor devices 213, the fitness / wellness devices 215 and the control devices 21 1 can by a
- Subscriber communication device 205 are controlled so that each doctor / caregiver with his mobile subscriber communication device 205 can initiate a data acquisition on the patient.
- the medical sensor devices 213 can have a very low fault tolerance and, for example, be in conformity with the Medical Devices Act. You can e.g. correspond to the first measurement data acquisition devices 103 according to the description of FIG.
- the fitness / wellness devices 215 may have high fault tolerance, i. Compared to the medical sensor devices 213 perform a much less accurate measurement of vital signs and generally have no compliance with the Medical Devices Act.
- the fitness / wellness devices 215 may e.g. correspond to the second measurement data acquisition devices 105 according to the description of FIG.
- a method for evaluating the data received from the medical sensor devices 213 and the fitness / wellness devices 215 may be provided
- the method can carry out an evaluation of vital data, the vital data being recorded by devices with fault tolerance of a first type 213, ie the medical sensor devices 213 and Devices of a second kind, ie the fitness / wellness equipment.
- the fault tolerance of the first type is lower, in particular substantially lower than the fault tolerance of the second type.
- the devices with fault tolerance of the first type can be an identifier
- the devices with fault tolerance of the second type have essentially no identification and data of these devices with fault tolerance of the second kind are processed for the acquisition of vital data according to their calibration quality.
- Vital data from devices with fault tolerance of the second kind can be stored taking into account the calibration quality in a database for medical health care, for example via the
- the data of the fault-tolerant devices of the first type may be stored in a first database and the data of the fault-tolerant devices of the second type may be stored in a separate second database and data of the second database may be added by references to the data of the first database.
- the reference from the first database to the second database adds information about the calibration quality or fault tolerance of the first type, in particular as a form factor.
- the reference permits an abstraction of the data in such a way that no conclusion can be made about personal data which may be contained in the respective data.
- a system may perform the procedure and authenticate the communication devices connected to the Internet.
- the method can be carried out with a computer program.
- FIG. 3 shows a schematic representation of a method 300 for
- the method 300 may include the following steps: 1. Step: detecting 301 of first measurement data by a first measurement data acquisition device, wherein the first measurement data acquisition device for the acquisition of the first measurement data is calibrated with a first error tolerance and transmitting the first measurement data and a first calibration information on the
- 3rd step receiving 303 the first measurement data and the first calibration information from the first measurement data acquisition device and receiving the second measurement data and the second calibration information from the second measurement data acquisition device.
- 4th step Providing 304 of the first measurement data and the second measurement data with reference to the first calibration information and the second calibration information of the corresponding
- the method 300 can run on a measurement data processing system 100 as described for FIG.
- the first calibration information may include information about a quality of the first measurement data
- the second calibration information may include information about a quality of the second measurement data.
- the method 300 may further include the step of: displaying the second calibration information relating to conformity to a medical standard, in particular regarding compliance with the Medical Devices Act.
- the method 300 may be executed on the decentralized system 200 described in FIG. 2 or on the measurement data processing system 100 according to FIG. 1.
- 4 shows a schematic representation of a method 400 for data processing in a health cloud according to an embodiment.
- the method 400 for processing data in a health cloud comprises the following steps as shown in FIG. 4: 1.
- Step 401 Request Vital Data
- Step 2 402 query the available patient devices
- 3rd step 403 recording of the vital data by medical device with low fault tolerance and with quantitative calibration, possibly calibrated
- 4th step 404 recording the vital data by the fitness device with high fault tolerance and with qualitative calibration, possibly unequally
- Step 5 preparing the data (medical device) and reporting the raw data and calibration quality to the server
- 6th step 406 :
- Step 407 Evaluation of the data under
- the method may be performed in the health cloud 413, for example the decentralized system 200 for processing vital data, as described in FIG. Steps 1, 2, and 7 may be implemented on a server 410 in the health cloud 413, steps 3 and 6 may be on a medical device 41 1 in the health cloud, and steps 4 and 5 on a fitness device 412 in the health cloud be implemented.
- the server 410 may be a measurement data server 101 as described above with respect to FIG.
- the medical device 41 1 may be a first measurement data acquisition device 103, as described above for FIG. 1.
- the fitness device 412 may be a second measurement data acquisition device 105, as described above with reference to FIG. 1.
- the medical device 41 1 has a low fault tolerance compared to the fitness device 412. Therefore, the medical device 41 1 is also referred to as a first type device specified by its low fault tolerance.
- the fitness device 412 is referred to as a device of a second type or a second type, which is characterized by its high
- Fault tolerance is specified in comparison to that of the medical device.
- the fault tolerance of the medical device 41 1 may be in the range of 0.01% while the fault tolerance of the fitness device 412 may be in the range of 0.1%. These are just examples, other numerical values are equally possible where the fault tolerance of the medical Device 41 1 is less than or substantially less than the fault tolerance of the fitness device 412.
- the method 400 relates to data processing in a health cloud 413.
- the health cloud 413 is a data processing system for processing data from substantially medical devices that meet specific medical data acquisition and processing requirements.
- the data processing system may also be opened on a case-by-case basis with data from the environment of portable devices, including wearables (ie portable devices) coming from the field of consumer products, to the patient for use by the patient
- Case by case means that data from the patient's device will allow information about the progression and onset of a disease at a stage at a time when the patient was not yet in medical treatment with a medical or medical practitioner.
- the process essentially proceeds as follows:
- the health cloud 413 comprises a server 410, on which data of the first category are stored.
- medical devices 41 1 of low fault tolerance are included.
- the low fault tolerance of the devices 41 1 is determined primarily by the Medical Devices Act.
- fitness devices 412 such as pulse monitors or pedometer, which have a high fault tolerance, which are not subject to the Medical Devices Act.
- These can be included in the Health Cloud 413 on a case-by-case basis, especially if, in a medical emergency, the data of the pulse meters of other fitness equipment make the evaluation of the data seem desirable.
- the fitness device 413 can in particular be connected to the health cloud 413 via a mobile communication interface, for example Bluetooth.
- the patient or the healer, who incorporates the device 412, can thus immediately receive an indication of the calibration quality and the conformity to the standard of the Medical Devices Act. This can be done, for example, by signaling in traffic light colors, wherein a low deviation can be characterized by a green signal color in the measured value display and a higher deviation can be indicated by a yellow or red signal color.
- the method 400 can proceed in detail as follows:
- step 401 vital data are only interrogated by the different types of devices.
- step 402 the query of the available patient devices takes place.
- step 403 the vital data is recorded by the medical device 41 1 with low fault tolerance and with qualitative calibration, which may also be calibrated.
- step 104 the vital data is recorded by the fitness device 412 with high fault tolerance and with qualitative calibration, which is essentially un-calibrated, by means of a reference.
- step 405 the preparation of the data and notification of the raw data and
- step 406 the preparation of the data and notification of the raw data
- the rendering can be done by adding a form factor.
- step 407 the evaluation of the data takes place taking into account the
- the device data and calibration quality can also be stored in a database due to the design conformity.
- the devices can then be identified on the basis of the identifier, in particular a serial number in a trust center.
- the Calculation of the fault tolerance is rendered obsolete and the manufacturer's instructions can preferably be used to determine the calibration tolerance.
- devices 412 of high fault tolerance may be incorporated into a medical data acquisition system (Health Cloud 413) with devices 41 1 of substantially low fault tolerance on a case-by-case basis
- Measured variables from different systems can be detected on the basis of multi-sensor modules.
- the devices 412, 413 can communicate automatically and allow the physician or nursing staff a more accurate analysis of the condition of the patient due to the larger measurement database.
- the diagnosis of the patient can be based on an extensive information base, i. not only the data of the medical devices 41 1 alone can be used for the diagnosis, but also measured data from the private environment created by patients can be included in the diagnosis.
- the method 400 may be executed on the decentralized system 200 described in FIG. 2 or on the measurement data processing system 100 according to FIG. 1.
- An aspect of the invention also includes a computer program product that can be loaded directly into the internal memory of a digital computer and
- the computer program product may be on a computer-suitable medium
- Computer readable program means which cause a computer, first measured data by a first
- Measuring data acquisition device to capture, with the first
- Measurement data acquisition device for the detection of the first measurement data is calibrated with a first error tolerance and to transmit the first measurement data and a first calibration information on the calibration of the first measurement data acquisition device; second measurement data to be detected by a second measurement data acquisition device, wherein the second measurement data acquisition device is calibrated for the detection of the second measurement data with a second error tolerance, wherein the first error tolerance is smaller than the second error tolerance, and the second measurement data and a second calibration information to be transmitted via the calibration of the second measurement data acquisition device; the first measurement data and the first calibration information from the first
- Receive measurement data acquisition device and receive the second measurement data and the second calibration information from the second measurement data acquisition device; and the first measurement data and the second measurement data with reference to the first calibration information and the second calibration information of the corresponding
- the computer may be a PC, for example a PC of a computer network.
- the computer may be implemented as a chip, an ASIC, a microprocessor or a signal processor, and may be implemented in a computer network, such as a computer
- Measurement data processing system 100 as described in Figure 1 or in one
- Embodiments of the invention may be implemented in individual circuits, partially integrated circuits, or fully integrated circuits or programming means.
- the term "for example” is meant to be an example rather than the best or optimal, certain embodiments have been illustrated and described herein, but it will be apparent to those skilled in the art that a variety of alternative and / or similar implementations may be substituted for those shown and shown described embodiments can be realized without departing from the concept of the present invention. LIST OF REFERENCE NUMBERS
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Abstract
Description
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DE102015108447.3A DE102015108447B4 (de) | 2015-05-28 | 2015-05-28 | Messdatenverarbeitungssystem |
PCT/EP2016/060982 WO2016188795A1 (de) | 2015-05-28 | 2016-05-17 | Messdatenverarbeitungssystem |
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EP3304375A1 true EP3304375A1 (de) | 2018-04-11 |
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EP16726493.6A Withdrawn EP3304375A1 (de) | 2015-05-28 | 2016-05-17 | Messdatenverarbeitungssystem |
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US (1) | US20180146928A1 (de) |
EP (1) | EP3304375A1 (de) |
JP (1) | JP2018522311A (de) |
KR (1) | KR20170139679A (de) |
CN (1) | CN107683508A (de) |
CA (1) | CA2986938A1 (de) |
DE (1) | DE102015108447B4 (de) |
RU (1) | RU2017140771A (de) |
WO (1) | WO2016188795A1 (de) |
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US6454709B1 (en) * | 2000-08-29 | 2002-09-24 | Peter Kleinschmidt | Tele-evaluation system, especially for medicine |
US8919605B2 (en) * | 2009-11-30 | 2014-12-30 | Intuity Medical, Inc. | Calibration material delivery devices and methods |
SE536114C2 (sv) * | 2010-08-25 | 2013-05-14 | Zafena Ab | System och metod för kommunicering av testdata från kliniska analysenheter till ett elektroniskt patientinformationshanteringssystem |
DE102010062657B4 (de) * | 2010-12-08 | 2023-08-31 | Endress + Hauser Wetzer Gmbh + Co Kg | Bereitstellung von Kalibrierungsdaten zu Messeinrichtungen |
US20120165639A1 (en) * | 2010-12-22 | 2012-06-28 | Roche Diagnostics Operations, Inc. | Storage of calibration data at a continuous glucose monitor |
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2015
- 2015-05-28 DE DE102015108447.3A patent/DE102015108447B4/de active Active
-
2016
- 2016-05-17 CA CA2986938A patent/CA2986938A1/en not_active Abandoned
- 2016-05-17 CN CN201680031115.4A patent/CN107683508A/zh active Pending
- 2016-05-17 KR KR1020177034436A patent/KR20170139679A/ko not_active Application Discontinuation
- 2016-05-17 WO PCT/EP2016/060982 patent/WO2016188795A1/de active Application Filing
- 2016-05-17 EP EP16726493.6A patent/EP3304375A1/de not_active Withdrawn
- 2016-05-17 RU RU2017140771A patent/RU2017140771A/ru not_active Application Discontinuation
- 2016-05-17 JP JP2017556698A patent/JP2018522311A/ja active Pending
- 2016-05-17 US US15/577,497 patent/US20180146928A1/en not_active Abandoned
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CN107683508A (zh) | 2018-02-09 |
JP2018522311A (ja) | 2018-08-09 |
DE102015108447A1 (de) | 2016-12-01 |
KR20170139679A (ko) | 2017-12-19 |
US20180146928A1 (en) | 2018-05-31 |
WO2016188795A1 (de) | 2016-12-01 |
RU2017140771A (ru) | 2019-07-03 |
DE102015108447B4 (de) | 2017-12-07 |
CA2986938A1 (en) | 2016-12-01 |
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