DE102004007698A1 - Method for detecting, wireless forwarding and processing multi-sensor signals - Google Patents

Abstract

Method for detecting, wireless forwarding and processing multi-sensor signals for observing and / or influencing stationary and / or mobile objects, wherein a plurality of autonomous sensors (1) for detecting physical measured values (2) on an object to be observed (3 ), wirelessly networked with each other, measurement-specific algorithms are wirelessly transmitted to the sensors, and preprocessed sensor data is received, pre-checked, processed, visualized and / or stored in a base station (4) and / or forwarded to at least one higher-level data processing system (6) be connected either locally or via a telecommunications network (7) with grid feed (8).

Description

overall task

Task of the MSAN network ( 1 ) is to use several autonomous sensors Si ( 1 ) used to acquire physical measurements ( 2 ) (eg temperature, humidity, oxygen content, precipitation, etc.) on the object to be observed ( 3 ), ie wirelessly by means of radio transmission ( 5 ) to cross-link the measurement-specific algorithms in the sensors with the preprocessed sensor data in a base station ( 4 ), to process, further process, visualize and store or to higher-level data processing systems ( 6 ), either suburban or via a telecommunications network ( 7 ) with mains supply ( 8th ) can also be connected remotely. The base station to grid connection can be wired as well as wireless ( 9 ). Optionally, the results of the sensor data analysis in the base station in the sense of a cascade control can also be used for controlling or regulating, ie for influencing the state of the object to be observed. For this purpose, control data ( 10 ) from the base station wirelessly to actuators ( 11 ), which directly affect the state of the object (eg shutting down a machine when a critical operating temperature has been reached). Integration of object data into a higher-level data processing system for object management (object data, object history, maintenance, maintenance and service information as well as other master data) via a defined data interface ( 13 )

application areas for this Methods are in various industries z.Bsp. mechanical engineering (Condition monitoring of rotating machines or driverless transport systems) or in medical technology (eg patient monitoring with several vital sensors).

individual tasks

• 1. Process phase 1 (MSAN network configuration & parameter setting) 1.1 Definition of the network topology including network identification and object name 1.2 Definition of the measured and control values to be recorded ( 2 ) (Type, number) 1.3 Definition of the measured value-specific preprocessing algorithms ( 40 ) and their parameterization ( 41 ) as well as the operating mode - PA mode ("permanently active"): Sensor transmits with set sampling frequency - DA mode ("dormant active"): Sensor only transmits the measured values after fulfillment of set conditions 1.4 Individual sensor and actuator configuration including software load 1.5 Power supply of Sensors and Actuators (Inductive Battery Charging) 1.6 Testing and Verification of Sensors and Actuators by IR Interface 1.7 A-priori network testing by autonomous "built-in-selft-test" (BIST) procedure 1.8 Attachment of sensors and actuators on Observing object 1.9 Individual examination of the individual sensors / actuators on the object 1.10. Checking the entire network at the object 1.11 Checking the network observation by remote monitoring device In the case of a control / additional task 1.12 Determining the actuators to be controlled ( 11 ) 1.13 Parameterization of the actuators
• 2. Process Phase 2a (MSAN grid operation - off line (island operation » 2.1 Measuring mode with automatic monitoring of the object to be observed 2.2 Measuring mode with manual monitoring individual measured values on the object to be observed (either via PC or over Display with menu buttons at the base station) 2.3 Reconfigure measuring mode with and reparameterize individual sensors
• 3. Process Phase 2b (MSAN network operation - online) 3.1 As 2.1 but with full integration in real-time operation into a parent DV structure for the object management
• 4. Autonomous self-monitoring while MSAN operation 4.1 Monitoring the power supply of individual sensors 4.2 Monitoring the signal processing of individual sensors 4.3 Plausibility check the received measured values of individual sensors

solution

central Element of the MSAN network are the sensors. They are the object a separate patent and are not described here. The process description varies from application to application. In the concrete present Invention application is based on a medical application, where the to be monitored Object is a human.

In the process phase 1 computer-aided the configuration and parameterization takes place on a PC. The user can set the number of sensors and actuators and set the following for each individual sensor:
a) Physical reading b) Lower alarm threshold c) Upper alarm threshold) Signal processing pro (Algorithm) e) Threshold (s) leading to the triggering of an alarm f) "Life Pulse" Time interval after which the sensor sends a data string, according to which the
G) PA or DA operating mode h) Network identification code to avoid interference with other nearby MSAN networks i) Patient identification code Actuator identifier (also includes h) and i »

After the network configuration, the preparation and individualization of the sensors takes place. For this purpose, reusable sensor body ( 10 ) with a measured-value-specific sensor / electronic unit (SEU) ( 21 ) Mistake. On the SEU is the actual sensor (chip) ( 26 ), the transmitting and receiving unit (Rx / Tx) ( 27 ) as well as the energy supply by means of inductively rechargeable battery ( 22 ). The preconfigured sensor will now enter the sensor configuration box (SCB) ( 23 ), which are connected to a PC ( 6 ) on which the network configuration has been loaded. The SCB includes a bi-directional IR interface ( 24 ) and an inductive charging device ( 25 ). After inserting the sensor, the SCB activates the sensor, carries out a complete functional test and, including the battery charge status, reports the results of the functional test to the PC. If all test data are in the green range, the "download" of the sensor software along with all parameter setting and configuration data takes place.

The actuators are generally a miniaturized transmit / receive electronic units ( 30 ), signal conditioning with optional D / A converter ( 31 ), which is a standard control signal (analog 4 ... 20 passive or active) or digital ( 35 ) for a servo or an actuator ( 32 ) and a rechargeable battery ( 12 ) to the autonomous energy supply. These components are housed in a compact actuator electronic unit (AEU) ( 34 ) integrated. The actuators have a different attachment mechanism or base body (depending on the location and servo or actuator design ( 33 ).

When wireless transmission method comes for applications in health care a radio transmission im for Medical devices regulated frequency band of 402-405 Mhz in question. The transmission power gets on the body Environment and should not exceed a target range of <2m 25uW. The transfer according to standardized Communication VITAL according to the standard ENV 13734/13735.

Before the sensor or actuator is removed from the SEU and attached to the patient, the activation or testing of the radio transmission takes place ( 5 ). This is done from the PC via the base station ( 4 ) sends an activation signal to the relevant sensor. The sensor is always in the ground state in the so-called DA mode (dormant active) to save energy. After the sensor is ready to receive, the so-called BIST procedure ("built-in self-test") is activated in the sensor. A self-check is carried out by means of software, the test results including all software, configuration and parameter data are sent back to the base station and from there to the PC. There, the comparison with the original data and the test passed the release of the sensor for attachment.

If all sensors or actuators are prepared in this way, the successive testing of the individual sensors takes place on humans. The received data are either manually checked by qualified personnel (eg the attending physician) on the PC screen or the data are automatically checked for abnormalities based on reference data (eg ECG database signatures). The same applies to the actuators. Pattern control signals (eg, jump function) are sent via the MSAN network to the individual actuators via the PC. The check is carried out either manually (eg by electrical measurement of the actuator control signal) or by tapping via IR interface ( 24 ).

To the attachment and verification of all Sensors and actuators via software on the PC take place in the last step the transfer the previously set in the network configuration part monitoring quantities to the remote monitoring device or the parent Patient data acquisition system (electronic patient record).

In front the beginning of the actual MSAN network operation phase has yet to be determined like patient monitoring has to take place: a) within a defined LAN area such. Eg hospital, house b) in an open environment Depending on the application is to select the transmission technology and to configure the base station. The configuration can be be fixed (a dedicated, hardwired station for the selected network e.g. DECT, Bluetooth, GSM »or but modular, i. the configuration is done by software selected in the base station.

With this last step, the entire value chain ( 5 ) closed.

The process phase 2 is the actually interesting operating phase of the MSAN network. This shows the presentation of the value creation network 4 ,

Clearly recognizable is the cascade control loop structure with the feedforward control known from control technology. The fastest one The actuation takes place via the actuation of the actuators directly from the base station. Are z. Ex. Critical blood glucose levels exceeded. An insulin pump on the patient can intervene immediately. The process is automatically registered by the base station and registered via the IT network in the patient database. The sensors can be used to monitor and store the body reactions to the automatically administered drug. If a doctor is on-site (nursing staff, home or emergency doctor), he can download all the data of interest to him via notebook from the base station or directly access the most important data via the display on the base station. Normally, therapies initiated by the physician can be immediately recorded offline and transmitted to the hospital. Thus, vital measures can be initiated before the patient is admitted.

in the Normal case may be a first aid or analysis of patient data also over a care center or telemedicine service center.

In In process phase 2a, the MSAN network is not over IT network with a spatial remote doctor, telemedicine center or hospital. There is also a direct connection to a patient database Not. All data is offline in the base station or in the local PC saved. Within this mode, however, is an automatic monitoring possible (e.g. while the patient is sleeping important vital parameters are recorded and monitored by the MSAN network as well as recorded). Through optical and acoustic signals can alert the patient to an alarm condition.

alternative can do this The expert personnel manually monitor individual values. Should be due a new treatment situation individual sensors or parameters reconfigured (e.g., more frequent Measurement and transmission of temperature values, other triggering thresholds for alarms), this can be done wirelessly via base station or connected PC.

In the process phase 2b is the entire MSAN network and thus the full regulatory strategy active. This can vary depending on the patient's condition in the fastest possible Time all the necessary measures be initiated.

There the entire network relies on the validity of the sensor signals is all network components (sensors, actuators, transmission links etc.) in freely selectable or adjustable time intervals with pattern sequences and test signals subjected to a test. This is not a problem in that far, very much many vital signs measured with today's processing speeds transmit low clock frequencies and evaluated. The principle of BIST functions is based on the injection of defined signatures at the beginning of the value chain (e.g., sensors) and measuring the response function of the entire network. This technique, too, comes from systems theory or control engineering and offers a high level of Safety.

5 shows a monitor display, as they can be used when using the invention in the field of patient monitoring with advantage.

Claims (5)

Method for detecting, wireless forwarding and processing multi-sensor signals for observing and / or influencing stationary and / or location-variable objects, wherein - a plurality of autonomous sensors ( 1 ) used to acquire physical measurements ( 2 ) on an object to be observed ( 3 ), are wirelessly networked with each other, - measurement-specific algorithms are transmitted wirelessly to the sensors, and - preprocessed sensor data in a base station ( 4 ) are received, pre-checked, processed, visualized and / or stored and / or to at least one higher-level data processing system ( 6 ), either locally or via a telecommunications network ( 7 ) with mains supply ( 8th ) connected. Method according to claim 1, characterized in that that the Connection between the base station and the grid feeder either wired or wireless. Method according to claim 1 or 2, characterized in that that of the sensors ( 1 ) are subjected to sensor data of a sensor data analysis in the base station and the results of the sensor data analysis in the base station in the sense of a cascade control for control and / or regulation in the sense of influencing the state of the object to be observed are used. Method according to Claim 3, characterized in that the control data ( 10 ) from the base station wirelessly to actuators ( 11 ) are transmitted, which act directly on the object state. Method according to one of the preceding claims, characterized in that the object data in a higher-level data processing system for object management (object data, object history, maintenance, care and service, information and other master data) via a defined Data interface to be integrated.