Abstract: A process, establishing Bluetooth pairing between a patient sensor (1) and a patient monitor (2), includes docking energy contacts (3) of the patient sensor with charging contacts (4) of a charging device (5) for charging a battery (6) of the patient sensor with an automatic detection of docking of the patient sensor with the charging device by a monitor detection device (7) of the patient monitor. The patient monitor is brought into a state of readiness for establishing Bluetooth pairing with the patient sensor. Patient sensor and charging device docking is automatically detected by a sensor detection device (8) of the patient sensor. The patient sensor is brought into a state of readiness for establishing Bluetooth pairing with the patient monitor. Bluetooth pairing between the patient sensor and the patient monitor is automatically established. A patient monitor system (20) is configured for carrying out the process.

Abstract: A person sensor system (1) includes a person sensor (2) to determine personal parameters of a person, a holding device (3) for holding the person sensor (2) on an article of clothing of the person in interaction with the person sensor (2) and a magnetic device (4) with a first magnetic device section (5) and with a second magnetic device section (6) for attracting each other by magnetic force. The first magnetic device section (5) is arranged at the person sensor (2) and the second magnetic device section (6) is arranged at the holding device (3). A magnetic field detection device (7) detects a magnetic field of the magnetic device (4). The person sensor system (1) is configured to set an operating state of the person sensor system (1) as a function of the magnetic field detected. A person monitoring system (28) includes the person sensor system (1).

Abstract: Methods and systems are described for providing an editor for modifying predefined data match policies. The methods and systems can receive search requests including search criteria and obtain data records and a plurality of respective data match policies for the data records that correspond to the search criteria. The methods and systems can display a first set of data records and a second set of data records. The first set of data records may match the search criteria and the second set of data records may be identified as a partial match to one or more data match policies associated with the first set of data records. The methods and systems can receive a request to modify a data match policy corresponding to at least one of the second set of data records and generate and display a plurality of suggestions for executing the at least one request.

Abstract: Methods and systems are described for providing an editor for modifying predefined data match policies. The methods and systems can receive search requests including search criteria and obtain data records and a plurality of respective data match policies for the data records that correspond to the search criteria. The methods and systems can display a first set of data records and a second set of data records. The first set of data records may match the search criteria and the second set of data records may be identified as a partial match to one or more data match policies associated with the first set of data records. The methods and systems can receive a request to modify a data match policy corresponding to at least one of the second set of data records and generate and display a plurality of suggestions for executing the at least one request.

Abstract: Qualification of data matches can be improved relative to existing approaches by use of first, second, and third similarity criteria, which can be used to identify a set of near match record pairs, identify a set of actual match record pairs and to flag as near matches those record pairs of the set of near matches that were identified as actual matches, and to identify and flag one or more suspect matches.

Abstract: Systems and methods for matching data based on numeric difference are described herein. Input data elements are parsed to identify a first number and a second number. A difference between the first number and the second number is calculated based on a predefined formula. Based on the difference, a matching score between the input data elements is evaluated. The matching score is proportional to a base matching score corresponding to a threshold difference, and a maximum score corresponding to a match between the first number and the second number. A similarity between the input data elements is reported based on the evaluated matching score.

Abstract: Qualification of data matches can be improved relative to existing approaches by use of first, second, and third similarity criteria, which can be used to identify a set of near match record pairs, identify a set of actual match record pairs and to flag as near matches those record pairs of the set of near matches that were identified as actual matches, and to identify and flag one or more suspect matches.

Abstract: Systems and methods for matching data based on numeric difference are described herein. Input data elements are parsed to identify a first number and a second number. A difference between the first number and the second number is calculated based on a predefined formula. Based on the difference, a matching score between the input data elements is evaluated. The matching score is proportional to a base matching score corresponding to a threshold difference, and a maximum score corresponding to a match between the first number and the second number. A similarity between the input data elements is reported based on the evaluated matching score.