Abstract: The disclosure relates to a method and a system for determining a carbohydrate intake event from glucose monitoring data indicative of a glucose level in a system having a data processing device provided with one or more processors.

Abstract: Disclosed is a portable device for collecting and processing continuous monitoring data. The device has a data interface configured to receive a stream of continuous monitoring data from a body-worn sensor, the continuous monitoring data being indicative of an analyte in a bodily fluid. A control is connectable to the data interface. The control controls a first mode of operation during which configuration parameters are established in response to receiving a start signal indicating a sensor session start of the body-worn sensor. The control also controls a second mode of operation during which the continuous monitoring data is collected and processed and also controls the switching from the first mode to the second mode. The control blocks further starting of the first mode for a remaining sensor session time after the switching to the second mode of operation. Also disclosed are a related medical system, method and computer program product.

Abstract: A computer-implemented method and a system for analyzing glucose monitoring data indicative of a glucose level, comprising: presenting by a data processing device provided a graphical window on a display device wherein the graphical window comprises a time abscissa axis that defines time units, and a glucose ordinate axis that defines glucose units; receiving a plurality of glucose monitoring values associated with a monitoring time period by the data processing device; segmenting the plurality of glucose monitoring values into a plurality of glucose monitoring traces indicative of the glucose level; defining a reference trace segment; determining the reference trace segment for each of the plurality of glucose monitoring traces; and plotting, for a time window comprising the reference trace segment, the plurality of glucose monitoring traces within the graphical window. Furthermore, a non-transitory computer readable medium is disclosed.

Abstract: A computer-implemented method and a system for analyzing glucose monitoring data indicative of a glucose level, comprising: presenting by a data processing device provided a graphical window on a display device wherein the graphical window comprises a time abscissa axis that defines time units, and a glucose ordinate axis that defines glucose units; receiving a plurality of glucose monitoring values associated with a monitoring time period by the data processing device; segmenting the plurality of glucose monitoring values into a plurality of glucose monitoring traces indicative of the glucose level; defining a reference trace segment; determining the reference trace segment for each of the plurality of glucose monitoring traces; and plotting, for a time window comprising the reference trace segment, the plurality of glucose monitoring traces within the graphical window. Furthermore, a non-transitory computer readable medium is disclosed.

Abstract: A method for characteristic monitoring in conjunction with a mode of continuously measured blood glucose values, in a monitor apparatus provided with a processor, a memory, a data interface, an input device, and a signaling device, the method comprising: providing a first set of event specific characteristics assigned to a first event, the first set of event specific characteristics being different from a second set of event specific characteristics assigned to a second event which is different from the first event, receiving blood glucose value data performing a safety check by comparing the first set of event specific characteristics to present characteristics derived from the blood glucose value data and/or the characteristic values, generating a warning signal or generating a safety signal, and outputting an output signal. A monitor apparatus is also disclosed.

Abstract: A handheld display device for processing continuous sensor data has a communication interface, a graphical user interface having a gesture recognition component, a processor and a memory. The processor continuously receives time dependent sensor data, carbohydrate data, event data, and insulin data. The event data is indicative of a physical state of the subject. The processor determines a sensor data scaling factor, a carbohydrate data scaling factor and an insulin data scaling factor. The processor controls the graphical user interface to render a plot having single time, analyte concentration, carbohydrate amount, and insulin delivery amount axes. The analyte concentration axis is rendered on a first side of the plot and carbohydrate amount and insulin delivery amount axes are rendered on an opposite side of the plot, according to the scaling factors. The graphical user interface can be controlled with single and/or double finger gestures to magnify, shrink or shift axes.

Abstract: A method for analysing physiological measurement values of a user is proposed. The method comprises at least one data acquisition step, wherein, during the data acquisition step, physiological measurement values of the user are acquired at different measurement times and stored in a measurement data record; at least one pattern selection step, wherein, during the pattern selection step, measurement values acquired during one comparison time interval are selected as at least one comparison pattern; and at least one pattern recognition step, wherein, during the pattern recognition step, patterns corresponding to the comparison pattern are sought after in the measurement data record.

Abstract: The application relates to a method for analyzing continuously monitored physiological measurement values of a user, the method being performed in a data processing system and comprising: providing, by a data interface, a set of present physiological measurement values, determining whether a common pattern of values is contained in both the set of present physiological measurement values and a set of historical physiological measurement values, if the common pattern of values is found, requesting the user to provide contextualization for at least the present physiological measurement values of the common pattern of values, receiving contextualization and storing contextualized data. Furthermore, the application relates to a device for analyzing continuously monitored physiological measurement values of a user.

Abstract: The application relates to a method for analyzing continuously monitored physiological measurement values of a user, the method being performed in a data processing system and comprising: providing, by a data interface, a set of present physiological measurement values, determining whether a common pattern of values is contained in both the set of present physiological measurement values and a set of historical physiological measurement values, if the common pattern of values is found, requesting the user to provide contextualization for at least the present physiological measurement values of the common pattern of values, receiving contextualization and storing contextualized data. Furthermore, the application relates to a device for analyzing continuously monitored physiological measurement values of a user.

Abstract: A method for analysing physiological measurement values of a user is proposed. The method comprises at least one data acquisition step, wherein, during the data acquisition step, physiological measurement values of the user are acquired at different measurement times and stored in a measurement data record; at least one pattern selection step, wherein, during the pattern selection step, measurement values acquired during one comparison time interval are selected as at least one comparison pattern; and at least one pattern recognition step, wherein, during the pattern recognition step, patterns corresponding to the comparison pattern are sought after in the measurement data record.

Abstract: A method for analysing physiological measurement values of a user is proposed. The method comprises at least one data acquisition step, wherein, during the data acquisition step, physiological measurement values of the user are acquired at different measurement times and stored in a measurement data record; at least one pattern selection step, wherein, during the pattern selection step, measurement values acquired during one comparison time interval are selected as at least one comparison pattern; and at least one pattern recognition step, wherein, during the pattern recognition step, patterns corresponding to the comparison pattern are sought after in the measurement data record.

Abstract: A method for analyzing physiological measurement values of a user is proposed. The method comprises at least one data acquisition step, wherein, during the data acquisition step, physiological measurement values of the user are acquired at different measurement times and stored in a measurement data record; at least one pattern selection step, wherein, during the pattern selection step, measurement values acquired during one comparison time interval are selected as at least one comparison pattern; and at least one pattern recognition step, wherein, during the pattern recognition step, patterns corresponding to the comparison pattern are sought after in the measurement data record.

Abstract: A patient diabetes monitoring system with an efficient unsupervised daily monitoring profile clustering algorithm, a method, and a computer product thereof are disclosed. The system may include a physiological data input device or sensor which receives a plurality of physiological measurements to generate a dataset, a memory which stores a clustering algorithm, and a processor. The clustering algorithm when executed by the processor, causes the processor to automatically pre-process the dataset to control an amount of bias/aggressiveness from the collected unsupervised daily monitoring profiles, thereby generating a pre-processed dataset, build a similarity matrix from the pre-processed dataset, and output an optimum number of similarity clusters found by the processor from the similarity matrix.

Abstract: The disclosure relates to a method and a system for determining a carbohydrate intake event from glucose monitoring data indicative of a glucose level in a system having a data processing device provided with one or more processors.

Abstract: A method for analysing physiological measurement values of a user is proposed. The method comprises at least one data acquisition step, wherein, during the data acquisition step, physiological measurement values of the user are acquired at different measurement times and stored in a measurement data record; at least one pattern selection step, wherein, during the pattern selection step, measurement values acquired during one comparison time interval are selected as at least one comparison pattern; and at least one pattern recognition step, wherein, during the pattern recognition step, patterns corresponding to the comparison pattern are sought after in the measurement data record.

Abstract: A method for analysing physiological measurement values of a user is proposed. The method comprises at least one data acquisition step, wherein, during the data acquisition step, physiological measurement values of the user are acquired at different measurement times and stored in a measurement data record; at least one pattern selection step, wherein, during the pattern selection step, measurement values acquired during one comparison time interval are selected as at least one comparison pattern; and at least one pattern recognition step, wherein, during the pattern recognition step, patterns corresponding to the comparison pattern are sought after in the measurement data record.

Abstract: A sensor device for detecting at least one analyte in a body fluid of a user. The sensor device includes an evaluation device for evaluating a data stream of time-dependent concentrations c of the analyte. The evaluation device includes a comparator device for comparing a current value c(t) of the concentration c with a first threshold value L and a second threshold value H, wherein H>L. The evaluation device defines a tolerance time interval. Further, the evaluation device, by using the comparator device, is configured to detect if the concentration c rises and exceeds the first threshold value L during the tolerance time interval and to prepare a warning signal W accordingly. The evaluation device is configured to suppress an output of the warning signal W at least until the tolerance time interval expires, under the precondition that c(t)<H during the tolerance time interval.

Abstract: A handheld display device for processing continuous sensor data has a communication interface, a graphical user interface having a gesture recognition component, a processor and a memory. The processor continuously receives time dependent sensor data, carbohydrate data, event data, and insulin data. The event data is indicative of a physical state of the subject. The processor determines a sensor data scaling factor, a carbohydrate data scaling factor and an insulin data scaling factor. The processor controls the graphical user interface to render a plot having single time, analyte concentration, carbohydrate amount, and insulin delivery amount axes. The analyte concentration axis is rendered on a first side of the plot and carbohydrate amount and insulin delivery amount axes are rendered on an opposite side of the plot, according to the scaling factors. The graphical user interface can be controlled with single and/or double finger gestures to magnify, shrink or shift axes.

Abstract: Disclosed is a portable device for collecting and processing continuous monitoring data. The device has a data interface configured to receive a stream of continuous monitoring data from a body-worn sensor, the continuous monitoring data being indicative of an analyte in a bodily fluid. A control is connectable to the data interface. The control controls a first mode of operation during which configuration parameters are established in response to receiving a start signal indicating a sensor session start of the body-worn sensor. The control also controls a second mode of operation during which the continuous monitoring data is collected and processed and also controls the switching from the first mode to the second mode. The control blocks further starting of the first mode for a remaining sensor session time after the switching to the second mode of operation. Also disclosed are a related medical system, method and computer program product.

Abstract: Disclosed is a portable device for processing continuous monitoring data. The portable device includes a data interface that receives a stream of continuous monitoring data from a body-worn sensor. The data is indicative of an analyte in a bodily fluid. The portable device also includes a storage device that can store the continuous monitoring data. The control processes the continuous monitoring data and is switchable between first and second modes of operation during a sensor session of the body-worn sensor. In the first mode of operation, the control is configured to provide video data indicative of the continuous monitoring data for outputting by a display. In the second mode of operation the control is configured to store the continuous monitoring data in the storage device and to block the continuous monitoring data from being displayed on the display. A related method, system and computer program product are also disclosed.