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 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 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 of enhancing readability of a graph showing glucose values received from a continuous glucose monitoring device (CGM) on the display of a handheld device includes receiving a plurality of CGM glucose values separated by a first fixed time interval. A second fixed time interval at which to display at least a portion of the plurality of CGM glucose values is received. The second fixed time interval is greater than the first fixed time interval. A computer processor of the handheld device determines a characteristic CGM glucose value at a preselected fixed time for each of a sequence of second fixed time intervals within a patient-specified time period. Each characteristic CGM glucose value is derived from two or more received CGM values centered about the preselected fixed time in the corresponding second fixed time interval. The characteristic CGM glucose values for a patient-selected period of time on the display.

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 of enhancing readability of a graph showing glucose values received from a continuous glucose monitoring device (CGM) on the display of a handheld device includes receiving a plurality of CGM glucose values separated by a first fixed time interval. A second fixed time interval at which to display at least a portion of the plurality of CGM glucose values is received. The second fixed time interval is greater than the first fixed time interval. A computer processor of the handheld device determines a characteristic CGM glucose value at a preselected fixed time for each of a sequence of second fixed time intervals within a patient-specified time period. Each characteristic CGM glucose value is derived from two or more received CGM values centered about the preselected fixed time in the corresponding second fixed time interval. The characteristic CGM glucose values for a patient-selected period of time on the display.