Abstract: Embodiments are directed to detecting and uploading measurement data of a non-connected medical measuring device. Embodiments include capturing an image of an identification object and a beginning event image of a medical measuring device and extracting identification data from the image of the identification object. Based on detecting that the identification object has been removed, an ending event image of the medical measuring device is captured. Embodiments include determining if a measurement event has occurred by comparing the ending event image and the beginning event image. Based on determining that the measurement event occurred, a measurement data of the ending event image is extracted and upload to a personal health record database.

Abstract: A method for generating a lifestyle progression (LSP) plan for a patient subject includes collecting patient data including a list of exercise activities performed over a plurality of non-overlapping periods for a plurality of patients and patient health records. The collected patient data is clustered into related groups using k-mean clustering. An LSP model for each cluster is created by averaging the exercise activities performed and respective period durations. Patient data for a patient subject including patient health records is received. A vector is calculated for the received patient data. A shortest distance between the calculated vector for the received patient data and vectors calculated for each LSP model is found. An LSP is built for the patient subject bases on the LSP model with the shortest distance to the calculated vector for the received patient data.

Abstract: Embodiments are directed to detecting and uploading measurement data of a non-connected medical measuring device. Embodiments include capturing an image of an identification object and a beginning event image of a medical measuring device and extracting identification data from the image of the identification object. Based on detecting that the identification object has been removed, an ending event image of the medical measuring device is captured. Embodiments include determining if a measurement event has occurred by comparing the ending event image and the beginning event image. Based on determining that the measurement event occurred, a measurement data of the ending event image is extracted and upload to a personal health record database.