The Utility of Shapelets for Analyzing Physical Activity of COPD Patients and nonCOPD controls Physical activity is an attractive endpoint for novel therapies in Chronic Obstructive Pulmonary Disease (COPD). However, a deep understanding about COPD physical activity patterns and disease severity is lacking. In this research, we study the physical activity patterns for 184 individuals with and without COPD from a single center in the COPDGene cohort. These subjects participated in a 3week observational study wearing wristworn accelerometers for collecting physical activity data. Our exploratory data analysis finds using the whole range of activity data is insufficient for patient clustering. Alternatively, we use shapelets, small and local subsequences, to better capture patientsu0027 behaviors in different groups. We develop a lengthbound heuristic algorithm for choosing the subset that has the best clustering result. The study shows the potentials of using shapelets for helping providers in assessing COPD patientsu0027 status.

Mobile Apps to Quantify Aspects of Physical Activity: a Systematic Review on its Reliability and Validity The purpose of this study was to systematically review and evaluate the evidence on the accuracy (validity) and consistency (reliability) of mobile apps used to quantify physical activity. Systematic literature searches were conducted in Pubmed, Science Direct, Web of Science, Physiotherapy Evidence Database (PEDro), Academic Search Complete and IEEE Xplore. Studies were included if they reported on the validity andor reliability of a mobile application aiming primarily at measuring physical activity in humans with or without pathology. The reference lists of included articles were also screened for reports not identified through electronic searches. The methodological quality of included studies was assessed by 2 independent reviewers and data extracted by one reviewer and checked for accuracy by a second reviewer. A total of 25 articles were included in this review, of which 18 refer to validity and 7 to both validity and reliability. Mean percentage difference was used as an indicator of validity and varied between 0.1% and 79.3%. Intraclass Correlation Coefficients varied between 0.02 and 0.99 indicating poor to excellent reliability. There is conflicting and insufficient evidence on the validity and reliability, respectively, of apps for measuring physical activity. Nevertheless, velocity and the place where the smartphone is carried seem to have an impact on validity.