Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations

JH Migueles, C Cadenas-Sanchez, U Ekelund… - Sports medicine, 2017 - Springer
Background Accelerometers are widely used to measure sedentary time, physical activity,
physical activity energy expenditure (PAEE), and sleep-related behaviors, with the …

[HTML][HTML] Calibration and validation of accelerometer-based activity monitors: A systematic review of machine-learning approaches

V Farrahi, M Niemelä, M Kangas, R Korpelainen… - Gait & posture, 2019 - Elsevier
Background Objective measures using accelerometer-based activity monitors have been
extensively used in physical activity (PA) and sedentary behavior (SB) research. To measure …

[HTML][HTML] Developing and evaluating digital interventions to promote behavior change in health and health care: recommendations resulting from an international …

S Michie, L Yardley, R West, K Patrick… - Journal of medical Internet …, 2017 - jmir.org
Devices and programs using digital technology to foster or support behavior change (digital
interventions) are increasingly ubiquitous, being adopted for use in patient diagnosis and …

Spatial prediction of flood susceptibility using random-forest and boosted-tree models in Seoul metropolitan city, Korea

S Lee, JC Kim, HS Jung, MJ Lee… - … , Natural Hazards and Risk, 2017 - Taylor & Francis
Since flood frequency increases with the impact of climate change, the damage that is
emphasized on flood-risk maps is based on actual flooded area data; therefore, flood …

GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour …

JH Migueles, E Aadland, LB Andersen… - British journal of sports …, 2022 - bjsm.bmj.com
The inter-relationship between physical activity, sedentary behaviour and sleep (collectively
defined as physical behaviours) is of interest to researchers from different fields. Each of …

Identification of immune-associated genes in diagnosing aortic valve calcification with metabolic syndrome by integrated bioinformatics analysis and machine learning

Y Zhou, W Shi, D Zhao, S Xiao, K Wang… - Frontiers in …, 2022 - frontiersin.org
Background Immune system dysregulation plays a critical role in aortic valve calcification
(AVC) and metabolic syndrome (MS) pathogenesis. The study aimed to identify pivotal …

[HTML][HTML] An ensemble learning framework for anomaly detection in building energy consumption

DB Araya, K Grolinger, HF ElYamany, MAM Capretz… - Energy and …, 2017 - Elsevier
During building operation, a significant amount of energy is wasted due to equipment and
human-related faults. To reduce waste, today's smart buildings monitor energy usage with …

Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,220 UK Biobank participants

M Willetts, S Hollowell, L Aslett, C Holmes, A Doherty - Scientific reports, 2018 - nature.com
Current public health guidelines on physical activity and sleep duration are limited by a
reliance on subjective self-reported evidence. Using data from simple wrist-worn activity …

An open-source monitor-independent movement summary for accelerometer data processing

D John, Q Tang, F Albinali… - Journal for the …, 2019 - journals.humankinetics.com
Background: Physical behavior researchers using motion sensors often use acceleration
summaries to visualize, clean, and interpret data. Such output is dependent on device …

Validity of consumer-based physical activity monitors for specific activity types.

MB Nelson, LA Kaminsky, DC Dickin… - Medicine and science …, 2016 - europepmc.org
Purpose Consumer-based physical activity (PA) monitors are popular for individual tracking
of PA variables. However, current research has not examined how these monitors track …