Feature selection for unsupervised machine learning of accelerometer data physical activity clusters – A systematic review

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Segmenting accelerometer data from daily life with unsupervised machine learning

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Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: systematic review and harmonised meta-analysis

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Towards a Portable Model to Discriminate Activity Clusters from Accelerometer Data

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A wavelet tensor fuzzy clustering scheme for multi-sensor human activity recognition

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Cognitive behavioural therapy with optional graded exercise therapy in patients with severe fatigue with myotonic dystrophy type 1: a multicentre, single-blind, randomised trial

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Wrist accelerometer shape feature derivation methods for assessing activities of daily living

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Towards unsupervised physical activity recognition using smartphone accelerometers

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Human activity data discovery from triaxial accelerometer sensor: Non-supervised learning sensitivity to feature extraction parametrization

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Unsupervised learning for human activity recognition using smartphone sensors

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Designing a Robust Activity Recognition Framework for Health and Exergaming Using Wearable Sensors

(2013) Nabil Alshurafa et al.   IEEE Journal of Biomedical and Health Informatics

A few useful things to know about machine learning

(2012) Pedro Domingos   COMMUNICATIONS OF THE ACM

Longitudinal Associations Between Changes in Physical Activity and Onset of Type 2 Diabetes in Older British Men: The influence of adiposity

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