Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges

S Qiu, H Zhao, N Jiang, Z Wang, L Liu, Y An, H Zhao… - Information …, 2022 - Elsevier
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …

Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions

HF Nweke, YW Teh, G Mujtaba, MA Al-Garadi - Information Fusion, 2019 - Elsevier
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …

Estimating sleep parameters using an accelerometer without sleep diary

VT Van Hees, S Sabia, SE Jones, AR Wood… - Scientific reports, 2018 - nature.com
Wrist worn raw-data accelerometers are used increasingly in large-scale population
research. We examined whether sleep parameters can be estimated from these data in the …

A survey on activity detection and classification using wearable sensors

M Cornacchia, K Ozcan, Y Zheng… - IEEE Sensors …, 2016 - ieeexplore.ieee.org
Activity detection and classification are very important for autonomous monitoring of humans
for applications, including assistive living, rehabilitation, and surveillance. Wearable sensors …

Lifelogging: Personal big data

C Gurrin, AF Smeaton, AR Doherty - Foundations and Trends® …, 2014 - nowpublishers.com
We have recently observed a convergence of technologies to foster the emergence of
lifelogging as a mainstream activity. Computer storage has become significantly cheaper …

Sedentary behaviors in today's youth: approaches to the prevention and management of childhood obesity: a scientific statement from the American Heart Association

TA Barnett, AS Kelly, DR Young, CK Perry, CA Pratt… - Circulation, 2018 - Am Heart Assoc
This scientific statement is about sedentary behavior and its relationship to obesity and other
cardiometabolic outcomes in youth. A deleterious effect of sedentary behavior on …

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 …

[HTML][HTML] Hip and wrist accelerometer algorithms for free-living behavior classification

K Ellis, J Kerr, S Godbole, J Staudenmayer… - Medicine and science …, 2016 - ncbi.nlm.nih.gov
Purpose Accelerometers are a valuable tool for objective measurement of physical activity
(PA). Wrist-worn devices may improve compliance over standard hip placement, but more …

A systematic literature review with meta-analyses of within-and between-day differences in objectively measured physical activity in school-aged children

HL Brooke, K Corder, AJ Atkin, EMF van Sluijs - Sports medicine, 2014 - Springer
Background Targeting specific time periods of the day or week may enhance physical
activity (PA) interventions in youth. The most prudent time segments to target are currently …

Exploring the context of sedentary behaviour in older adults (what, where, why, when and with whom)

CF Leask, JA Harvey, DA Skelton… - European Review of …, 2015 - Springer
Background Older adults are the most sedentary segment of the population. Little
information is available about the context of sedentary behaviour to inform guidelines and …