Wheeled mobile robots: state of the art overview and kinematic comparison among three omnidirectional locomotion strategies

L Tagliavini, G Colucci, A Botta, P Cavallone… - Journal of intelligent & …, 2022 - Springer
In the last decades, mobile robotics has become a very interesting research topic in the field
of robotics, mainly because of population ageing and the recent pandemic emergency …

From data acquisition to data fusion: a comprehensive review and a roadmap for the identification of activities of daily living using mobile devices

IM Pires, NM Garcia, N Pombo, F Flórez-Revuelta - Sensors, 2016 - mdpi.com
This paper focuses on the research on the state of the art for sensor fusion techniques,
applied to the sensors embedded in mobile devices, as a means to help identify the mobile …

[HTML][HTML] Glucotypes reveal new patterns of glucose dysregulation

H Hall, D Perelman, A Breschi, P Limcaoco… - PLoS …, 2018 - journals.plos.org
Diabetes is an increasing problem worldwide; almost 30 million people, nearly 10% of the
population, in the United States are diagnosed with diabetes. Another 84 million are …

Modeling two-person segmentation and locomotion for stereoscopic action identification: A sustainable video surveillance system

N Khalid, M Gochoo, A Jalal, K Kim - Sustainability, 2021 - mdpi.com
Due to the constantly increasing demand for automatic tracking and recognition systems,
there is a need for more proficient, intelligent and sustainable human activity tracking. The …

Semi-supervised near-miss fall detection for ironworkers with a wearable inertial measurement unit

K Yang, CR Ahn, MC Vuran, SS Aria - Automation in construction, 2016 - Elsevier
Accidental falls (slips, trips, and falls from height) are the leading cause of occupational
death and injury in construction. As a proactive accident prevention measure, near miss can …

Adaptive sliding window segmentation for physical activity recognition using a single tri-axial accelerometer

MHM Noor, Z Salcic, I Kevin, K Wang - Pervasive and Mobile Computing, 2017 - Elsevier
Previous studies on physical activity recognition have utilized various fixed window sizes for
signal segmentation targeting specific activities. Naturally, an optimum window size varies …

[HTML][HTML] Development of a methodological framework for a robust prediction of the main behaviours of dairy cows using a combination of machine learning algorithms …

L Riaboff, S Poggi, A Madouasse, S Couvreur… - … and Electronics in …, 2020 - Elsevier
Development of a methodological framework for a robust prediction of the main behaviours of
dairy cows using a combination of machine learning algorithms on accelerometer data …

Evaluation of sampling frequency, window size and sensor position for classification of sheep behaviour

E Walton, C Casey, J Mitsch… - Royal Society …, 2018 - royalsocietypublishing.org
Automated behavioural classification and identification through sensors has the potential to
improve health and welfare of the animals. Position of a sensor, sampling frequency and …

A survey on anomalous behavior detection for elderly care using dense-sensing networks

S Deep, X Zheng, C Karmakar, D Yu… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
Facing the gradual ageing society, elderly people living independently are in need of
serious attention. In order to assist them to live in a safer environment, the increasing cost of …

Detecting heat events in dairy cows using accelerometers and unsupervised learning

MS Shahriar, D Smith, A Rahman, M Freeman… - … and electronics in …, 2016 - Elsevier
This study was conducted to investigate the detection of heat events in pasture-based dairy
cows fitted with on-animal sensors using unsupervised learning. Accelerometer data from …