Advanced internet of things for personalised healthcare systems: A survey

J Qi, P Yang, G Min, O Amft, F Dong, L Xu - Pervasive and mobile …, 2017 - Elsevier
As a new revolution of the Internet, Internet of Things (IoT) is rapidly gaining ground as a
new research topic in many academic and industrial disciplines, especially in healthcare …

Measurement of physical activity in clinical practice using accelerometers

D Arvidsson, J Fridolfsson… - Journal of internal …, 2019 - Wiley Online Library
Accelerometers are commonly used in clinical and epidemiological research for more
detailed measures of physical activity and to target the limitations of self‐report methods …

Sensor-based datasets for human activity recognition–a systematic review of literature

E De-La-Hoz-Franco, P Ariza-Colpas, JM Quero… - IEEE …, 2018 - ieeexplore.ieee.org
The research area of ambient assisted living has led to the development of activity
recognition systems (ARS) based on human activity recognition (HAR). These systems …

Wearable sensors based human behavioral pattern recognition using statistical features and reweighted genetic algorithm

MAK Quaid, A Jalal - Multimedia Tools and Applications, 2020 - Springer
Human behavior pattern recognition (BPR) from accelerometer signals is a challenging
problem due to variations in signal durations of different behaviors. Analysis of human …

[HTML][HTML] Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review

J Qi, P Yang, A Waraich, Z Deng, Y Zhao… - Journal of biomedical …, 2018 - Elsevier
Due to importantly beneficial effects on physical and mental health and strong association
with many rehabilitation programs, Physical Activity Recognition and Monitoring (PARM) …

State of the science and recommendations for using wearable technology in sleep and circadian research

M de Zambotti, C Goldstein, J Cook, L Menghini… - Sleep, 2024 - academic.oup.com
Wearable sleep-tracking technology is of growing use in the sleep and circadian fields,
including for applications across other disciplines, inclusive of a variety of disease states …

An overview of data fusion techniques for Internet of Things enabled physical activity recognition and measure

J Qi, P Yang, L Newcombe, X Peng, Y Yang, Z Zhao - Information Fusion, 2020 - Elsevier
Due to importantly beneficial effects on physical and mental health and strong association
with many rehabilitation programs, Physical Activity Recognition and Measure (PARM) has …

[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] Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms

J Chong, P Tjurin, M Niemelä, T Jämsä, V Farrahi - Gait & posture, 2021 - Elsevier
Purpose Machine-learning (ML) approaches have been repeatedly coupled with raw
accelerometry to classify physical activity classes, but the features required to optimize their …

Kinect and wearable inertial sensors for motor rehabilitation programs at home: State of the art and an experimental comparison

B Milosevic, A Leardini, E Farella - Biomedical engineering online, 2020 - Springer
Background Emerging sensing and communication technologies are contributing to the
development of many motor rehabilitation programs outside the standard healthcare …