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 …

Research of fall detection and fall prevention technologies: A systematic review

L Ren, Y Peng - IEEE Access, 2019 - ieeexplore.ieee.org
Falls are abnormal activity events that occur infrequently; however, they are serious health
problems among elderly individuals. With the advancements of technologies, falls have …

Adaptive extreme edge computing for wearable devices

E Covi, E Donati, X Liang, D Kappel… - Frontiers in …, 2021 - frontiersin.org
Wearable devices are a fast-growing technology with impact on personal healthcare for both
society and economy. Due to the widespread of sensors in pervasive and distributed …

A survey on recent advances in wearable fall detection systems

A Ramachandran, A Karuppiah - BioMed research international, 2020 - Wiley Online Library
With advances in medicine and healthcare systems, the average life expectancy of human
beings has increased to more than 80 yrs. As a result, the demographic old‐age …

Latest research trends in gait analysis using wearable sensors and machine learning: A systematic review

A Saboor, T Kask, A Kuusik, MM Alam… - Ieee …, 2020 - ieeexplore.ieee.org
Gait is the locomotion attained through the movement of limbs and gait analysis examines
the patterns (normal/abnormal) depending on the gait cycle. It contributes to the …

Enabling AI in future wireless networks: A data life cycle perspective

DC Nguyen, P Cheng, M Ding… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT)
networks, which can be mostly attributed to the increasing communication and sensing …

Smart fusion of sensor data and human feedback for personalized energy-saving recommendations

I Varlamis, C Sardianos, C Chronis, G Dimitrakopoulos… - Applied Energy, 2022 - Elsevier
Despite the variety of sensors that can be used in a smart home or office setup, for
monitoring energy consumption and assisting users to save energy, their usefulness is …

Vision and inertial sensing fusion for human action recognition: A review

S Majumder, N Kehtarnavaz - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Human action recognition is used in many applications such as video surveillance, human-
computer interaction, assistive living, and gaming. Many papers have appeared in the …

NT-FDS—A noise tolerant fall detection system using deep learning on wearable devices

M Waheed, H Afzal, K Mehmood - Sensors, 2021 - mdpi.com
Given the high prevalence and detrimental effects of unintentional falls in the elderly, fall
detection has become a pertinent public concern. A Fall Detection System (FDS) gathers …

Sensing within smart buildings: A survey

W Alsafery, O Rana, C Perera - ACM Computing Surveys, 2023 - dl.acm.org
Increasingly, buildings are being fitted with sensors for the needs of different sectors, such
as education, industry and business. Using Internet of Things devices combined with …