Machine learning in medical applications: A review of state-of-the-art methods

M Shehab, L Abualigah, Q Shambour… - Computers in Biology …, 2022 - Elsevier
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

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 …

Review of wearable devices and data collection considerations for connected health

V Vijayan, JP Connolly, J Condell, N McKelvey… - Sensors, 2021 - mdpi.com
Wearable sensor technology has gradually extended its usability into a wide range of well-
known applications. Wearable sensors can typically assess and quantify the wearer's …

A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions

SK Yadav, K Tiwari, HM Pandey, SA Akbar - Knowledge-Based Systems, 2021 - Elsevier
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …

A survey on wearable sensor modality centred human activity recognition in health care

Y Wang, S Cang, H Yu - Expert Systems with Applications, 2019 - Elsevier
Increased life expectancy coupled with declining birth rates is leading to an aging
population structure. Aging-caused changes, such as physical or cognitive decline, could …

Automated cognitive health assessment in smart homes using machine learning

AR Javed, LG Fahad, AA Farhan, S Abbas… - Sustainable Cities and …, 2021 - Elsevier
Abstract The Internet of Things (IoT) provides smart solutions for future urban communities to
address key benefits with the least human intercession. A smart home offers the necessary …

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 …

Context-aware computing, learning, and big data in internet of things: a survey

OB Sezer, E Dogdu… - IEEE Internet of Things …, 2017 - ieeexplore.ieee.org
Internet of Things (IoT) has been growing rapidly due to recent advancements in
communications and sensor technologies. Meanwhile, with this revolutionary transformation …

Daily activity feature selection in smart homes based on pearson correlation coefficient

Y Liu, Y Mu, K Chen, Y Li, J Guo - Neural processing letters, 2020 - Springer
In the case of a smart home, the ability to recognize daily activities depends primarily on the
strategy used for selecting the appropriate features related to these activities. To achieve 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 …