Human activity recognition using inertial, physiological and environmental sensors: A comprehensive survey

F Demrozi, G Pravadelli, A Bihorac, P Rashidi - IEEE access, 2020 - ieeexplore.ieee.org
In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …

Recent advances in wearable optical sensor automation powered by battery versus skin-like battery-free devices for personal healthcare—A review

NL Kazanskiy, MA Butt, SN Khonina - Nanomaterials, 2022 - mdpi.com
Currently, old-style personal Medicare techniques rely mostly on traditional methods, such
as cumbersome tools and complicated processes, which can be time consuming and …

Human activity recognition using marine predators algorithm with deep learning

AM Helmi, MAA Al-qaness, A Dahou… - Future Generation …, 2023 - Elsevier
In the era of smart life, tracking human activities and motion can play a significant role in the
advanced modern applications, such as the Internet of things (IoT), Internet of healthcare …

Human daily and sport activity recognition using a wearable inertial sensor network

YL Hsu, SC Yang, HC Chang, HC Lai - IEEE Access, 2018 - ieeexplore.ieee.org
This paper presents a wearable inertial sensor network and its associated activity
recognition algorithm for accurately recognizing human daily and sport activities. The …

[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 …

Machine learning-based identification and classification of physical fatigue levels: A novel method based on a wearable insole device

MF Antwi-Afari, S Anwer, W Umer, HY Mi, Y Yu… - International Journal of …, 2023 - Elsevier
Construction is known for being a labor-intensive and risky industry. Within various
occupational settings such as construction, physical fatigue is an underlying health condition …

Revolution in flexible wearable electronics for temperature and pressure monitoring—A review

MA Butt, NL Kazanskiy, SN Khonina - Electronics, 2022 - mdpi.com
In the last few decades, technology innovation has had a huge influence on our lives and
well-being. Various factors of observing our physiological characteristics are taken into …

Sustainable wearable system: Human behavior modeling for life-logging activities using K-Ary tree hashing classifier

A Jalal, M Batool, K Kim - Sustainability, 2020 - mdpi.com
Human behavior modeling (HBM) is a challenging classification task for researchers
seeking to develop sustainable systems that precisely monitor and record human life-logs. In …

Accelerometer-based human activity recognition for patient monitoring using a deep neural network

E Fridriksdottir, AG Bonomi - Sensors, 2020 - mdpi.com
The objective of this study was to investigate the accuracy of a Deep Neural Network (DNN)
in recognizing activities typical for hospitalized patients. A data collection study was …

Application of raw accelerometer data and machine-learning techniques to characterize human movement behavior: a systematic scoping review

A Narayanan, F Desai, T Stewart… - … of Physical Activity …, 2020 - journals.humankinetics.com
Background: Application of machine learning for classifying human behavior is increasingly
common as access to raw accelerometer data improves. The aims of this scoping review are …