Deep learning in human activity recognition with wearable sensors: A review on advances

S Zhang, Y Li, S Zhang, F Shahabi, S Xia, Y Deng… - Sensors, 2022 - mdpi.com
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

Sensor-based and vision-based human activity recognition: A comprehensive survey

LM Dang, K Min, H Wang, MJ Piran, CH Lee, H Moon - Pattern Recognition, 2020 - Elsevier
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …

Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges

HF Nweke, YW Teh, MA Al-Garadi, UR Alo - Expert Systems with …, 2018 - Elsevier
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …

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 …

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 …

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 …

Power consumption analysis, measurement, management, and issues: A state-of-the-art review of smartphone battery and energy usage

PKD Pramanik, N Sinhababu, B Mukherjee… - ieee …, 2019 - ieeexplore.ieee.org
The advancement and popularity of smartphones have made it an essential and all-purpose
device. But lack of advancement in battery technology has held back its optimum potential …

Feature learning for human activity recognition using convolutional neural networks: A case study for inertial measurement unit and audio data

F Cruciani, A Vafeiadis, C Nugent, I Cleland… - CCF Transactions on …, 2020 - Springer
Abstract The use of Convolutional Neural Networks (CNNs) as a feature learning method for
Human Activity Recognition (HAR) is becoming more and more common. Unlike …

Generalization and personalization of mobile sensing-based mood inference models: an analysis of college students in eight countries

L Meegahapola, W Droz, P Kun, A De Götzen… - Proceedings of the …, 2023 - dl.acm.org
Mood inference with mobile sensing data has been studied in ubicomp literature over the
last decade. This inference enables context-aware and personalized user experiences in …

Development of a real-time wearable fall detection system in the context of Internet of Things

Z Qian, Y Lin, W Jing, Z Ma, H Liu, R Yin… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Fall detection is of increasing significance in terms of the health monitoring of the elderly and
disabled people, as falls may lead to physical injuries or even mental trauma. The existing …