Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities

K Chen, D Zhang, L Yao, B Guo, Z Yu… - ACM Computing Surveys …, 2021 - dl.acm.org
The vast proliferation of sensor devices and Internet of Things enables the applications of
sensor-based activity recognition. However, there exist substantial challenges that could …

Smart watches: A review of evolution in bio-medical sector

RS Chandel, S Sharma, S Kaur, S Singh… - Materials Today …, 2022 - Elsevier
Smartwatch (SW) is a wearable gadget used in everyday life. It is equivalent to a customary
wristwatch and offers features similar to a smartphone. These features include access to the …

A scalable and transferable federated learning system for classifying healthcare sensor data

L Sun, J Wu - IEEE Journal of Biomedical and Health …, 2022 - ieeexplore.ieee.org
With the development of Internet of Medical Things, massive healthcare sensor data (HSD)
are transmitted in the Internet, which faces various security problems. Healthcare data are …

Multi-sensor human activity recognition using CNN and GRU

O Nafea, W Abdul, G Muhammad - International Journal of Multimedia …, 2022 - Springer
In the current era of rapid technological innovation, human activity recognition (HAR) has
emerged as a principal research area in the field of multimedia information retrieval. The …

Cnns for heart rate estimation and human activity recognition in wrist worn sensing applications

E Brophy, W Muehlhausen… - 2020 IEEE …, 2020 - ieeexplore.ieee.org
Wrist-worn smart devices are providing increased insights into human health, behaviour and
performance through sophisticated analytics. However, battery life, device cost and sensor …

Detecting deepfake videos using euler video magnification

R Das, G Negi, AF Smeaton - arXiv preprint arXiv:2101.11563, 2021 - arxiv.org
Recent advances in artificial intelligence make it progressively hard to distinguish between
genuine and counterfeit media, especially images and videos. One recent development is …

High accuracy human activity recognition using machine learning and wearable devices' raw signals

A Papaleonidas, AP Psathas… - Journal of Information and …, 2022 - Taylor & Francis
Human activity recognition (HAR) is vital in a wide range of real-life applications such as
health monitoring of olderly people, abnormal behaviour detection and smart home …

Optimised convolutional neural networks for heart rate estimation and human activity recognition in wrist worn sensing applications

E Brophy, W Muehlhausen, AF Smeaton… - arXiv preprint arXiv …, 2020 - arxiv.org
Wrist-worn smart devices are providing increased insights into human health, behaviour and
performance through sophisticated analytics. However, battery life, device cost and sensor …

Machine learning modeling of human activity using PPG signals

AP Psathas, A Papaleonidas, L Iliadis - International Conference on …, 2020 - Springer
The use of wearables is contributing towards the decrease of risk for chronic diseases
related to cardiovascular or diabetes problems. Most wearables measure heart rate and the …

Hierarchical deep learning model with inertial and physiological sensors fusion for wearable-based human activity recognition

DY Hwang, PC Ng, Y Yu, Y Wang… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
This paper presents a human activity recognition (HAR) system with wearable devices.
While various approaches have been suggested for HAR, most of them focus on either 1) …