A survey on wearable human activity recognition: innovative pipeline development for enhanced research and practice
Recent trends in Wearable Human Activity Recognition (WHAR) have led to an
unprecedented 42.9% increase in scholarly articles in 2022, underscoring the urgency for a …
unprecedented 42.9% increase in scholarly articles in 2022, underscoring the urgency for a …
Depth sensors-based action recognition using a modified K-ary entropy classifier
Surveillance system is acquiring an ample interest in the field of computer vision. Existing
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …
What makes good contrastive learning on small-scale wearable-based tasks?
Self-supervised learning establishes a new paradigm of learning representations with much
fewer or even no label annotations. Recently there has been remarkable progress on large …
fewer or even no label annotations. Recently there has been remarkable progress on large …
Dual-branch interactive networks on multichannel time series for human activity recognition
The popularity of convolutional architecture has made sensor-based human activity
recognition (HAR) become one primary beneficiary. By simply superimposing multiple …
recognition (HAR) become one primary beneficiary. By simply superimposing multiple …
Inertial-measurement-unit-based novel human activity recognition algorithm using conformer
YW Kim, WH Cho, KS Kim, S Lee - Sensors, 2022 - mdpi.com
Inertial-measurement-unit (IMU)-based human activity recognition (HAR) studies have
improved their performance owing to the latest classification model. In this study, the …
improved their performance owing to the latest classification model. In this study, the …
Improvement of Performance in Freezing of Gait detection in Parkinson's Disease using Transformer networks and a single waist-worn triaxial accelerometer
Freezing of gait (FOG) is one of the most incapacitating symptoms in Parkinson's disease,
affecting more than 50% of patients in advanced stages of the disease. The presence of …
affecting more than 50% of patients in advanced stages of the disease. The presence of …
Lightweight transformers for human activity recognition on mobile devices
Human Activity Recognition (HAR) on mobile devices has shown to be achievable with
lightweight neural models learned from data generated by the user's inertial measurement …
lightweight neural models learned from data generated by the user's inertial measurement …
Attention-based residual BiLSTM networks for human activity recognition
J Zhang, Y Liu, H Yuan - IEEE Access, 2023 - ieeexplore.ieee.org
Human activity recognition (HAR) commonly employs wearable sensors to identify and
analyze the time series data collected by them, enabling the recognition of specific actions …
analyze the time series data collected by them, enabling the recognition of specific actions …
Semisupervised Generative Adversarial Networks with Temporal Convolutions for Human Activity Recognition
Many potential applications of human activity recognition (HAR) can be found in health,
surveillance, manufacturing, sports, and so on. For instance, HAR can be exploited in …
surveillance, manufacturing, sports, and so on. For instance, HAR can be exploited in …
A benchmark for domain adaptation and generalization in smartphone-based human activity recognition
O Napoli, D Duarte, P Alves, DHP Soto, HE de Oliveira… - Scientific Data, 2024 - nature.com
Human activity recognition (HAR) using smartphone inertial sensors, like accelerometers
and gyroscopes, enhances smartphones' adaptability and user experience. Data distribution …
and gyroscopes, enhances smartphones' adaptability and user experience. Data distribution …