Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities
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 …
sensor-based activity recognition. However, there exist substantial challenges that could …
[HTML][HTML] Trends in human activity recognition with focus on machine learning and power requirements
The advancement and availability of technology can be employed to improve our daily lives.
One example is Human Activity Recognition (HAR). HAR research has been mainly …
One example is Human Activity Recognition (HAR). HAR research has been mainly …
Temporal-channel convolution with self-attention network for human activity recognition using wearable sensors
E Essa, IR Abdelmaksoud - Knowledge-Based Systems, 2023 - Elsevier
Human activity recognition (HAR) is an essential task in many applications such as health
monitoring, rehabilitation, and sports training. Sensor-based HAR has received increasing …
monitoring, rehabilitation, and sports training. Sensor-based HAR has received increasing …
Deep ConvLSTM with self-attention for human activity decoding using wearable sensors
Decoding human activity accurately from wearable sensors can aid in applications related to
healthcare and context awareness. The present approaches in this domain use recurrent …
healthcare and context awareness. The present approaches in this domain use recurrent …
Deep neural networks for human activity recognition with wearable sensors: Leave-one-subject-out cross-validation for model selection
Human Activity Recognition (HAR) has been attracting significant research attention
because of the increasing availability of environmental and wearable sensors for collecting …
because of the increasing availability of environmental and wearable sensors for collecting …
Attention-based convolutional neural network for weakly labeled human activities' recognition with wearable sensors
Traditional methods of human activity recognition usually require a large amount of strictly
labeled data for training classifiers. However, it is hard for one to keep a fixed activity when …
labeled data for training classifiers. However, it is hard for one to keep a fixed activity when …
[HTML][HTML] Stochastic recognition of physical activity and healthcare using tri-axial inertial wearable sensors
Featured Application The proposed technique is an application of physical activity detection,
analyzing three challenging benchmark datasets. It can be applied in sports assistance …
analyzing three challenging benchmark datasets. It can be applied in sports assistance …
MultiCNN-FilterLSTM: Resource-efficient sensor-based human activity recognition in IoT applications
With the recent advances in the Internet of Things (IoT) technologies, various human-
centered applications have proliferated and improved the quality of users' life. In the …
centered applications have proliferated and improved the quality of users' life. In the …
IF-ConvTransformer: A framework for human activity recognition using IMU fusion and ConvTransformer
Y Zhang, L Wang, H Chen, A Tian, S Zhou… - Proceedings of the ACM …, 2022 - dl.acm.org
Recent advances in sensor based human activity recognition (HAR) have exploited deep
hybrid networks to improve the performance. These hybrid models combine Convolutional …
hybrid networks to improve the performance. These hybrid models combine Convolutional …
Towards energy efficiency in the internet of wearable things: A systematic review
WB Qaim, A Ometov, A Molinaro, I Lener… - IEEE …, 2020 - ieeexplore.ieee.org
Personal mobile devices such as smartwatches, smart jewelry, and smart clothes have
launched a new trend in the Internet of Things (IoT) era, namely the Internet of Wearable …
launched a new trend in the Internet of Things (IoT) era, namely the Internet of Wearable …