Sensor-based and vision-based human activity recognition: A comprehensive survey
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …
of sensing devices, including vision sensors and embedded sensors, has motivated the …
A systematic review of smartphone-based human activity recognition methods for health research
Smartphones are now nearly ubiquitous; their numerous built-in sensors enable continuous
measurement of activities of daily living, making them especially well-suited for health …
measurement of activities of daily living, making them especially well-suited for health …
Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects
Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …
people because of its ability to learn extensive high-level information about human activity …
FL-PMI: federated learning-based person movement identification through wearable devices in smart healthcare systems
Recent technological developments, such as the Internet of Things (IoT), artificial
intelligence, edge, and cloud computing, have paved the way in transforming traditional …
intelligence, edge, and cloud computing, have paved the way in transforming traditional …
Unimib shar: A dataset for human activity recognition using acceleration data from smartphones
Smartphones, smartwatches, fitness trackers, and ad-hoc wearable devices are being
increasingly used to monitor human activities. Data acquired by the hosted sensors are …
increasingly used to monitor human activities. Data acquired by the hosted sensors are …
Collossl: Collaborative self-supervised learning for human activity recognition
A major bottleneck in training robust Human-Activity Recognition models (HAR) is the need
for large-scale labeled sensor datasets. Because labeling large amounts of sensor data is …
for large-scale labeled sensor datasets. Because labeling large amounts of sensor data is …
A federated learning aggregation algorithm for pervasive computing: Evaluation and comparison
Pervasive computing promotes the installation of connected devices in our living spaces in
order to provide services. Two major developments have gained significant momentum …
order to provide services. Two major developments have gained significant momentum …
Imutube: Automatic extraction of virtual on-body accelerometry from video for human activity recognition
The lack of large-scale, labeled data sets impedes progress in developing robust and
generalized predictive models for on-body sensor-based human activity recognition (HAR) …
generalized predictive models for on-body sensor-based human activity recognition (HAR) …
Sensing with earables: A systematic literature review and taxonomy of phenomena
T Röddiger, C Clarke, P Breitling… - Proceedings of the …, 2022 - dl.acm.org
Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-
worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new …
worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new …
Trends in human activity recognition using smartphones
Recognizing human activities and monitoring population behavior are fundamental needs of
our society. Population security, crowd surveillance, healthcare support and living …
our society. Population security, crowd surveillance, healthcare support and living …