ArticleSensors (Basel, Switzerland)2022
Skeleton Graph-Neural-Network-Based Human Action Recognition: A Survey.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Confidence-Aware Gated Multimodal Fusion for Robust Temporal Action Localization in Occluded Environments.Sensors (Basel, Switzerland) · 2026Article
- AviaTAD-LGH: A Multi-Task Spatio-Temporal Action Detector with Lightweight Gradient Harmonization for Real-Time Avian Behavior Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Clustered Federated Spatio-Temporal Graph Attention Networks for Skeleton-Based Action Recognition.Sensors (Basel, Switzerland) · 2025Article
- A Comprehensive Methodological Survey of Human Activity Recognition Across Diverse Data Modalities.Sensors (Basel, Switzerland) · 2025Review
- A Structured and Methodological Review on Multi-View Human Activity Recognition for Ambient Assisted Living.Journal of imaging · 2025Article
- A novel approach for joint indoor localization and activity recognition using a hybrid CNN-GRU and MRF framework.PloS one · 2025Article
- Mapping Method of Human Arm Motion Based on Surface Electromyography Signals.Sensors (Basel, Switzerland) · 2024Article
- Action Recognition of Taekwondo Unit Actions Using Action Images Constructed with Time-Warped Motion Profiles.Sensors (Basel, Switzerland) · 2024Article
- Skeleton-Based Human Pose Recognition Using Channel State Information: A Survey.Sensors (Basel, Switzerland) · 2022Review
- A Spatio-Temporal Graph Convolutional Network Model for Internet of Medical Things (IoMT).Sensors (Basel, Switzerland) · 2022Article
- A Survey on Wireless Wearable Body Area Networks: A Perspective of Technology and Economy.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Human action recognition has been applied in many fields, such as video surveillance and human computer interaction, where it helps to improve performance. Numerous reviews of the literature have been done, but rarely have these reviews concentrated on skeleton-graph-based approaches. Connecting the skeleton joints as in the physical appearance can naturally generate a graph. This paper provides an up-to-date review for readers on skeleton graph-neural-network-based human action recognition. After analyzing previous related studies, a new taxonomy for skeleton-GNN-based methods is proposed according to their designs, and their merits and demerits are analyzed. In addition, the datasets and codes are discussed. Finally, future research directions are suggested.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.