ReviewSensors (Basel, Switzerland)2023
Dynamic Gesture Recognition Based on FMCW Millimeter Wave Radar: Review of Methodologies and Results.
Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Upper Limb Tremors Classification for Parkinson's Disease Using W-Band (76-81 GHz) Doppler Millimeter-Wave Sensing and Deep-Learning-Based Classifier.Sensors (Basel, Switzerland) · 2026Article
- CBAM-Enhanced CNN-LSTM with Improved DBSCAN for High-Precision Radar-Based Gesture Recognition.Sensors (Basel, Switzerland) · 2026Article
- Neuromorphic-inspired multi-view global-local fusion for IR-UWB radar dynamic gesture recognition.Frontiers in neuroscience · 2026Article
- Micro Gesture Recognition with Multi-Dimensional Feature Fusion and CQ-MobileNetV3 Using FMCW Radar.Sensors (Basel, Switzerland) · 2025Article
- MCT-CNN-LSTM: A Driver Behavior Wireless Perception Method Based on an Improved Multi-Scale Domain-Adversarial Neural Network.Sensors (Basel, Switzerland) · 2025Article
- Hand Gesture Recognition on Edge Devices: Sensor Technologies, Algorithms, and Processing Hardware.Sensors (Basel, Switzerland) · 2025Review
- TRANS-CNN-Based Gesture Recognition for mmWave Radar.Sensors (Basel, Switzerland) · 2024Article
- Human Movement Recognition Based on 3D Point Cloud Spatiotemporal Information from Millimeter-Wave Radar.Sensors (Basel, Switzerland) · 2023Article
- Robust Hand Gesture Recognition Using a Deformable Dual-Stream Fusion Network Based on CNN-TCN for FMCW Radar.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
As a convenient and natural way of human-computer interaction, gesture recognition technology has broad research and application prospects in many fields, such as intelligent perception and virtual reality. This paper summarized the relevant literature on gesture recognition using Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar from January 2015 to June 2023. In the manuscript, the widely used methods involved in data acquisition, data processing, and classification in gesture recognition were systematically investigated. This paper counts the information related to FMCW millimeter wave radar, gestures, data sets, and the methods and results in feature extraction and classification. Based on the statistical data, we provided analysis and recommendations for other researchers. Key issues in the studies of current gesture recognition, including feature fusion, classification algorithms, and generalization, were summarized and discussed. Finally, this paper discussed the incapability of the current gesture recognition technologies in complex practical scenes and their real-time performance for future development.
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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.