ArticleSensors (Basel, Switzerland)2021
Identification of Human Motion Using Radar Sensor in an Indoor Environment.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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.
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Who cites it
6 citing papers in PubMed.
- Entropy-Based Human Activity Measure Using FMCW Radar.Entropy (Basel, Switzerland) · 2025Article
- Respiratory Rate Sensing for a Non-Stationary Human Assisted by Motion Detection.Sensors (Basel, Switzerland) · 2025Article
- Method for Improving Range Resolution of Indoor FMCW Radar Systems Using DNN.Sensors (Basel, Switzerland) · 2022Article
- Applying Deep Learning-Based Human Motion Recognition System in Sports Competition.Frontiers in neurorobotics · 2022Article
- Comprehensive mPoint: A Method for 3D Point Cloud Generation of Human Bodies Utilizing FMCW MIMO mm-Wave Radar.Sensors (Basel, Switzerland) · 2021Article
- Ultra-Wideband Radar-Based Indoor Activity Monitoring for Elderly Care.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
In this paper, we propose a method of identifying human motions, such as standing, walking, running, and crawling, using a millimeter wave radar sensor. In our method, two signal processing is performed in parallel to identify the human motions. First, the moment at which a person's motion changes is determined based on the statistical characteristics of the radar signal. Second, a deep learning-based classification algorithm is applied to determine what actions a person is taking. In each of the two signal processing, radar spectrograms containing the characteristics of the distance change over time are used as input. Finally, we evaluate the performance of the proposed method with radar sensor data acquired in an indoor environment. The proposed method can find the moment when the motion changes with an error rate of 3%, and also can classify the action that a person is taking with more than 95% accuracy.
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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.