Pulsed Millimeter Wave Radar for Hand Gesture Sensing and Classification
(2019) In IEEE Sensors Letters 3(12).- Abstract
A pulsed millimeter wave radar operating at a frame rate of 144 Hz is utilized to record 2160 scattering signatures of 12 generic hand gestures. Gesture recognition is achieved by machine learning, utilizing transfer learning on a pretrained convolutional neural network. This yields excellent classification results with a validation accuracy of 99.5%, based on a 60% training versus 40% validation split. The corresponding confusion matrix is also presented, showing a high level of classification orthogonality between the tested gestures. This is the first demonstration where data from a pulsed millimeter wave radar is used for gesture recognition by machine learning. It proves that the range-time envelope representation of high... (More)
A pulsed millimeter wave radar operating at a frame rate of 144 Hz is utilized to record 2160 scattering signatures of 12 generic hand gestures. Gesture recognition is achieved by machine learning, utilizing transfer learning on a pretrained convolutional neural network. This yields excellent classification results with a validation accuracy of 99.5%, based on a 60% training versus 40% validation split. The corresponding confusion matrix is also presented, showing a high level of classification orthogonality between the tested gestures. This is the first demonstration where data from a pulsed millimeter wave radar is used for gesture recognition by machine learning. It proves that the range-time envelope representation of high frame-rate data from a pulsed radar is suitable for hand gesture recognition. Further improvements are expected for more complex detection schemes and tailored neural networks.
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- author
- Fhager, Lars Ohlsson LU ; Heunisch, Sebastian LU ; Dahlberg, Hannes ; Evertsson, Anton and Wernersson, Lars Erik LU
- organization
- publishing date
- 2019-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- classification, convolutional neural network, gesture sensing, hand gesture recognition, machine learning, Microwave/millimeter wave sensors, millimeter wave radar, pulsed radar, transfer learning
- in
- IEEE Sensors Letters
- volume
- 3
- issue
- 12
- article number
- 3502404
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85082634141
- ISSN
- 2475-1472
- DOI
- 10.1109/LSENS.2019.2953022
- language
- English
- LU publication?
- yes
- id
- 1c34f121-df71-43a7-b39c-5caf5090917c
- date added to LUP
- 2020-04-28 16:20:32
- date last changed
- 2022-04-18 22:01:34
@article{1c34f121-df71-43a7-b39c-5caf5090917c, abstract = {{<p>A pulsed millimeter wave radar operating at a frame rate of 144 Hz is utilized to record 2160 scattering signatures of 12 generic hand gestures. Gesture recognition is achieved by machine learning, utilizing transfer learning on a pretrained convolutional neural network. This yields excellent classification results with a validation accuracy of 99.5%, based on a 60% training versus 40% validation split. The corresponding confusion matrix is also presented, showing a high level of classification orthogonality between the tested gestures. This is the first demonstration where data from a pulsed millimeter wave radar is used for gesture recognition by machine learning. It proves that the range-time envelope representation of high frame-rate data from a pulsed radar is suitable for hand gesture recognition. Further improvements are expected for more complex detection schemes and tailored neural networks.</p>}}, author = {{Fhager, Lars Ohlsson and Heunisch, Sebastian and Dahlberg, Hannes and Evertsson, Anton and Wernersson, Lars Erik}}, issn = {{2475-1472}}, keywords = {{classification; convolutional neural network; gesture sensing; hand gesture recognition; machine learning; Microwave/millimeter wave sensors; millimeter wave radar; pulsed radar; transfer learning}}, language = {{eng}}, number = {{12}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Sensors Letters}}, title = {{Pulsed Millimeter Wave Radar for Hand Gesture Sensing and Classification}}, url = {{http://dx.doi.org/10.1109/LSENS.2019.2953022}}, doi = {{10.1109/LSENS.2019.2953022}}, volume = {{3}}, year = {{2019}}, }