Abstract
In this paper, a method to detect frames was described that can be used as hand gesture data when configuring a real-time hand gesture recognition system using continuous wave (CW) radar. Detecting valid frames raises accuracy which recognizes gestures. Therefore, it is essential to detect valid frames in the real-time hand gesture recognition system using CW radar. The conventional research on hand gesture recognition systems has not been conducted on detecting valid frames. We took the R-wave on electrocardiogram (ECG) detection as the conventional method. The detection probability of the conventional method was 85.04%. It has a low accuracy to use the hand gesture recognition system. The proposal consists of 2-stages to improve accuracy. We measured the performance of the detection method of hand gestures provided by the detection probability and the recognition probability. By comparing the performance of each detection method, we proposed an optimal detection method. The proposal detects valid frames with an accuracy of 96.88%, 11.84% higher than the accuracy of the conventional method. Also, the recognition probability of the proposal method was 94.21%, which was 3.71% lower than the ideal method.
Highlights
HUMAN-computer interaction (HCI) recognizes the purpose of humans and operates a device.Hand gesture recognition is a type of HCI that gets the hand gestures of humans sorted and steers the device for each gesture
The hand gesture recognition system using frequency modulated continuous wave (FMCW) radar can get a high accuracy when exponentially weighted moving average (EWMA) is applied as a detection method
The software part trigger signal comes in, the short term Fourier transform (STFT) module receives a valid frame from the DPRAM; this frame is output analyzes and recognizes motion using the spectrogram transmitted by the digital signal processing to spectrogram by STFT
Summary
HUMAN-computer interaction (HCI) recognizes the purpose of humans and operates a device. Radar sensors are less sensitive to recognition environments and privacy violations and are being actively studied for hand gesture recognition [10,11,12,13,14,15]. It is impossible to use the above detection methods for a real-time hand gesture recognition system using CW radar. Real-time hand gesture recognition using FMCW radar employs an exponentially weighted moving average (EWMA), which is one of the CFAR algorithms used to detect valid frames [19]. The hand gesture recognition system using FMCW radar can get a high accuracy when EWMA is applied as a detection method. Methods were provided to detect frames that can be used in real-time hand gesture recognition using.
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