# Hand Gesture Recognition on Edge Devices:
## 4 Sensor Technologies
### Radar  
Extensive research has been done on radar-based hand gesture recognition. The survey [10] gives a summary of radar-based HGR systems. In radar, the send pattern can either be a single frequency or a chirp. In case of the chirp, the sent frequency is linearly increased among a given frequency band. After all frequencies have been sent, the chirp restarts with the lowest frequency. Both frequency types can either be sent continuously or as a pulse. That means the actuation of radar can either consist of a continuously sent single frequency, a pulse repeated at a given period, a pulse of a chirp, or a continuously repeated chirp for continuous wave radar. The technologies are called single-frequency continuous-wave radar (SFCW) or frequency-modulated continuous-wave radar (FMCW) for continuous actuation, and ultra-wideband radar (UWB) and Doppler-radar in case a short pulse of either one or several frequencies is sent. Figure 4 depicts an actuation with a single frequency of continuous wave, middle, or pulsed in the bottom plot. Figure 5 shows FMCW and pulsed chirp actuation. In case of UWB, a very short pulse--theoretically a dirac--is sent. A possible practical way to send such a pulse is to send a wave with a very low frequency for a very short time period. In this way, a burst consisting of many different frequencies is sent. It is depicted in Figure 6.  
Radars that use frequencies in the spectrum from 30 GHz to 300 GHz are called mmWave radar, as their wavelength is between 1 and 10 mm. mmWave radar can refer to pulsed or continuous wave actuation. A frequency of 60 GHz radar is commonly used for short-range applications like IoT devices and therefore HGR. The survey [10] describes FMCW, SFCW, and UWB technologies and how they are used for HGR. It gives an overview about radar-based HGR until 2021. However, especially on the algorithm side the field is rapidly developing. Radar pre-processing is traditionally based on the Fourier transform. A common way of depicting radar data is stacking actuation pulses. Applying the Fourier transform on one or both of the axes of the resulting array creates intensity maps that can be fed into ML systems for gesture classification. Possible pre-processing/map generation algorithms are explained in depth in Sections 5.3 and 5.5. Movements in a radial direction cause changes in the frequency according to the Doppler effect, an increased frequency when moving towards the radar and a decreased frequencythe radar. If this effect is mainly used, it is also called doppler radar. Radar is the only technology introduced here that can achieve similarly low power usage as ultrasound when the system is optimized for this goal. As it is an extensively researched technology, successful attempts with the goal of low power have already been reported, as for example in [20]. In radar HGR, oftentimes several sending and receiving antennas are used simultaneously. This technology is called multiple-input multiple-output (MIMO). A more in-detail description of this algorithm is given in Section 5.2.  
Figure 4: Actuation with a single frequency.  
Figure 5: Actuation with a chirp.  
The following subsections give more in-depth descriptions of common pre-processing approaches for HGR with radar, cell network, WiFi, and ultrasound waves.