“…[3,[13][14][15] As a primary mode to understand and mimic humanhuman interaction since the beginning of human cognition, hand gesture recognition (HGR) has been the holy grail of HRI because of its efficient communication in rugged environments that are difficult with verbal or facial expressions (e.g., construction sites and emergency rescues). [3,[16][17][18][19][20][21][22][23] Conventional methods for HGR typically rely on the use of visual or infrared cameras [24] electromyography (EMG) measurements, [24,25] or stretchable strain sensors [26] with resources-intensive machine learning algorithms to decipher the gestures. However, the accuracy of HGR has been hindered because of the limited visual image quality due to environmental interference, poor contact impedance, and lowquality data due to cross-talks in EMG and strain sensors.…”