Remote photonic detection of human senses using secondary speckle patterns
Zeev Kalyuzhner, Sergey Agdarov, Itai Orr, Yafim Beiderman, Aviya Bennett, Zeev Zalevsky
Abstract
Neural activity research has recently gained significant attention due to its association with sensory information and behavior control. However, the current methods of brain activity sensing require expensive equipment and physical contact with the tested subject. We propose a novel photonic-based method for remote detection of human senses. Physiological processes associated with hemodynamic activity due to activation of the cerebral cortex affected by different senses have been detected by remote monitoring of nano-vibrations generated by the transient blood flow to the specific regions of the human brain. We have found that a combination of defocused, self-interference random speckle patterns with a spatiotemporal analysis, using Deep Neural Network, allows associating between the activated sense and the seemingly random speckle patterns.