This paper presents a high-order sensory processing nanocircuit based on coupled VO2 oscillators, aiming to address the limitations of conventional circuit elements in area and power efficiency. The authors demonstrate an experimental hardware demonstration of a capacitance-coupled VO2 phase-change oscillatory network, which serves as a continuous-time dynamic system for sensory pre-processing and encodes information in phase differences. A decision-making module is designed for post-processing through software simulation to complete a bio-inspired dynamic sensory system. The experiments show that this transistor-free coupling network excels in sensory processing tasks such as touch and gesture recognition, achieving significant advantages in terms of fewer devices and lower energy-delay-product compared to conventional methods. The work paves the way for an efficient and compact neuromorphic sensory system based on nano-scale nonlinear dynamics, which is crucial for advanced applications like wearable electronics, autonomous driving, and virtual reality. The system's ability to interact with the environment and process spatiotemporal patterns efficiently makes it a promising candidate for future sensory systems.This paper presents a high-order sensory processing nanocircuit based on coupled VO2 oscillators, aiming to address the limitations of conventional circuit elements in area and power efficiency. The authors demonstrate an experimental hardware demonstration of a capacitance-coupled VO2 phase-change oscillatory network, which serves as a continuous-time dynamic system for sensory pre-processing and encodes information in phase differences. A decision-making module is designed for post-processing through software simulation to complete a bio-inspired dynamic sensory system. The experiments show that this transistor-free coupling network excels in sensory processing tasks such as touch and gesture recognition, achieving significant advantages in terms of fewer devices and lower energy-delay-product compared to conventional methods. The work paves the way for an efficient and compact neuromorphic sensory system based on nano-scale nonlinear dynamics, which is crucial for advanced applications like wearable electronics, autonomous driving, and virtual reality. The system's ability to interact with the environment and process spatiotemporal patterns efficiently makes it a promising candidate for future sensory systems.