Improved Morse Code Recognition and Real-Time Translation System Based on a Low-Cost, Tailorable Flexible Capacitive Sensor

The increasing demand for flexible wearable electronic devices has prompted the rapid development of pressure sensors capable of monitoring a range of human movements and physiological signals. However, an increasing number of studies are requiring pressure sensors with high performance while also seeking low-cost, large-scale, or even disposable manufacturing methods. In this study, we propose a flexible capacitive sensor based on low-cost, tailorable materials. The sensor employs a polyurethane sponge coated with inert metals, namely copper and nickel (Cu@Ni/PUS), as electrodes and a polyimide (PI) film as the dielectric layer. The prepared pressure sensors exhibit high sensitivity (0-17.5 kPa, 49.14% kPa-1), a rapid response time (80 ms), low hysteresis (6.49%), and high stability. Furthermore, the Cu@Ni/PUS sensor was integrated into an insulated glove, and an innovative, improved Morse code encoding scheme was developed. By combining the CNN-TCN dual-channel neural network model, we achieved the high-precision classification of the 26 alphabet letters (99.20%), providing a method for low-cost, high-efficiency Morse code transmission using flexible tactile sensors. Based on these findings, we also developed an improved Morse code real-time translation system that completes real-time encryption and decryption of improved Morse code gestures. The experimental results demonstrate that this research has broad application prospects in low-cost, accessible human-computer interaction and wearable devices for individuals with disabilities.