IoT-Enabled Soft Capacitive Tactile Sensors: Characterization Through Linear Regression Analysis

Soft and flexible capacitive tactile sensors have become important tools for precise force measurement in wearable health monitors, soft robotics, and advanced human-machine interaction systems. Their real-time ability to detect and quantify forces opens new boundaries in medical diagnostics, automation safety, and adaptive technologies. This work presents a 4×4 capacitive sensor matrix fabricated using thermoplastic polyurethane (TPU) substrates and nanoparticle-based silver ink, with a 300 μm Ecoflex 30 dielectric layer to ensure high sensitivity and reliability. The matrix integrates passive electromagnetic interference (EMI) shielding to enhance signal integrity while maintaining robust force detection. The system employs a mutual capacitance sensing board (MUCA) for data acquisition and an SHT30 sensor for monitoring environmental parameters like temperature and humidity. Real-time data processing and visualization are achieved via a lightweight Wi-Fi-enabled dashboard hosted on an Arduino Nano 33 IoT microcontroller. This dashboard dynamically displays force distributions, heatmaps, and environmental metrics, offering an intuitive user interface. The sensor matrix demonstrates a force detection range of 1 to 16 N, with a strong linear correlation (R2 = 0.9952) between force and mutual capacitance changes, validated through extensive single and multi-touch testing using a universal manipulator. The system's battery-efficient design enables continuous operation for over 148 hours, making it suitable for remote and autonomous applications. Potential applications span wearable prosthetics, soft robotics, and IoT-driven systems. This work highlights the integration of scalable fabrication, robust signal processing, and real-time visualization to offer a versatile and energy-efficient tactile sensing solution.