This talk presents two works that explore human-technology interfaces for training and mobility. The first focuses on a mannequin-based simulation system for ophthalmic anesthesia training, developed to address the challenges and risks associated with needle-based intraorbital injections. The system replicates human ocular anatomy with high fidelity and integrates a multi-electrode capacitive sensing scheme to detect needle depth, proximity to extraocular muscles, and contact with critical structures. Trainees receive real-time visual feedback through a 3D GUI, enhancing procedural safety and competence in a risk-free environment. The second work introduces a wearable pathway classification system that uses shoes embedded with flexible electrodes to measure floor impedance. This impedance-based sensing method improves upon traditional vision-based techniques by capturing non-visual properties of the surface—such as moisture content—and enables accurate classification of pathways like soil, mud, grass, and pavement. The system has significant applications in assisting the visually impaired, lower-limb amputees, and diabetic patients, as well as in robotic navigation. Despite being developed in different contexts and time frames, both works aim to improve safety, decision-making, and environmental awareness through embedded sensing and real-time feedback.

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