| PhD Viva

Name of the Speaker: Mr. Shubhanshu Sharma (EE20D413)
Guide: Dr. Boby George
Online meeting link: https://meet.google.com/unb-qyvs-ubj
Date/Time: 19th September 2025 (Friday), 3:00 PM
Title: Design of a Wearable Ground Impedance Sensor for Pathway Classification, Gait Analysis, and Navigation Assistance

Abstract :

Safe mobility is critically affected in individuals with visual impairment, diabetic neuropathy, or lower-limb amputation due to impaired foot–eye coordination. Existing pathway classification schemes involving cameras, inertial measurement units, audio, vibration and ultrasonic-based signals rely on limited information about the pathways, often leading to restricted classification accuracy. In addition, it fails to sense the pathway condition, such as wet or dry. In this talk, a novel electrical impedance–based sensing framework for pathway classification and gait analysis is proposed. Modified footwear with flexible electrodes measures the impedance of pathways, including soil, mud, road, and grass. An analytical model based on conformal mapping is developed to estimate pathway electrical properties and validated against finite element analysis (FEA) and experimental measurements. The impedance data, in comparison with deep learning classifiers, enhances recognition performance, achieving 100% classification accuracy. The sensing framework is extended to gait analysis, enabling simultaneous estimation of pathway class and spatiotemporal gait parameters. Validation against force-plate references across seven subjects yielded average RMSE values of 0.02 s (stride time), 1.4 cm (stride length), and a maximum of ±5% error in walking speed, demonstrating high fidelity. To translate the technology into assistive devices, a smart cane prototype was developed. Unlike vision-based aids limited by ambient lighting, the impedance cane operates in real time and achieves 97.8% classification accuracy in controlled trials and 91.5% accuracy on unseen pathways. Finally, to overcome the limitations of inter-shoe current leakage, a single-shoe bipolar electrode system was proposed. Its robustness was demonstrated through FEA, laboratory experiments, and field trials, with results matching four-probe measurements. This work establishes impedance-based sensing as a practical solution for pathway classification, gait assessment, and assistive navigation.