Force Sensitive Resistors (FSRs) are used for kinetic evaluation of human gait by measuring under foot pressures during gait. FSRs from different manufacturers, with variation in morphologies and loading capacities were selected in past research projects. However a functional comparison of different FSRs and options on how to choose them for gait analysis is not established yet. In this work, investigation and comparison of behavioral patterns in measuring normal gait from two major FSR sensors are done. These FSRs had been utilised previously for the purpose of gait sensing. They were placed underneath the heel alternatively to detect heel pressures while wearing footwear with laces and with another footwear possessing straps for harnessing. Both sensors are connected to a miniature low power wireless senor node used for data collection and wireless transmission for off-line analysis of pressure patterns. The results give good indications on capabilities and trade-offs when using the two sensors types.
Electrical stimulators are often prescribed to correct foot drop walking. However, commercial foot drop stimulators trigger inappropriately under certain non-gait scenarios. Past researches addressed this limitation by defining stimulation control based on automaton of a gait cycle executed by foot drop of affected limb/foot only. Since gait is a collaborative activity of both feet, this research highlights the role of normal foot for robust gait detection and stimulation triggering. A novel bipedal gait model is proposed where gait cycle is realized as an automaton based on concurrent gait sub-phases (states) from each foot. The input for state transition is fused information from feet-worn pressure and inertial sensors. Thereafter, a bipedal gait model-based stimulation control algorithm is developed. As a feasibility study, bipedal gait model and stimulation control are evaluated in real-time simulation manner on normal and simulated foot drop gait measurements from 16 able-bodied participants with three speed variations, under inappropriate triggering scenarios and with foot drop rehabilitation exercises. Also, the stimulation control employed in commercial foot drop stimulators and single foot gait-based foot drop stimulators are compared alongside. Gait detection accuracy (98.9%) and precise triggering under all investigations prove bipedal gait model reliability. This infers that gait detection leveraging bipedal periodicity is a promising strategy to rectify prevalent stimulation triggering deficiencies in commercial foot drop stimulators. Graphical abstract Bipedal information-based gait recognition and stimulation triggering.
The approach can be employed in different contexts, such as enabling pedestrian localization approaches to accommodate back stepping or any application that requires knowledge of changing directions while walking.
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