A novel plantar pressure analysis method to signify gait dynamics in Parkinson's disease

Abstract

<abstract><p>Plantar pressure can signify the gait performance of patients with Parkinson's disease (PD). This study proposed a plantar pressure analysis method with the dynamics feature of the sub-regions plantar pressure signals. Specifically, each side's plantar pressure signals were divided into five sub-regions. Moreover, a dynamics feature extractor (DFE) was designed to extract features of the sub-regions signals. The radial basis function neural network (RBFNN) was used to learn and store gait dynamics. And a classification mechanism based on the output error in RBFNN was proposed. The classification accuracy of the proposed method achieved 100.00% in PD diagnosis and 95.89% in severity assessment on the online dataset, and 96.00% in severity assessment on our dataset. The experimental results suggested that the proposed method had the capability to signify the gait dynamics of PD patients.</p></abstract>

AI-Assisted Insole Sensing System for Multifunctional Plantar-Healthcare Applications

“…11 Similarly, patients with peripheral neuropathy may exhibit a reduced stride length while experiencing a marked increase in cadence. 12 Additionally, individuals with Parkinson's disease tend to exhibit a significant increase in pressure on the toes compared to the general population, 13 whereas stroke patients typically concentrate their plantar pressure on the lateral side of the foot. 14 These aforementioned major diseases show a high prevalence worldwide, with each manifesting unique alterations in gait parameters.…”