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During the preceding decades, human gait analysis has been the center ofattention for the scientific community, while the association between gaitanalysis and overall health monitoring has been extensively reported.Technological advances further assisted in this alignment, resulting in accessto inexpensive and remote healthcare services. Various assessment tools, suchas software platforms and mobile applications, have been proposed by thescientific community and the market that employ sensors to monitor human gaitfor various purposes ranging from biomechanics to the progression of functionalrecovery. The framework presented herein offers a valuable digital biomarkerfor diagnosing and monitoring Parkinson's disease that can help clinicalexperts in the decision-making process leading to corrective planning orpatient-specific treatment. More accurate and reliable decisions can beprovided through a wide variety of integrated Artificial Intelligencealgorithms and straightforward visualization techniques, including, but notlimited to, heatmaps and bar plots. The framework consists of three corecomponents: the insole pair, the mobile application, and the cloud-basedplatform. The insole pair deploys 16 plantar pressure sensors, anaccelerometer, and a gyroscope to acquire gait data. The mobile applicationformulates the data for the cloud platform, which orchestrates the componentinteraction through the web application. Utilizing open communication protocolsenables the straightforward replacement of one of the core components with arelative one (e.g., a different model of insoles), transparently from the enduser, without affecting the overall architecture, resulting in a framework withthe flexibility to adjust its modularity.

Smart Insole: A Gait Analysis Monitoring Platform Targeting Parkinson Disease Patients Based on Insoles