SmartStrideFoG: Wearable system to characterize freezing of gait using Stride-to-Stride variability as a biomarker

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dc.contributor.author Raghuvanshi, Ankita
dc.contributor.author Yadav, Vaibhav Ramprasad
dc.contributor.author Kanetkar, Manasi
dc.contributor.author Lahiri, Uttama
dc.coverage.spatial India
dc.date.accessioned 2025-08-21T08:23:50Z
dc.date.available 2025-08-21T08:23:50Z
dc.date.issued 2025-06-05
dc.identifier.citation Raghuvanshi, Ankita; Yadav, Vaibhav Ramprasad; Kanetkar, Manasi and Lahiri, Uttama, "SmartStrideFoG: Wearable system to characterize freezing of gait using Stride-to-Stride variability as a biomarker", in the International Conference on Electronics, AI and Computing (EAIC 2025), Jalandhar, IN, Jun. 05-07, 2025.
dc.identifier.uri https://doi.org/10.1109/EAIC66483.2025.11101396
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/11786
dc.description.abstract Freezing of Gait (FoG) is a debilitating motor symptom of individuals with Parkinson’s Disease (PD). The FoG is characterized by sudden interruptions in movement despite one’s intention to walk. Research suggests the presence of a critical Pre-FoG window, marked by progressive reduction in stride length while walking. In this study, we used SmartStrideFoG, a wearable device consisting of shoes with instrumented insoles integrated with Inertial Measurement Units to quantify one’s gait in terms of spatial and temporal gait parameters. These gait parameters were subsequently analyzed to evaluate one’s stride-to-stride variability. Results of our study carried out with fourteen individuals with PD (GroupPD) and fourteen age-matched healthy counterparts (GroupH) showed the potential of SmartStrideFoG to quantify differences in the stride-to-stride variability of GroupPD and GroupH. Furthermore, SmartStrideFoG could identify the pre-FoG window by sensing abrupt changes in stride-to-stride variability even before the occurrence of freezing episode. This shows the potential of SmartStrideFoG to offer promising biomarker i.e., stride-to-stride variability for detection and prediction of FoG that can have clinical significance. This in turn can guide interventionists to adopt necessary clinical strategies to overcome forthcoming FoG, making it a valuable tool for clinical intervention.
dc.description.statementofresponsibility by Ankita Raghuvanshi, Vaibhav Ramprasad Yadav, Manasi Kanetkar and Uttama Lahiri
dc.language.iso en_US
dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
dc.subject Freezing of gait
dc.subject Inertial measurement units
dc.subject Instrumented insoles
dc.subject Wearable technology
dc.subject Parkinson's disease
dc.title SmartStrideFoG: Wearable system to characterize freezing of gait using Stride-to-Stride variability as a biomarker
dc.type Conference Paper
dc.relation.journal International Conference on Electronics, AI and Computing (EAIC 2025)


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