Prithvi Patil

National Institute of Technology Srinagar

Papers

Total Citations

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About

Prithvi Patil is a researcher at the forefront of biomedical engineering and computational intelligence, with a primary focus on clinical gait analysis and human motion recognition. His most influential work, "Clinical Human Gait Classification: Extreme Learning Machine Approach" (2019), has garnered 93 citations and introduces a novel application of the Extreme Learning Machine (ELM) algorithm for biometric gait pattern classification. This contribution is particularly significant for early detection of gait abnormalities in patients with brain or neurological disorders—conditions where subtle deviations often evade standard clinical observation. By demonstrating that machine learning can reliably classify pathological gait patterns, Patil’s research bridges the gap between advanced computational methods and practical clinical diagnostics. His work holds promise for non-invasive, low-cost screening tools that could transform rehabilitation monitoring and neurodegenerative disease management. Beyond this landmark paper, Patil continues to explore the intersection of sensor-based biomechanics and deep learning, aiming to develop real-time systems for personalized healthcare. His contributions are shaping a future where data-driven gait analysis becomes a routine part of neurological assessment, offering hope for earlier intervention and improved patient outcomes.