Papers
2
Total Citations
47
H-Index
2
About
Astha Verma is a leading researcher in biomechanics and human motion analysis, with a focused expertise in the computational modeling of gait. Her work centers on the development of advanced kinematic models to decode the complex sub-phases of human locomotion. Verma’s major contribution lies in pioneering the use of Long Short-Term Memory (LSTM) networks and universal polynomial equations to calculate real-time inverse kinematics (IK) for the lower limb. By deriving joint angle values from leg positions during walking, she has created robust, data-driven tools that eliminate the need for cumbersome sensor arrays. Her most cited paper, "Development of the LSTM Model and Universal Polynomial Equation for All the Sub-Phases of Human Gait" (2023), has garnered 42 citations, reflecting its immediate impact on rehabilitation robotics and prosthetics design. This work, building on her earlier 2021 study, provides a unified mathematical framework applicable across all gait sub-phases, enabling more precise and adaptive assistive technologies. Verma’s research bridges the gap between theoretical kinematics and practical, real-world applications, offering a scalable solution for clinical gait analysis and wearable robotics. Her achievements position her as a key innovator in making human motion analysis more accessible and computationally efficient.
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