Smriti Bala
Papers
2
Total Citations
13
H-Index
2
About
Smriti Bala is a rising researcher at the forefront of neurorehabilitation and human-machine interaction, specializing in the forecasting and monitoring of muscle fatigue. Her work is pivotal for advancing adaptive control in assistive technologies, including exoskeletons, prostheses, and functional electrical stimulation (FES)-based neuroprostheses. Bala’s major contributions lie in developing sophisticated deep learning models to predict fatigue-induced changes in surface electromyography (sEMG) signals. Her most-cited paper, "MEFFNet: Forecasting Myoelectric Indices of Muscle Fatigue in Healthy and Post-Stroke During Voluntary and FES-Induced Dynamic Contractions" (2024, 7 citations), introduces a novel network for real-time fatigue monitoring in both healthy and clinical populations. Complementing this, her earlier work, "An Attention-based Deep CNN-BiLSTM Model for Forecasting of Fatigue-induced sEMG Signals During Isotonic Contractions" (2022, 6 citations), demonstrates a powerful hybrid architecture that captures the non-stationary nature of fatigue. By enabling accurate, long-duration fatigue estimation, Bala’s research directly enhances the safety and efficacy of wearable robotics and neuroprosthetic control, marking her as a key innovator in the field.
Research Focus
Key Achievements
Top Papers
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