Grip Force

Grip force research focuses on understanding and controlling the force applied during grasping, with key objectives including accurate prediction and assistive technologies for individuals with impaired hand function. Current research employs diverse approaches, including machine learning models like recurrent neural networks (RNNs) and Koopman operators, often leveraging electromyography (EMG) signals to estimate and predict grip force in real-time. These advancements hold significant promise for improving robotic prosthetics, rehabilitation tools, and human-robot collaboration by enabling more natural and intuitive interaction.