Cross-step detection using center-of-pressure based algorithm for real-time applications

The proposed algorithm represents an advancement in gait event detection on instrumented treadmills. By leveraging the CoP signal, it successfully identifies gait events and cross-steps in the simulated real-time processing operation, providing valuable insights into human locomotion. The algorithm's ability to accommodate diverse CoP patterns enhance its applicability to a wide range of individuals and gait characteristics. The algorithm's performance was consistent across different populations, suggesting its potential for diverse clinical and research settings, particularly in the domains of gait analysis and rehabilitation practices.