Estimation of Middle Finger Motion Using Extended Kalman Filter

In this digital era, people are likely to forget about their physical health, so that many diseases can attack them. One of the diseases they often suffer from is a disease caused by nervous disorders, stroke. Stroke has long-term impacts on the person experiencing it. Some of the therapies required for post-stroke rehabilitation are physical therapy and occupational therapy by practicing several active movements such as walking slowly (even if you are still using assistive devices), holding, etc. One part of the body that needs training is the muscles of the hands and fingers, with the aim of returning the condition of the hands and the movement of the fingers to normal. So, the assistance of a robotic finger arm or Prosthetic Robotic Arm is needed. One of the efforts to develop a robotic finger arm assistance is finger movement estimation. One reliable estimation method that frequently used is the Extended Kalman Filter (EKF) method. In this paper, the study was conducted regarding the comparison of two simulations, that is, the simulation by the EKF method of the movement of the middle finger on the right hand and that of the middle finger on the left hand. And, the simulation results showed that it has an error of around 3 -7%.