Estimating joint angles from biological signals for multi-joint exoskeletons

Abstract

Biological signals are used to control robotic exoskeletons. Our research group has developed a Brain-Machine Interface (BMI)-based Occupational Therapy Assist Suit (BOTAS), which can be controlled by both electroencephalography (EEG) and electromyography (EMG) signals. This paper presents a new method for estimating the joint angles of the arms and hands for the BOTAS from EMG signals using mathematical musculoskeletal models. In six able-bodied participants, the method succeeded in estimating the flexion/extension angles of the elbow, wrist, and metacarpophalangeal (MP) joint of the index finger. In a patient with an upper cervical spinal cord injury, the method succeeded in estimating the elbow angles. The participants could control the BOTAS empowered by the method. These results suggest that the method is potentially useful for controlling robotic exoskeletons in patients with paralyzed arms and fingers.