A Novel User-Specific Wearable Controller for Surgical Robots

Abstract

Wearable sensors have emerged as an active field of research in human-computer interaction. This study explores the use of wearable sensors to detect human motion for precise control of a two-arm surgical robot designed for gripping and dissecting tissues. The wearable sensory sheath was designed with flexible e-textile bipolar electrodes to collect forearm electromyogram (EMG) and inertial measurement units (IMU) to capture arm motions of the user. Four pairs of bipolar electrodes were used to collect EMG from the forearm muscles and two IMU for detecting rotation and translation of each arm of the subject. Features were extracted from the EMG and linear discriminant analysis was used as the decoding method to classify the signals of the muscles. A calibration procedure was setup in the beginning for calibrating the IMU sensors to familiarize the user with the working space environment and the mapped-motions of the robot arms. A training session was then conducted for each user to control wrist flexion, wrist extension, hand opening and hand closure of the robot arms. Six users were asked to perform random arm and hand movements to ensure satisfactory mapping of the movements of the surgical robot. To evaluate the system, two tasks which were important in controlling surgical robots were designed: (1) using the dissector to mark dots along a straight line and (2) lifting a weight from one location to another. The results of this study found that the performance of different users in operating the motion controller and the wearable sensory sheath were similar in accuracy. Most users completed the same task in a shorter time with a standard motion controller than the wearable sensory sheath. The results show that most users adapt to a standard motion controller faster than the wearable sensors although the latter can be calibrated individually and is a user-specific approach for the control of robot.