An EMG Interface for the Control of Motion and Compliance of a Supernumerary Robotic Finger

Abstract

In this paper, we propose a novel electromyographic (EMG) control interface to control motion and joints compliance of a supernumerary robotic finger. The supernumerary robotic fingers are a recently introduced class of wearable robotics that provides users additional robotic limbs in order to compensate or augment the existing abilities of natural limbs without substituting them. Since supernumerary robotic fingers are supposed to closely interact and perform actions in synergy with the human limbs, the control principles of extra finger should have similar behavior as human's ones including the ability of regulating the compliance. So that, it is important to propose a control interface and to consider the actuators and sensing capabilities of the robotic extra finger compatible to implement stiffness regulation control techniques. We propose EMG interface and a control approach to regulate the compliance of the device through servo actuators. In particular, we use a commercial EMG armband for gesture recognition to be associated with the motion control of the robotic device and surface one channel EMG electrodes interface to regulate the compliance of the robotic device. We also present an updated version of a robotic extra finger where the adduction/abduction motion is realized through ball bearing and spur gears mechanism. We have validated the proposed interface with two sets of experiments related to compensation and augmentation. In the first set of experiments, different bimanual tasks have been performed with the help of the robotic device and simulating a paretic hand since this novel wearable system can be used to compensate the missing grasping abilities in chronic stroke patients. In the second set, the robotic extra finger is used to enlarge the workspace and manipulation capability of healthy hands. In both sets, the same EMG control interface has been used. The obtained results demonstrate that the proposed control interface is intuitive and can successfully be used, not only to control the motion of a supernumerary robotic finger but also to regulate its compliance. The proposed approach can be exploited also for the control of different wearable devices that has to actively cooperate with the human limbs.

Keywords: compliance control; supernumerary robotic fingers; wearable robotics.

Figure 1

On left, the exploded cad view, whereas on right, the prototype of the robotic extra finger. Four modules are used for the flexion/extension motion, while the revolute joint based on bearings and spur gears mechanism at the finger base is used for the adduction/abduction motion. The device can be worn on the forearm through an elastic band.

Figure 2

The complete system: the EMG interface on one arm, whereas the supernumerary robotic finger is on the other arm. Myo Armband is positioned on the forearm, while the one channel interface is placed on the biceps muscle.

Figure 3

Block diagram of complete system. On top left, the block diagram of EMG one channel interface is shown, where (a) surface electrodes, (b) snap leads, (c) acquisition board, and (d) control board. On top, right, the myoarm band with its major components (e) logo LED, (f) status LED, (g) expandable flex, (h) micro USB charging port, and (i) electrical sensor.

Figure 4

Block diagram of the EMG circuit board (Gain = 1000; Bandwidth = 10–400 Hz). V_IN+ and V_IN− are the “detecting electrodes” while V_ss = V_cc/2 is the “ground electrode.”

Figure 5

On left, (A) the maximum voluntary contraction (MVC) proportional to the biceps muscle contraction is shown. While on right, (B) the graph between Δq and percentage of MVC for different values of k_d is plotted.

Figure 6

Examples of possible achievable grasps at working positions (A–D) and bracelet at rest position (E). In (A,B), the robotic finger coordinates with healthy hand to realize the anatomically impossible and ulnar grasp, respectively. While in (C,D), it interacts with paretic hand to realize power and precision grasp.

Figure 7

(A) The recognized gestures and associated trigger signal. (B) The finite state machine that controls the motion of the robotic device in corresponds to the generated gesture.

Figure 8

Supernumerary robotic finger helping in bimanual task of ADL. All the bimanual tasks can be completed in the presence of robotic device even if one hand is non-functional. (A) Opening coffee can, (B) opening meat can, (C) pouring water, (D) opening mustard container, (E) opening gelatin box, and (F) opening tomato can.

Figure 9

Examples of tasks performed by the augmented hand, i.e., human hand plus supernumerary robotic finger. In all the tasks, the human healthy hand and robotic finger work together to complete the tasks that are impossible to do with human hand only. (A) Unscrewing a cap of bottle, (B) grasping bigger box, (C) grasping two balls, (D) opening door, (E) soldering a board, and (F) grasping plate and glass.

Figure 10

Forces exerted by the modules on the grasped object during a power grasp.

Figure 11

Positions of the modules during a power grasp.

Figure 12

Forces exerted by the modules on the grasped object during a precision grasp.

Figure 13

Positions of the modules during a precision grasp.

Figure 14

Raw EMG signal captured by the one channel interface during the execution of the task reported in Figure 8A.

Figure 15

The processed EMG signal used to compute the value of parameter k_d.