Supernumerary Robotic Fingers Research Articles

Development of Flexure‐Based Supernumerary Robotic Finger for Hand Function Augmentation

This study introduces a flexure‐based supernumerary robotic finger (FBSF) inspired by the proportions of the human thumb, aiming to overcome existing limitations in robotic finger design. In pursuit of seamless cooperation with the user's hand, human finger proportions are replicated. Finite element analysis of all five fingers indicates that the thumb‐mimicking configuration offers the largest workspace and bending angle. The FBSF, featuring a polycarbonate paired crossed flexural hinge structure and high impact polystyrene links, closely mirrors the human thumb. Weighing 59 g (main body) and 170 g (control box), the FBSF enables user‐driven control and decoupled actuation based on user intent, utilizing the electromyographic signal of the extensor carpi ulnaris via isometric contractions. An experimental protocol, including task blocks (releasing, clenching), confirms the FBSF's responsiveness to user intentions. When utilizing FBSF, it has been verified using a motion capture camera system that it is possible to extend the existing hand workspace by approximately 29.72%. Performance tests demonstrate the FBSF's capability to grasp various objects and assist in tasks, with a maximum load‐bearing capacity of 2.6 kg experimentally verified. This study demonstrates the potential of the developed FBSF to augment hand functionality in diverse applications.

Functional Reorganization After Four-Week Brain-Computer Interface-Controlled Supernumerary Robotic Finger Training: A Pilot Study of Longitudinal Resting-State fMRI.

Humans have long been fascinated by the opportunities afforded through motor augmentation provided by the supernumerary robotic fingers (SRFs) and limbs (SRLs). However, the neuroplasticity mechanism induced by the motor augmentation equipment still needs further investigation. This study focused on the resting-state brain functional reorganization during longitudinal brain–computer interface (BCI)-controlled SRF training in using the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC) metrics. Ten right-handed subjects were enrolled for 4 weeks of BCI-controlled SRF training. The behavioral data and the neurological changes were recorded at baseline, training for 2 weeks, training for 4 weeks immediately after, and 2 weeks after the end of training. One-way repeated-measure ANOVA was used to investigate long-term motor improvement [F(2.805,25.24) = 43.94, p < 0.0001] and neurological changes. The fALFF values were significantly modulated in Cerebelum_6_R and correlated with motor function improvement (r = 0.6887, p < 0.0402) from t0 to t2. Besides, Cerebelum_9_R and Vermis_3 were also significantly modulated and showed different trends in longitudinal SRF training in using ReHo metric. At the same time, ReHo values that changed from t0 to t1 in Vermis_3 was significantly correlated with motor function improvement (r = 0.7038, p < 0.0344). We conclude that the compensation and suppression mechanism of the cerebellum existed during BCI-controlled SRF training, and this current result provided evidence to the neuroplasticity mechanism brought by the BCI-controlled motor-augmentation devices.

Development of 6 DOF Supernumerary Robotic Fingers Integrated with 3D Animation

The paper presents the development of wearable robot called supernumerary robotic fingers (SRF) that can be integrated with 3D Animation. The robot comprises of two parts, robotic finger (RF) and robotic thumb (RT). RF is located next to little finger, and RT is located next to the thumb. The robot is driven by modified glove sensor. 3D CAD model is exported into SimMechanics for 3D Animation purpose under MATLAB/Simulink environment. Forward kinematics of the robot is studied using SimMechanics and the trajectory of each robotic fingertip will be calculated. Based on the experimental result, the robot and its 3D animation can be operated by a healthy person in real time. The robot can assist in object manipulation with ten-inch tablet using single human hand.

Development of Low Cost Supernumerary Robotic Fingers as an Assistive Device

This paper presents the development of new type of wearable robot namely Supernumerary Robotic Finger (SRF) as an assistive robot for healthy people or people with hemiparesis or hemiplegia. SRF comprises of two manipulators attached in user's wrist. Three flex sensors are utilized to measure the finger bending of the user's finger. The posture of SRF is driven by modified glove sensor. The kinematics of both robotic thumb (RT) and robotic finger (RF) is studied using D-H parameter method and RoboAnalyzer software in order to understand the kinematic behavior of this robot. Each of RT and RF has three degrees of freedom (DOF). The posture of RT and RF is controlled using bending angles of thumb and finger from the user that are read by flex sensor. Based on the experimental results for people with healthy hand, the proposed SRF can assist object manipulation task in grasping, holding, and manipulating an object by using single hand when normally it only can be done by using two hands. From the experimental results on a person with healthy hand, the proposed of SRF can be employed as an assistive device for people with hemiparesis or hemiplegia. This device will enable people with diminished hand function work more independently.

Toward wearable supernumerary robotic fingers to compensate missing grasping abilities in hemiparetic upper limb

This paper presents the design, analysis, fabrication, experimental characterization, and evaluation of two prototypes of robotic extra fingers that can be used as grasp compensatory devices for a hemiparetic upper limb. The devices are the results of experimental sessions with chronic stroke patients and consultations with clinical experts. Both devices share a common principle of work, which consists in opposing the device to the paretic hand or wrist so to restrain the motion of an object. They can be used by chronic stroke patients to compensate for grasping in several activities of daily living (ADLs) with a particular focus on bimanual tasks. The robotic extra fingers are designed to be extremely portable and wearable. They can be wrapped as bracelets when not being used, to further reduce the encumbrance. Both devices are intrinsically compliant and driven by a single actuator through a tendon system. The motion of the robotic devices can be controlled using an electromyography-based interface embedded in a cap. The interface allows the user to control the device motion by contracting the frontalis muscle. The performance characteristics of the devices have been measured experimentally and the shape adaptability has been confirmed by grasping various objects with different shapes. We tested the devices through qualitative experiments based on ADLs involving five chronic stroke patients. The prototypes successfully enabled the patients to complete various bimanual tasks. Results show that the proposed robotic devices improve the autonomy of patients in ADLs and allow them to complete tasks that were previously impossible to perform.

Empirical characterization of modular variable stiffness inflatable structures for supernumerary grasp-assist devices

This paper presents the design, fabrication, and experimental characterization of modular, variable stiffness inflatable components for pneumatically actuated supernumerary robotic (SR) grasp-assist devices. The proposed SR grasp-assist devices are comprised of soft rigidizable finger phalanges and variable stiffness pneumatic bending actuators that are manufactured using soft lithography fabrication methods. The mechanical and kinematic properties of these modular, inflatable components are characterized experimentally under various loading conditions and over a range of geometric design parameters. The resulting data-driven properties are then used to predict the grasp strengths and motion patterns of SR grasp-assist device configurations designed to accommodate the manipulation of daily living objects. Experimental results demonstrate the ability to program grasp synergies into SR fingers by strategic inflation of the bending actuator antagonist chambers (varying mechanical stiffness), without the need for complicated, high-power mechanisms or precise, low-level motion control. The results also demonstrate the underactuated grasp adaptations enabled by modular inflatable components and the ability to predict mechanical grasping capabilities of wearable pneumatic SR grasp-assist devices using insights from empirical data.

A magnetic compatible supernumerary robotic finger for functional magnetic resonance imaging (fMRI) acquisitions: Device description and preliminary results.

The Supernumerary robotic limbs are a recently introduced class of wearable robots that, differently from traditional prostheses and exoskeletons, aim at adding extra effectors (i.e., arms, legs, or fingers) to the human user, rather than substituting or enhancing the natural ones. However, it is still undefined whether the use of supernumerary robotic limbs could specifically lead to neural modifications in brain dynamics. The illusion of owning the part of body has been already proven in many experimental observations, such as those relying on multisensory integration (e.g., rubber hand illusion), prosthesis and even on virtual reality. In this paper we present a description of a novel magnetic compatible supernumerary robotic finger together with preliminary observations from two functional magnetic resonance imaging (fMRI) experiments, in which brain activity was measured before and after a period of training with the robotic device, and during the use of the novel MRI-compatible version of the supernumerary robotic finger. Results showed that the usage of the MR-compatible robotic finger is safe and does not produce artifacts on MRI images. Moreover, the training with the supernumerary robotic finger recruits a network of motor-related cortical regions (i.e. primary and supplementary motor areas), hence the same motor network of a fully physiological voluntary motor gestures.

A soft supernumerary robotic finger and mobile arm support for grasping compensation and hemiparetic upper limb rehabilitation

In this paper, we present the combination of our soft supernumerary robotic finger i.e. Soft-SixthFinger with a commercially available zero gravity arm support, the SaeboMAS. The overall proposed system can provide the needed assistance during paretic upper limb rehabilitation involving both grasping and arm mobility to solve task-oriented activities. The Soft-SixthFinger is a wearable robotic supernumerary finger designed to be used as an active assistive device by post stroke patients to compensate the paretic hand grasp. The device works jointly with the paretic hand/arm to grasp an object similarly to the two parts of a robotic gripper. The SaeboMAS is a commercially available mobile arm support to neutralize gravity effects on the paretic arm specifically designed to facilitate and challenge the weakened shoulder muscles during functional tasks. The proposed system has been designed to be used during the rehabilitation phase when the arm is potentially able to recover its functionality, but the hand is still not able to perform a grasp due to the lack of an efficient thumb opposition. The overall system also act as a motivation tool for the patients to perform task-oriented rehabilitation activities.With the aid of proposed system, the patient can closely simulate the desired motion with the non-functional arm for rehabilitation purposes, while performing a grasp with the help of the Soft-SixthFinger. As a pilot study we tested the proposed system with a chronic stroke patient to evaluate how the mobile arm support in conjunction with a robotic supernumerary finger can help in performing the tasks requiring the manipulation of grasped object through the paretic arm. In particular, we performed the Frenchay Arm Test (FAT) and Box and Block Test (BBT). The proposed system successfully enabled the patient to complete tasks which were previously impossible to perform.

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

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.

Implicit and Intuitive Grasp Posture Control for Wearable Robotic Fingers: A Data-Driven Method Using Partial Least Squares

Functionality of a human hand can be augmented with wearable robotic fingers to enable grasping and manipulation of objects with a single hand. Such technology will have applications in manufacturing and construction, as well as health care. This paper presents a method for controlling extra robotic fingers, termed “Supernumerary Robotic Fingers (SR Fingers),” in coordination with human fingers to grasp diverse objects. Two hypotheses are proposed and verified through experiments. One is that humans prefer grasp posture of their fingers and that of the SR Fingers to be highly correlated when working together, which is represented with a few principal components, resembling grasp synergy in neuromotor control. The other hypothesis is that SR Finger posture can be controlled to coordinate with human finger posture via grasp synergy of the hybrid human–robotic hand. Partial least squares regression is used for predicting a desired posture of the SR Fingers from the measurement of human fingers. This method is implemented on a pair of wrist-mounted SR Fingers. Experiments demonstrate that the prototype SR Fingers can assist the human user in performing single-handed grasping tasks without requiring explicit commands.