scholarly journals Decoding a New Neural–Machine Interface for Control of Artificial Limbs

2007 ◽  
Vol 98 (5) ◽  
pp. 2974-2982 ◽  
Author(s):  
Ping Zhou ◽  
Madeleine M. Lowery ◽  
Kevin B. Englehart ◽  
He Huang ◽  
Guanglin Li ◽  
...  
Keyword(s):  
Motor Control ◽  
Degrees Of Freedom ◽  
Clinical Success ◽  
Surface Emg ◽  
Robotic Arm ◽  
Electrode Arrays ◽  
Control Information ◽  
Targeted Muscle Reinnervation ◽  
Prosthetic Limbs ◽  
Machine Interface

An analysis of the motor control information content made available with a neural–machine interface (NMI) in four subjects is presented in this study. We have developed a novel NMI–called targeted muscle reinnervation (TMR)—to improve the function of artificial arms for amputees. TMR involves transferring the residual amputated nerves to nonfunctional muscles in amputees. The reinnervated muscles act as biological amplifiers of motor commands in the amputated nerves and the surface electromyogram (EMG) can be used to enhance control of a robotic arm. Although initial clinical success with TMR has been promising, the number of degrees of freedom of the robotic arm that can be controlled has been limited by the number of reinnervated muscle sites. In this study we assess how much control information can be extracted from reinnervated muscles using high-density surface EMG electrode arrays to record surface EMG signals over the reinnervated muscles. We then applied pattern classification techniques to the surface EMG signals. High accuracy was achieved in the classification of 16 intended arm, hand, and finger/thumb movements. Preliminary analyses of the required number of EMG channels and computational demands demonstrate clinical feasibility of these methods. This study indicates that TMR combined with pattern-recognition techniques has the potential to further improve the function of prosthetic limbs. In addition, the results demonstrate that the central motor control system is capable of eliciting complex efferent commands for a missing limb, in the absence of peripheral feedback and without retraining of the pathways involved.

The Development of a Myoelectric Training Tool for Above-Elbow Amputees

2012 ◽  
Vol 6 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Michael R Dawson ◽  
Farbod Fahimi ◽  
Jason P Carey
Keyword(s):  
Degrees Of Freedom ◽  
Learning Task ◽  
Robotic Arm ◽  
Signal Acquisition ◽  
Myoelectric Prosthesis ◽  
Training Tool ◽  
Myoelectric Prostheses ◽  
Training Systems ◽  
Targeted Muscle Reinnervation

The objective of above-elbow myoelectric prostheses is to reestablish the functionality of missing limbs and increase the quality of life of amputees. By using electromyography (EMG) electrodes attached to the surface of the skin, amputees are able to control motors in myoelectric prostheses by voluntarily contracting the muscles of their residual limb. This work describes the development of an inexpensive myoelectric training tool (MTT) designed to help upper limb amputees learn how to use myoelectric technology in advance of receiving their actual myoelectric prosthesis. The training tool consists of a physical and simulated robotic arm, signal acquisition hardware, controller software, and a graphical user interface. The MTT improves over earlier training systems by allowing a targeted muscle reinnervation (TMR) patient to control up to two degrees of freedom simultaneously. The training tool has also been designed to function as a research prototype for novel myoelectric controllers. A preliminary experiment was performed in order to evaluate the effectiveness of the MTT as a learning tool and to identify any issues with the system. Five able-bodied participants performed a motor-learning task using the EMG controlled robotic arm with the goal of moving five balls from one box to another as quickly as possible. The results indicate that the subjects improved their skill in myoelectric control over the course of the trials. A usability survey was administered to the subjects after their trials. Results from the survey showed that the shoulder degree of freedom was the most difficult to control.

Selective motor fascicle transfer and neural-machine interface: case report

2020 ◽  
Vol 132 (3) ◽  
pp. 825-831 ◽  
Author(s):  
Takehiko Takagi ◽  
Yosuke Ogiri ◽  
Ryu Kato ◽  
Mitsuhiko Kodama ◽  
Yusuke Yamanoi ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Elbow Flexion ◽  
Identification Rate ◽  
Multiple Degrees Of Freedom ◽  
Targeted Muscle Reinnervation ◽  
Nerve Transfers ◽  
Nerve Fascicle ◽  
Machine Interface ◽  
Electromyographic Signal ◽  
Long Head

An amputated nerve transferred to a nearby muscle produces a transcutaneously detectable electromyographic signal corresponding to the transferred nerve; this technique is known as targeted muscle reinnervation (TMR). There are 2 issues to overcome to improve this technique: the caliber and the selectivity of the transferred nerve. It is optimal to select and transfer each motor fascicle to achieve highly developed myoelectric arms with multiple degrees-of-freedom motion. The authors report on a case in which they first identified the remnant stumps of the amputated median and radial nerves and then identified the sensory fascicles using somatosensory evoked potentials. Each median nerve fascicle was transferred to the long head branch of the biceps or the brachialis branch, while the short head branch of the biceps was retained for elbow flexion. Each radial nerve fascicle was transferred to the medial or lateral head branch of the triceps, while the long head branch of the triceps was retained for elbow extension. Electrophysiological and functional tests were conducted in the reinnervated muscles. Functional and electrophysiological improvement was noted, with marked improvement in the identification rate for each digit, forearm, and elbow motion after the selective nerve transfers. The authors note that more selective nerve transfers may be required for the development of prostheses with multiple degrees of freedom.

scholarly journals Noninvasive Electroencephalogram Based Control of a Robotic Arm for Reach and Grasp Tasks

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jianjun Meng ◽  
Shuying Zhang ◽  
Angeliki Bekyo ◽  
Jaron Olsoe ◽  
Bryan Baxter ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Human Subjects ◽  
Brain Activity ◽  
Computer Interface ◽  
Robotic Arm ◽  
Multiple Degrees Of Freedom ◽  
Non Invasive ◽  
Prosthetic Limbs ◽  
Reach And Grasp ◽  
Low Dimensional

Abstract Brain-computer interface (BCI) technologies aim to provide a bridge between the human brain and external devices. Prior research using non-invasive BCI to control virtual objects, such as computer cursors and virtual helicopters, and real-world objects, such as wheelchairs and quadcopters, has demonstrated the promise of BCI technologies. However, controlling a robotic arm to complete reach-and-grasp tasks efficiently using non-invasive BCI has yet to be shown. In this study, we found that a group of 13 human subjects could willingly modulate brain activity to control a robotic arm with high accuracy for performing tasks requiring multiple degrees of freedom by combination of two sequential low dimensional controls. Subjects were able to effectively control reaching of the robotic arm through modulation of their brain rhythms within the span of only a few training sessions and maintained the ability to control the robotic arm over multiple months. Our results demonstrate the viability of human operation of prosthetic limbs using non-invasive BCI technology.

scholarly journals BIOMIMETIC DESIGN OF LOW STIFFNESS ACTUATOR SYSTEMS FOR PROSTHETIC LIMBS

2011 ◽  
Author(s):  
D. L. Russell ◽  
M. McTavish
Keyword(s):  
Mechanical Properties ◽  
Degrees Of Freedom ◽  
Analytical Techniques ◽  
Energetic Costs ◽  
Multiple Degrees Of Freedom ◽  
Prosthetic Limbs ◽  
Limb Stiffness ◽  
Human Arm ◽  
Biomimetic Approach ◽  
Low Stiffness

The various relationships that are possible between the mechanical properties of single actuators and the overall mechanism (in this case a human arm with or without a prosthetic elbow) are discussed. Graphical and analytical techniques for describing the range of overall limb stiffnesses that are achievable and for characterizing the overall limb stiffness have been developed. Using a biomimetic approach and, considering energetic costs, stability and complexity, the implications of choosing passive or active implementations of stiffness are discussed. These techniques and approaches are particularly applicable with redundant (agonist - antagonist) actuators and multiple degrees of freedom. Finally, a novel biomimetic approach for control is proposed.

Design Human-Robot Collaborative Lifting Task Using Optimization

2021 ◽  
Author(s):  
Asif Arefeen ◽  
Yujiang Xiang
Keyword(s):  
Degrees Of Freedom ◽  
Joint Angle ◽  
Joint Torque ◽  
Robotic Arm ◽  
Inverse Dynamic ◽  
Floating Base ◽  
Grasping Forces ◽  
Design Variables ◽  
Human Arm ◽  
Lifting Task

Abstract In this paper, an optimization-based dynamic modeling method is used for human-robot lifting motion prediction. The three-dimensional (3D) human arm model has 13 degrees of freedom (DOFs) and the 3D robotic arm (Sawyer robotic arm) has 10 DOFs. The human arm and robotic arm are built in Denavit-Hartenberg (DH) representation. In addition, the 3D box is modeled as a floating-base rigid body with 6 global DOFs. The interactions between human arm and box, and robot and box are modeled as a set of grasping forces which are treated as unknowns (design variables) in the optimization formulation. The inverse dynamic optimization is used to simulate the lifting motion where the summation of joint torque squares of human arm is minimized subjected to physical and task constraints. The design variables are control points of cubic B-splines of joint angle profiles of the human arm, robotic arm, and box, and the box grasping forces at each time point. A numerical example is simulated for huma-robot lifting with a 10 Kg box. The human and robotic arms’ joint angle, joint torque, and grasping force profiles are reported. These optimal outputs can be used as references to control the human-robot collaborative lifting task.

scholarly journals Simulating 3r robot dynamics using imported cad in Maplesim

2020 ◽  
pp. 401-413
Keyword(s):  
Degrees Of Freedom ◽  
Research Field ◽  
Robotic Arm ◽  
Robot Dynamics ◽  
Industrial Education ◽  
Learning And Teaching ◽  
Manufacturing Efficiency ◽  
Potential Basis ◽  
And Control ◽  
Support Research

With the development of information technology, many applications of robots are increasingly being applied to support research, learning, and teaching. This paper mainly investigates the modeling and simulation of a robotic arm with 3 degrees of freedom (dofs) for different applications. First, Kinematics and dynamics model of the robot based on the standard Denavit Hartenberg (D-H) modeling method, where the forward kinematics of robot is analyzed and computed to obtain by using the inverse kinematics, and then the solution of the robot dynamics is derived. Second, a CAD model of the robot is designed on CATIA software to convert to MapleSim software to simulation and control. Final, numerical simulation is presented to display results. This work provides a potential basis for the realization of the robotic arm in the industrial, education, and research field, which is of great significance for improving manufacturing efficiency and support teaching and research in the robot field.

scholarly journals Postural Synergy-Based Exoskeleton Reproducing Natural Human Movements to Improve Upper Limb Motor Control after Stroke

2020 ◽  
Author(s):  
Chang He ◽  
Cai-Hua Xiong ◽  
Ze-Jian Chen ◽  
Wei Fan ◽  
Xiao-Lin Huang
Keyword(s):  
Motor Control ◽  
Upper Limb ◽  
Degrees Of Freedom ◽  
Response Rate ◽  
Human Movement ◽  
Interaction Force ◽  
Human Anatomy ◽  
Clinical Trial Registration ◽  
Upper Limb Exoskeleton ◽  
Human Movements

Abstract Background: Upper limb exoskeletons have drawn significant attention in neurorehabilitation because of anthropomorphic mechanical structure analogous to human anatomy. Whereas, the training movements are typically underorganized because most exoskeletons only control the movement of the hand in space, without considering rehabilitation of joint motion, particularly inter-joint postural synergy. The purposes of this study were to explore the application of a postural synergy-based exoskeleton (Armule) reproducing natural human movements for robot-assisted neurorehabilitation and to preliminarily assess its effect on patients' upper limb motor control after stroke. Methods: We developed a novel upper limb exoskeleton based on the concept of postural synergy, which provided five degrees of freedom (DOF) , natural human movements of the upper limb. Eight participants with hemiplegia due to a first-ever, unilateral stroke were recruited and included. They participated in exoskeleton therapy sessions 45 minutes/day, 5 days/week for 4 weeks, with passive/active training under anthropomorphic trajectories and postures. The primary outcome was the Fugl-Meyer Assessment for Upper Extremities (FMA-UE). The secondary outcomes were the Action Research Arm Test(ARAT), modified Barthel Index (mBI) , and exoskeleton kinematic as well as interaction force metrics: motion smoothness in the joint space, postural synergy error, interaction force smoothness, and the intent response rate. Results: After the 4-weeks intervention, all subjects showed significant improvements in the following clinical measures: the FMA-UE ( p =0.02), the ARAT ( p =0.003), and the mBI score ( p <0.001). Besides, all subjects showed significant improvements in motion smoothness ( p =0.004), postural synergy error ( p =0.014), interaction force smoothness ( p =0.004), and the intent response rate ( p =0.008). Conclusions: The subjects were well adapted to our device that assisted in completing functional movements with natural human movement characteristics. The results of the preliminary clinical intervention indicate that the Armule exoskeleton improves individuals’ motor control and activities of daily living (ADL) function after stroke, which might be associated with kinematic and interaction force optimization and postural synergy modification during functional tasks. Clinical trial registration: ChiCTR, ChiCTR1900026656; Date of registration: October 17, 2019. http://www.chictr.org.cn/showproj.aspx?proj=44420

A remote center of motion robotic arm for computer assisted surgery

Robotica ◽  
1996 ◽  
Vol 14 (1) ◽  
pp. 103-109 ◽  
Author(s):  
B. Eldridge ◽  
K. Gruben ◽  
D. LaRose ◽  
J. Funda ◽  
S. Gomory ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Computer Assisted Surgery ◽  
Video Camera ◽  
Robotic Arm ◽  
Computer Assisted ◽  
Robot Arm ◽  
Minimally Invasive Surgical ◽  
Tissue Manipulation ◽  
Servo Controller ◽  
Rotation Stage

SummaryWe have designed a robotic arm based on a double parallel four bar linkage to act as an assistant in minimally invasive surgical procedures. The remote center of motion (RCM) geometry of the robot arm kinematically constraints the robot motion such that minimal translation of an instrument held by the robot takes place at the entry portal into the patientApos;s body. In addition to the two rotational degrees of freedom comprising the RCM arm, distal translation and rotation are provided to manoeuver the instrument within the patient's body about an axis coincident with the RCM. An XYZ translation stage located proximal to the RCM arm provides positioning capability to establish the RCM location relative to the patients anatomy. An electronics set capable of controlling the system, as well as performing a series of safety checks to verify correct system operation, has also been designed and constructed. The robot is capable of precise positional motion. Repeatability in the ±10 micron range is demonstrated. The complete robotic system consists of the robot hardware and an IBM PC-AT based servo controller connected via a custom shared memory link to a host IBM PS/2. For laparoscopic applications, the PS/2 includes an image capture board to capture and process video camera images. A camera rotation stage has also been designed for this application. We have successfully demonstrated this system as an assistant in a laparoscopic cholecystectomy. Further applications for this system involving active tissue manipulation are under development.

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