A biomimetic controller for a multifinger prosthesis

Abboudi, R.L.; Glass, C.A.; Newby, Nicki Ann; Flint, James A.; Craelius, William

doi:10.1109/86.769401

Cited by 58 publications

(43 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These include reliability and durability of the sensor sleeves, the ease of donning for users, ease of calibration, and compatibility with controller interfaces. Preliminary trials with amputees have demonstrated that donning and calibration of FMG are relatively simple, that its sensitivity is not seriously compromised by the wearing of a protective stocking, and that it works well with residua with severely damaged tissue [13]. A crucial component that is still lacking is an electronic interface with sufficient analog inputs that are compatible with diverse sensors to enable multidimensional control.…”

Section: Force Myography As Control Modalitymentioning

confidence: 99%

“…To date, FMG is the only neuromuscular imaging modality that has demonstrated simultaneous multifunctional and multiple degrees-of-freedom control of prosthetic hands [13][14][15]17], including multifinger operation by amputees. Previous results with amputees suggested the potential of FMG as a register of force magnitude volition [13]. Herein, we directly test its effectiveness in predicting grip force in nondisabled limbs.…”

Section: Introductionmentioning

confidence: 99%

“…Volitions concerning the hand, such as individual finger flexions, are encoded in the forearm FMG as characteristic force images that can be readily decoded for multifinger biomimetic control of robotic and virtual hands by amputees [1,[13][14][15][16]. To date, FMG is the only neuromuscular imaging modality that has demonstrated simultaneous multifunctional and multiple degrees-of-freedom control of prosthetic hands [13][14][15]17], including multifinger operation by amputees. Previous results with amputees suggested the potential of FMG as a register of force magnitude volition [13].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pressure signature of forearm as predictor of grip force

Wininger

Kim

Craelius

2008

JRRD

113

View full text Add to dashboard Cite

Abstract-We studied the relationship between grip force and external forearm pressure in nondisabled subjects using force myography (FMG). FMG uses a sensorized cuff surrounding the forearm to register the distributed mechanical force, detecting pressure on the sensors generated by the volumetric changes of the underlying musculo-tendinous complex. Each of nine nondisabled subjects donned the FMG cuff and applied grip forces to a cylindrical dynamometer; grip forces ranged from 0% to 100% of the subjects' maximum voluntary contraction. The cuff was positioned with seven force sensors located on both the anterior and posterior surfaces of the proximal forearm, but no attempt was made to match sensor placement with particular muscles or sites. Grip prediction was simply encoded as the rectified sum of the FMG sensor outputs. During grip and release cycles, the FMG waveforms of each subject correlated closely with his or her force waveforms (r > 0.89). FMG also correlated highly with the timing of grip onset and release (intraclass correlation coefficient (ICC(A,2)) = 0.99) and time to peak (ICC(A,2) = 0.91), with negligible lag. These results demonstrate that when applied to the forearm, FMG represents a grip force signature that may be useful for near-real-time proportional control of upper-limb prosthetic devices.

show abstract

Section: Force Myography As Control Modalitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Pressure signature of forearm as predictor of grip force

Wininger

Kim

Craelius

2008

JRRD

113

View full text Add to dashboard Cite

show abstract

“…The controllability is the responds to trend of designing prosthesis that easier to control by user, more than the design of more complex hands, having more degrees of freedom [10]. The controllability can be considered from several points of view such as from the point of view of patients and from the point of view of the controller.…”

Section: Gripper Functionalitymentioning

confidence: 99%

ANALYSIS of Control Force Grasping for a Multifunctional Five Fingered Robot to Pick-up Various of Components

Widhiada

Kumara

Nindhia

2016

MATEC Web of Conferences

View full text Add to dashboard Cite

Abstract. Multi-fingered robot gripper has become popular in the major research topics as grasping an object in robotic systems. The author considers a matter of style-based control model for a multi-fingered robot hand grasping an object with a known geometric characteristics. This paper introduces design process and analysis of contact force the five fingered gripper suitable to handle several of objects. The author applied Simulink/SimMechanics, Support package Arduino and Inventor software packages to facilatate and integrated the design of contact force gripper systems. The advance of PID control is used to control dynamics motions of the five fingered gripper systems. The multifunction finger's gripper is developed to handle the various components. Contact force between fingertips and object surface is computed using the Hooke law concept. The analysis of experiment result shows the optimum of contact forces are achieved to hold the object. The spring and damper algorithm is used to compute the interaction of force between fingertips and object surface.

show abstract

“…Overcoming this obstacle and developing the proper humanmachine interface requires knowing the capabilities of amputees to control a hand. Our previous work has shown that amputees can control simple flexion of multiple fingers (Abboudi, Glass, Newby, Flint, & Craelius, 1999;Phillips & Craelius, in press); however, little else is known about their residual potential and how to exploit it. This report extends our knowledge of the residual abilities of amputees by testing their control over a virtual hand.…”

Section: Introductionmentioning

confidence: 99%

Manipulation Practice for Upper-Limb Amputees Using Virtual Reality

Kuttuva

Burdea

Flint

et al. 2005

Presence: Teleoperators & Virtual Environments

View full text Add to dashboard Cite

We developed a novel interface that gives upper-limb amputees a virtual hand that can manipulate objects in a challenging environment. The interface registers specific myokinetic activity of the residual limbs, and encodes the intended voluntary movements that are then actualized as virtual hand motions. The composite myokinetic interface-virtual reality (MKI-VR) system consists of an array of pressure sensors mounted in an arm sleeve, sensors of elbow-and shoulder-joint angles, a trained filter derived from the pseudoinverse of a response matrix, and a virtual hand model, programmed in Java 3D. Users can manipulate virtual objects such as balls and pegs in a 3D training environment, while their performance at various difficulty levels is scored. In preliminary tests, upper-limb amputees readily gained the ability to grasp and release virtual objects. We propose the utility of the MKI-VR system both as an assessment tool for rehabilitation engineers, and as a motivator for amputees to exercise and thereby maintain their residual motor ability.

show abstract

A biomimetic controller for a multifinger prosthesis

Cited by 58 publications

References 17 publications

Pressure signature of forearm as predictor of grip force

Pressure signature of forearm as predictor of grip force

ANALYSIS of Control Force Grasping for a Multifunctional Five Fingered Robot to Pick-up Various of Components

Manipulation Practice for Upper-Limb Amputees Using Virtual Reality

Contact Info

Product

Resources

About