The development of neural interfaces to provide improved control and somatosensory feedback from prosthetic limbs has initiated a new ability to probe the various dimensions of embodiment. Scientists in the field of neuroprosthetics require dependable measures of ownership, body representation, and agency to quantify the sense of embodiment felt by patients for their prosthetic limbs. These measures are critical to perform generalizable experiments and compare the utility of the new technologies being developed.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
November 2021
Multiarticulate bionic hands are now capable of recreating the endogenous movements and grip patterns of the human hand, yet amputees continue to be dissatisfied with existing control strategies. One approach towards more dexterous and intuitive control is to create a semi-autonomous bionic hand that can synergistically aid a human with complex tasks. To that end, we have developed a bionic hand that can automatically detect and grasp nearby objects with minimal force using multi-modal fingertip sensors.
View Article and Find Full Text PDFObjective: A current biomedical engineering challenge is the development of a system that allows fluid control of multi-functional prosthetic devices through a human-machine interface. Here we probe this challenge by studying two subjects with trans-radial limb loss as they control a virtual hand and wrist system using 6 or 8 chronically implanted intramuscular electromyographic (iEMG) signals. The subjects successfully controlled a 4, 5, and 6 Degrees of Freedom (DoF's) virtual hand and wrist systems to perform a target matching task.
View Article and Find Full Text PDFIntroduction: People with partial hand loss represent the largest population of upper limb amputees by a factor of 10. The available prosthetic componentry for people with digit loss provide various methods of control, kinematic designs, and functional abilities. Here, the Point Digit II is empirically tested and a discussion is provided comparing the Point Digit II with the existing commercially available prosthetic fingers.
View Article and Find Full Text PDFBackground: The bottleneck in upper limb prosthetic design is the myoelectric control algorithm. Here we studied the clinical readiness of the myoelectric postural control algorithm in a laboratory setting with two trans-radial amputees using a commercially available prosthetic limb system.
Technique: The postural control algorithm was integrated into prosthetic limb systems using standard of care components.
Multiple sources of sensory information are combined to develop hand posture percepts in the intact system, but the combination of multiple artificial somatosensory percepts by human prosthesis users has not been studied. Here, we report on a case study in which a person with transradial amputation identified prosthetic hand postures using artificial somatosensory feedback. He successfully combined five artificial somatosensory percepts to achieve above-chance performance of 95.
View Article and Find Full Text PDFImproved neural interfacing strategies are needed for the full articulation of advanced prostheses. To address limitations of existing control interface designs, the work of our laboratory has presented an optical approach to reading activity from individual nerve fibers using activity-dependent calcium transients. Here, we demonstrate the feasibility of such signals to control prosthesis actuation by using the axonal fluorescence signal in an ex vivo mouse nerve to drive a prosthetic digit in real-time.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
June 2017
The functional assessment of myoelectric control algorithms by persons with amputation promotes the overarching goal of the field of prosthetic limb design: to replace what was lost. However, many studies use experimental paradigms with virtual interfaces and able-bodied subjects that do not capture the challenges of a clinical implementation with an amputee population. A myoelectric control system must be robust to variable physiology, loading effects of the prosthesis on the limb, and limb position effects during dynamic tasks.
View Article and Find Full Text PDFThe myoelectric controller (MEC) remains a technological bottleneck in the development of multifunctional prosthetic hands. Current MECs require physiologically inappropriate commands to indicate intent and lack effectiveness in a clinical setting. Postural control schemes use surface electromyography signals to drive a cursor in a continuous two-dimensional domain that is then transformed into a hand posture.
View Article and Find Full Text PDFProviding functionally effective sensory feedback to users of prosthetics is a largely unsolved challenge. Traditional solutions require high band-widths for providing feedback for the control of manipulation and yet have been largely unsuccessful. In this study, we have explored a strategy that relies on temporally discrete sensory feedback that is technically simple to provide.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
July 2014
Restoring dexterous motor function equivalent to that of the human hand after amputation is one of the major goals in rehabilitation engineering. To achieve this requires the implementation of a effortless human-machine interface that bridges the artificial hand to the sources of volition. Attempts to tap into the neural signals and to use them as control inputs for neuroprostheses range in invasiveness and hierarchical location in the neuromuscular system.
View Article and Find Full Text PDFA myoelectric controller should provide an intuitive and effective human-machine interface that deciphers user intent in real-time and is robust enough to operate in daily life. Many myoelectric control architectures have been developed, including pattern recognition systems, finite state machines, and more recently, postural control schemes. Here, we present a comparative study of two types of finite state machines and a postural control scheme using both virtual and physical assessment procedures with seven nondisabled subjects.
View Article and Find Full Text PDFIn this article, we set forth a detailed analysis of the mechanical characteristics of anthropomorphic prosthetic hands. We report on an empirical study concerning the performance of several commercially available myoelectric prosthetic hands, including the Vincent, iLimb, iLimb Pulse, Bebionic, Bebionic v2, and Michelangelo hands. We investigated the finger design and kinematics, mechanical joint coupling, and actuation methods of these commercial prosthetic hands.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
March 2014
An ideal myoelectric prosthetic hand should have the ability to continuously morph between any posture like an anatomical hand. This paper describes the design and validation of a morphing myoelectric hand controller based on principal component analysis of human grasping. The controller commands continuously morphing hand postures including functional grasps using between two and four surface electromyography (EMG) electrodes pairs.
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