Literature DB >> 29629874

Object discrimination using electrotactile feedback.

Tapas J Arakeri1, Brady A Hasse, Andrew J Fuglevand.   

Abstract

OBJECTIVE: A variety of bioengineering systems are being developed to restore tactile sensations in individuals who have lost somatosensory feedback because of spinal cord injury, stroke, or amputation. These systems typically detect tactile force with sensors placed on an insensate hand (or prosthetic hand in the case of amputees) and deliver touch information by electrically or mechanically stimulating sensate skin above the site of injury. Successful object manipulation, however, also requires proprioceptive feedback representing the configuration and movements of the hand and digits. APPROACH: Therefore, we developed a simple system that simultaneously provides information about tactile grip force and hand aperture using current amplitude-modulated electrotactile feedback. We evaluated the utility of this system by testing the ability of eight healthy human subjects to distinguish among 27 objects of varying sizes, weights, and compliances based entirely on electrotactile feedback. The feedback was modulated by grip-force and hand-aperture sensors placed on the hand of an experimenter (not visible to the subject) grasping and lifting the test objects. We were also interested to determine the degree to which subjects could learn to use such feedback when tested over five consecutive sessions. MAIN
RESULTS: The average percentage correct identifications on day 1 (28.5%  ±  8.2% correct) was well above chance (3.7%) and increased significantly with training to 49.2%  ±  10.6% on day 5. Furthermore, this training transferred reasonably well to a set of novel objects. SIGNIFICANCE: These results suggest that simple, non-invasive methods can provide useful multisensory feedback that might prove beneficial in improving the control over prosthetic limbs.

Entities:  

Mesh:

Year:  2018        PMID: 29629874      PMCID: PMC6331001          DOI: 10.1088/1741-2552/aabc9a

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


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4.  Multichannel Electrotactile Feedback With Spatial and Mixed Coding for Closed-Loop Control of Grasping Force in Hand Prostheses.

Authors:  Strahinja Dosen; Marko Markovic; Matija Strbac; Minja Belic; Vladimir Kojic; Goran Bijelic; Thierry Keller; Dario Farina
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2016-04-07       Impact factor: 3.802

5.  Electrocutaneous stimulation for sensory communication in rehabilitation engineering.

Authors:  A Y Szeto; F A Saunders
Journal:  IEEE Trans Biomed Eng       Date:  1982-04       Impact factor: 4.538

6.  Comparison of codes for sensory feedback using electrocutaneous tracking.

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Journal:  Ann Biomed Eng       Date:  1977-12       Impact factor: 3.934

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  8 in total

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