Cited by 197Prosthetics and Rehabilitation RoboticsMuscle activation and electromyography studiesStroke Rehabilitation and Recovery

EMG and EPP-integrated human-machine interface between the paralyzed and rehabilitation exoskeleton

Yin, Y. H., Fan, Y. J., Xu, L. D.·2012·IEEE Transactions on Information Technology in Biomedicine

Abstract

Although a lower extremity exoskeleton shows great prospect in the rehabilitation of the lower limb, it has not yet been widely applied to the clinical rehabilitation of the paralyzed. This is partly caused by insufficient information interactions between the paralyzed and existing exoskeleton that cannot meet the requirements of harmonious control. In this research, a bidirectional human-machine interface including a neurofuzzy controller and an extended physiological proprioception (EPP) feedback system is developed by imitating the biological closed-loop control system of human body. The neurofuzzy controller is built to decode human motion in advance by the fusion of the fuzzy electromyographic signals reflecting human motion intention and the precise proprioception providing joint angular feedback information. It transmits control information from human to exoskeleton, while the EPP feedback system based on haptic stimuli transmits motion information of the exoskeleton back to the human. Joint angle and torque information are transmitted in the form of air pressure to the human body. The real-time bidirectional human-machine interface can help a patient with lower limb paralysis to control the exoskeleton with his/her healthy side and simultaneously perceive motion on the paralyzed side by EPP. The interface rebuilds a closed-loop motion control system for paralyzed patients and realizes harmonious control of the human-machine system.

Integrity signals

Registry

Crossref · 10.1109/titb.2011.2178034

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • A human-machine interface between a paralyzed individual and rehabilitation exoskeleton was developed by Shanghai Jiao Tong University to help patients with lower limb paralysis.

    “a human–machine interface between a paralyzed individual and rehabilitation exoskeleton was developed by Shanghai Jiao Tong University (Shanghai, China) to help patients with lower limb paralysis [45].”

The citation lists haven’t been fetched yet

References 32 · Cited by 197

Authors
Yin, Y. H., Fan, Y. J., & Xu, L. D.
Affiliations
  • Shanghai Jiao Tong University (CN)
  • University of Science and Technology of China (CN)
Venue
IEEE Transactions on Information Technology in Biomedicine
Published
2012-07
Volume
16
Issue
4
Pages
542-549
ISSN
  • 1089-7771 (ISSN-L)
  • 1558-0032
OpenAlex
W2092623288
Cited by
197
References
32
Citations by year
2026: 2 · 2025: 3 · 2024: 13 · 2023: 8 · 2022: 12 · 2021: 9 · 2020: 16 · 2019: 12 · 2018: 19 · 2017: 10 · 2016: 16 · 2015: 14 · 2014: 22 · 2013: 23 · 2012: 18
FWCI
14.02
Type
journal article
Language
en
Open access
closed
Locations
  • IEEE Transactions on Information Technology in Biomedicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
  • Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
  • Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
Keywords
lower limb exoskeleton, paraplegia, human-machine interaction, electromyography, bidirectional control, haptic feedback, motor intention decoding, rehabilitation, closed-loop motion control
MeSH terms
Adult, Algorithms, Artificial Intelligence, Artificial Limbs, Electromyography, Humans, Male, Man-Machine Systems, Paraplegia, Proprioception, Robotics, Signal Processing, Computer-Assisted, User-Computer Interface, Neural Networks, Computer, Fuzzy Logic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review