Evidence map›Paper›PMID 37840396›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2023

Hybrid Bionic Nerve Interface for Application in Bionic Limbs.

Youngjun Cho, Hyung Hwa Jeong, Heejae Shin, Changsik John Pak, Jeongmok Cho, Yongwoo Kim, Donggeon Kim, Taehyeon Kim, Hoijun Kim, Sohee Kim and 4 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Hybrid Bionic Nerve Interface for Application in Bionic Limbs.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 3 institutions in 1 country.

Youngjun ChoDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, 42899, South Korea.
Hyung Hwa JeongDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, University of Ulsan College of Medicine, 05505, Seoul, South Korea.
Heejae ShinDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, 42899, South Korea.
Changsik John PakDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, University of Ulsan College of Medicine, 05505, Seoul, South Korea.
Jeongmok ChoDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, University of Ulsan College of Medicine, 05505, Seoul, South Korea.
Yongwoo KimDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, 42899, South Korea.
Donggeon KimDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, University of Ulsan College of Medicine, 05505, Seoul, South Korea.
Taehyeon KimDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, University of Ulsan College of Medicine, 05505, Seoul, South Korea.
Hoijun KimGraduate School of Smart Convergence, Kwangwoon University, Seoul, 01897, South Korea.
Sohee KimDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, 42899, South Korea.
Soonchul KwonGraduate School of Smart Convergence, Kwangwoon University, Seoul, 01897, South Korea.
Joon Pio HongDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, University of Ulsan College of Medicine, 05505, Seoul, South Korea.
Hyunsuk Peter SuhDepartment of Plastic and Reconstructive Surgery, Asan Medical Center, University of Ulsan College of Medicine, 05505, Seoul, South Korea.
Sanghoon LeeDepartment of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, 42899, South Korea.ORCID 0000-0001-8989-6939
Ulsan College · KRDaegu Gyeongbuk Institute of Science and Technology · KRKwangwoon University · KR

Funding

Korea Medical Device Development Fund RS-2020-KD000196
6 · The paper itself

Abstract

Intuitive and perceptual neuroprosthetic systems require a high degree of neural control and a variety of sensory feedback, but reliable neural interfaces for long-term use that maintain their functionality are limited. Here, a novel hybrid bionic interface is presented, fabricated by integrating a biological interface (regenerative peripheral nerve interface (RPNI)) and a peripheral neural interface to enhance the neural interface performance between a nerve and bionic limbs. This interface utilizes a shape memory polymer buckle that can be easily implanted on a severed nerve and make contact with both the nerve and the muscle graft after RPNI formation. It is demonstrated that this interface can simultaneously record different signal information via the RPNI and the nerve, as well as stimulate them separately, inducing different responses. Furthermore, it is shown that this interface can record naturally evoked signals from a walking rabbit and use them to control a robotic leg. The long-term functionality and biocompatibility of this interface in rabbits are evaluated for up to 29 weeks, confirming its promising potential for enhancing prosthetic control.

Indexed as

BionicsPeripheral NervesAnimalsElectromyographyNerve RegenerationProstheses and ImplantsRabbitsneural interfaceneuroprostheticregenerative peripheral nerve interfacerobotic legshape memory polymer

Identifiers

PMID37840396
PMCPMC10724394
OpenAlexW4387661275

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.