Evidence map›Paper›PMID 42504483›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

1-D Collocated Dual-Gradient Sensory Fibers for Comprehensive Sensing and Decoding of Complex Human Motion and Physiology.

Yunheum Lee, Sungha Jeon, Min Kim, Joonhee Won, Jinwook Yeo, Kyunghyun Jo, Soyeon Lee, Kieun Park, Yechan Yang, Chul Kim and 4 more

Abstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yunheum LeeDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID https://orcid.org/0000-0002-3748-3136
Sungha JeonDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Min KimSchool of Computing, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of KoreaKorea.
Joonhee WonDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Jinwook YeoDepartment of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Kyunghyun JoProgram of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID https://orcid.org/0000-0002-0652-1515
Soyeon LeeSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Kieun ParkDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Yechan YangInterdisciplinary Program in Bioengineering, College of Engineering, Seoul National University, Seoul, Republic of Korea.
Chul KimDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID https://orcid.org/0000-0002-3882-6022
Gun-Hee LeeDepartments of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.ORCID https://orcid.org/0000-0003-4949-3355
Seunghwa RyuDepartment of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.ORCID https://orcid.org/0000-0001-9516-5809
Sungho JoSchool of Computing, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of KoreaKorea.
Seongjun ParkMedical Research Center, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-1981-9628

Funding

Boston-Korea Project RS-2024-00467213Ministry of Health and WelfareMinistry of Science and ICT, South KoreaNational Research Foundation of Korea RS-2023-00302489National Research Foundation of Korea RS-2026-25474579
6 · The paper itself

Abstract

Wearable interfaces that capture both weak physiological fluctuations and large body motions remain difficult to realize in a single fiber because most strain-sensing fibers are governed by one dominant electromechanical response mode. Consequently, mechanically distinct deformation regimes are ambiguously represented, limiting sensing range and information quality for downstream motion interpretation. Here, we develop a monolithic dual-gradient fiber with complementary sensing regimes programmed through coupled materials and process design. By jointly tuning the percolation behavior and rheological drawability of carbon black/carbon nanotube-filled styrene-ethylene-butylene-styrene (SEBS) composites, we identified two formulations suitable for coaxial co-drawing within one continuous strand. The resulting fiber pairs a highly responsive layer for small deformation with a robust layer that stays informative at larger strain, producing synchronized but nonredundant signals. At low strain (0%-10%), the high-sensitivity layer exhibits a gauge factor of 51.28, over four times the low-sensitivity layer (12.42), while the two layers remain functional up to approximately 40% and 160% strain, respectively. This architecture preserves mechanically salient features across distinct and superimposed inputs, supporting measurements from pulse and respiration to joint motion. In a single-fiber glove, the dual-sensitivity design improves gesture-classification accuracy by more than 10% relative to single-sensitivity controls, enriching features for decoding.

Indexed as

Wearable Electronic DevicesHumansMovementNanotubes, CarbonSootNanotubes, CarbonSootartificial sensationscomprehensive sensory processingdual‐gradient deep learning decodingfiber sensorstretchable electronics decoding

Identifiers

PMID42504483
PMCPMC13591664

What OpenQuestion holds

Textmetadata
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Registered trials

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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.