Evidence map›Paper›PMID 42301576›Full record

ReviewNano-micro letters2026

Triboelectric Wearable Sensors for Human-Centric Smart Electronics: From Self-Powered Sensing to Artificial Intelligence-Assisted Human-Machine Interface Systems.

Yoonsang Ra, Sumin Cho, Xinge Guo, Dongwhi Choi, Chengkuo Lee

Abstract readReview
In one paragraph

Review in Nano-micro letters, 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

5 authors.

Yoonsang Ra *Department of Mechanical Engineering (Integrated Engineering Program), Kyung Hee University, 1732 Deogyeong-daero, Yongin, Gyeonggi, 17104, Republic of Korea.
Sumin Cho *Department of Mechanical Engineering (Integrated Engineering Program), Kyung Hee University, 1732 Deogyeong-daero, Yongin, Gyeonggi, 17104, Republic of Korea.
Xinge GuoDepartment of Electrical & Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117576, Singapore.
Dongwhi ChoiDepartment of Mechanical Engineering (Integrated Engineering Program), Kyung Hee University, 1732 Deogyeong-daero, Yongin, Gyeonggi, 17104, Republic of Korea. dongwhi.choi@khu.ac.kr.
Chengkuo LeeDepartment of Electrical & Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117576, Singapore. elelc@nus.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As intelligent electronics become increasingly integrated into daily life, health care, virtual interaction, and assistive systems, human-machine interfaces (HMIs) require sensing platforms that are not only wearable and self-powered but also capable of translating human signals into adaptive machine functions. Triboelectric wearable sensors are particularly attractive in this regard because they directly transduce human-generated mechanical stimuli, provide broad material and structural design freedom, and are readily adaptable to body-interfaced formats. In this review, wearability refers to body-mounted, skin-interfaced, textile-integrated, or otherwise human-attached triboelectric sensing platforms, whereas human-centric smart electronics refers to downstream electronic systems that remain functionally anchored to human-originated sensing, interpretation, feedback, or control. From this perspective, we review triboelectric wearable sensors from fundamentals to applications, covering working principles, material selection, device architectures, and fabrication strategies. We further discuss artificial intelligence-assisted signal processing, triboelectric artificial synapses, and neuromorphic computing as key bridges from self-powered sensing to intelligent HMI. Representative application spaces, including health care, gesture recognition, device control, immersive virtual interaction, wearable-to-robotic extensions, and intelligent transportation are discussed only when wearable triboelectric sensing serves as the primary human-input interface. Finally, the remaining challenges and future directions toward next-generation human-centric smart electronics are outlined.

Indexed as

Artificial intelligenceHuman–machine interfaceSmart electronicsTriboelectric nanogeneratorWearable sensor

Identifiers

PMID42301576
PMCPMC13272748

What OpenQuestion holds

Textmetadata
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.