Evidence map›Paper›PMID 42280942›Full record

ReviewSensors (Basel, Switzerland)2026

Wearable Multifunctional Sensors for Human Activity Recognition.

Lu Zhang, Yi Du, Haolong Li, Shiquan Yan, Quanxing Yao, Chunyu Liu, Yuejun Zhang, Xiaojian Zhu

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

8 authors.

Lu ZhangSchool of Materials Science and Chemical Engineering, Ningbo University, Ningbo 315211, China.
Yi DuNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
Haolong LiNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
Shiquan YanNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
Quanxing YaoNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
Chunyu LiuNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
Yuejun ZhangSchool of Materials Science and Chemical Engineering, Ningbo University, Ningbo 315211, China.ORCID 0000-0003-1132-6332
Xiaojian ZhuNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China.

Funding

Fundamental Research Funds for the Central Universities 20720230030Key Program of the National Natural Science Foundation of China 62433017National Key Research and Development Program of China 2023YFB3208600National Natural Science Foundation of China No. 62274140Xiaomi Young Talents Program/Xiaomi Foundation, and Shenzhen Science and Technology Program JCYJ20230807091401003
6 · The paper itself

Abstract

Driven by the profound convergence of the Internet of Things (IoT) and ubiquitous computing, wearable multifunctional sensors have emerged as a key technology for high-precision human activity recognition (HAR). Advancements in novel materials and flexible electronics have propelled the evolution of these sensors, enabling advances in decoupling heterogeneous signals, enhancing system robustness, and expanding environmental perception. This review systematically examines the frontier research on wearable multifunctional sensors for HAR. We provide an in-depth analysis of three core architectural design paradigms: architecture-level integration, which relies on physical spatial isolation for hardware-level signal decoupling; monolithic integration, which strives for extreme spatial compactness and spatiotemporal signal consistency; and the emerging intrinsically multifunctional design, which leverages novel stimuli-responsive materials for the intrinsic orthogonal discrimination of multidimensional signals. Furthermore, we delineate the diverse application scenarios of these highly integrated sensing platforms across medical rehabilitation, sports science, human-computer interaction (HCI), and daily behavior perception. Finally, this article discusses the critical challenges currently confronting this technology and outlines its future development prospects.

Indexed as

Biosensing TechniquesHuman ActivitiesWearable Electronic DevicesHumansflexible electronicshuman activity recognitionmultifunctional fusionsignal decouplingwearable sensors

Identifiers

PMID42280942
PMCPMC13259353

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.