Evidence map›Paper›PMID 42796170›Full record

ReviewMicromachines2026

Soft Mechanical Inductive Sensors: Principles, Design, and Applications.

Muhammad Awais, Gayatri Indukumar, Diana Cafiso, Lucia Beccai

Abstract readReview
In one paragraph

Review in Micromachines, 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

4 authors.

Muhammad AwaisSoft BioRobotics Perception Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy.ORCID 0009-0001-1885-5790
Gayatri IndukumarSoft BioRobotics Perception Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy.ORCID 0009-0007-8577-3932
Diana CafisoSoft BioRobotics Perception Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy.ORCID 0000-0003-3038-7632
Lucia BeccaiSoft BioRobotics Perception Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy.ORCID 0000-0002-8754-5155

Funding

European Commission 101069536
6 · The paper itself

Abstract

Soft mechanical inductive (SMI) sensors are emerging as a promising solution for advanced robotics, healthcare, and wearable devices, offering high precision, adaptability, and environmental robustness. These sensors leverage coil-based designs to achieve resilience against temperature variations, humidity, and mechanical wear, making them suitable for long-term operation in challenging environments. Existing reviews tend to focus narrowly on specific applications of coil-based inductive sensors, such as soft-robotic tactile sensing or biomedical devices, without systematically comparing design methodologies, fabrication techniques, or broader use cases, thereby lacking a unified perspective on the field. This review addresses this gap by analyzing recent developments in SMI sensors from theoretical concepts and practical design to their use cases. The review focuses on the working principles, design strategies, fabrication techniques, electronic interfaces, and, finally, the applications of coil-based SMI sensors. Key applications in soft robotics, prosthetics, and haptic devices are examined, highlighting the transformative potential of these sensors across diverse domains. Finally, the review discusses critical challenges, including sensitivity optimization, durability, and environmental interference, and outlines future directions to further advance this promising technology.

Indexed as

angle sensorsbiomedical applicationscoil designcomplementary metal-oxide-semiconductor (CMOS) fabricationprinted circuit board (PCB) fabricationproprioceptionsoft lithographysoft mechanical inductive sensorssoft robotics

Identifiers

PMID42796170
PMCPMC13609018

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.