Evidence map›Paper›PMID 42236956›Full record

ArticleCommunications engineering2026

Single-Pixel Tactile Skin via compressive sampling.

Ariel Slepyan, Laura Xing, Rudy Zhang, Nitish Thakor

Abstract read
In one paragraph

Article in Communications engineering, 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.

Ariel Slepyan *Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA. aslepya1@jhu.edu.ORCID http://orcid.org/0009-0001-5265-7421
Laura Xing *Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Rudy Zhang *Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.
Nitish ThakorDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA. nitish@jhu.edu.ORCID http://orcid.org/0000-0002-9981-9395

Funding

National Science Foundation (NSF) 1830444U.S. Department of Defense (United States Department of Defense) W81XWH2010842
6 · The paper itself

Abstract

Large-area, high-speed tactile skins could improve robotics, prosthetics, and human-machine interfaces, but scaling them is limited by wiring complexity and readout bandwidth. We introduce Single-Pixel Tactile Skin (SPTS), a flexible, daisy-chainable tactile array that implements compressive sampling directly in hardware. Each sensing element uses a miniature low-cost microcontroller to apply programmable analog weights, while all pixel currents are summed into a single output channel. Repeating this process yields global projections from which tactile images are reconstructed using sparse recovery, reducing the measurements required relative to raster scanning. In a 10×10 array, SPTS achieved ≥98% object classification accuracy with 20 measurements, corresponding to an effective 3500 FPS, and captured an 8 ms projectile impact in 23 reconstructed frames. Because reconstruction quality improves progressively with measurement count, SPTS can rapidly localize contact from sparse data and refine tactile images over time, enabling scalable, responsive tactile sensing for physical interaction and control.

Identifiers

PMID42236956
PMCPMC13542120

What OpenQuestion holds

Textmetadata
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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.