Evidence map›Paper›PMID 35755449›Full record

ArticleFrontiers in physiology2022

3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch.

Shan Xu, Chang Xu, Sarah McIntyre, Håkan Olausson, Gregory J Gerling

Abstract read
In one paragraph

Article in Frontiers in physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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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.

Shan XuSchool of Engineering and Applied Science, University of Virginia, Charlottesville, VA, United States.
Chang XuSchool of Engineering and Applied Science, University of Virginia, Charlottesville, VA, United States.
Sarah McIntyreCenter for Social and Affective Neuroscience (CSAN), Linköping University, Linköping, Sweden.
Håkan OlaussonCenter for Social and Affective Neuroscience (CSAN), Linköping University, Linköping, Sweden.
Gregory J GerlingSchool of Engineering and Applied Science, University of Virginia, Charlottesville, VA, United States.

Funding

CRCNS: Neural Representations of Object Compliance in the Periphery R01NS105241 · NINDS · UNIVERSITY OF VIRGINIA · PI GERLING, GREGORY JOHN, LUMPKIN, ELLEN A · 2017 to 2019
$990k
NINDS NIH HHS R01 NS105241
6 · The paper itself

Abstract

Across a plethora of social situations, we touch others in natural and intuitive ways to share thoughts and emotions, such as tapping to get one's attention or caressing to soothe one's anxiety. A deeper understanding of these human-to-human interactions will require, in part, the precise measurement of skin-to-skin physical contact. Among prior efforts, each measurement approach exhibits certain constraints, e.g., motion trackers do not capture the precise shape of skin surfaces, while pressure sensors impede skin-to-skin contact. In contrast, this work develops an interference-free 3D visual tracking system using a depth camera to measure the contact attributes between the bare hand of a toucher and the forearm of a receiver. The toucher's hand is tracked as a posed and positioned mesh by fitting a hand model to detected 3D hand joints, whereas a receiver's forearm is extracted as a 3D surface updated upon repeated skin contact. Based on a contact model involving point clouds, the spatiotemporal changes of hand-to-forearm contact are decomposed as six, high-resolution, time-series contact attributes, i.e., contact area, indentation depth, absolute velocity, and three orthogonal velocity components, together with contact duration. To examine the system's capabilities and limitations, two types of experiments were performed. First, to evaluate its ability to discern human touches, one person delivered cued social messages, e.g., happiness, anger, sympathy, to another person using their preferred gestures. The results indicated that messages and gestures, as well as the identities of the touchers, were readily discerned from their contact attributes. Second, the system's spatiotemporal accuracy was validated against measurements from independent devices, including an electromagnetic motion tracker, sensorized pressure mat, and laser displacement sensor. While validated here in the context of social communication, this system is extendable to human touch interactions such as maternal care of infants and massage therapy.

Indexed as

emotion communicationhapticshuman performancesocial touchtactile mechanicstouchvisual tracking

Identifiers

PMID35755449
PMCPMC9219726

What OpenQuestion holds

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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.