3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch
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 measuremen...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Physiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphys.2022.841938/full |
| _version_ | 1817969083948204032 |
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| author | Shan Xu Chang Xu Sarah McIntyre Håkan Olausson Gregory J. Gerling |
| author_facet | Shan Xu Chang Xu Sarah McIntyre Håkan Olausson Gregory J. Gerling |
| author_sort | Shan Xu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T20:16:55Z |
| format | Article |
| id | doaj.art-f2cb7a6ceaa94e18b2121f34adf9e1df |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-04-13T20:16:55Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-f2cb7a6ceaa94e18b2121f34adf9e1df2022-12-22T02:31:41ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2022-06-011310.3389/fphys.2022.8419388419383D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human TouchShan Xu0Chang Xu1Sarah McIntyre2Håkan Olausson3Gregory J. Gerling4School of Engineering and Applied Science, University of Virginia, Charlottesville, VA, United StatesSchool of Engineering and Applied Science, University of Virginia, Charlottesville, VA, United StatesCenter for Social and Affective Neuroscience (CSAN), Linköping University, Linköping, SwedenCenter for Social and Affective Neuroscience (CSAN), Linköping University, Linköping, SwedenSchool of Engineering and Applied Science, University of Virginia, Charlottesville, VA, United StatesAcross 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.https://www.frontiersin.org/articles/10.3389/fphys.2022.841938/fulltouchsocial touchhapticsvisual trackingtactile mechanicshuman performance |
| spellingShingle | Shan Xu Chang Xu Sarah McIntyre Håkan Olausson Gregory J. Gerling 3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch Frontiers in Physiology touch social touch haptics visual tracking tactile mechanics human performance |
| title | 3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch |
| title_full | 3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch |
| title_fullStr | 3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch |
| title_full_unstemmed | 3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch |
| title_short | 3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch |
| title_sort | 3d visual tracking to quantify physical contact interactions in human to human touch |
| topic | touch social touch haptics visual tracking tactile mechanics human performance |
| url | https://www.frontiersin.org/articles/10.3389/fphys.2022.841938/full |
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