ArticleFrontiers in physiology2022
3D Visual Tracking to Quantify Physical Contact Interactions in Human-to-Human Touch.
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.
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Who cites it
7 citing papers in PubMed.
- Emergent technologies in clinical neurophysiology to study the neuromuscular system: IFCN handbook chapter.Clinical neurophysiology practice · 2026Review
- Strain-based biomarkers at the skin surface differentiate asymmetries in soft tissue mobility associated with myofascial pain.Journal of the mechanical behavior of biomedical materials · 2025Article
- Strain-based biomarkers at the skin surface detect changes in soft tissue mobility linked to myofascial pain following soft tissue manipulation intervention.medRxiv : the preprint server for health sciences · 2025Article
- Article
- Evaluating the Physics and Repeatability of Human Brushers in Delivering Affective Touch.IEEE transactions on hapticsArticle
- Social and Emotional Touch Between Romantic Partners is Affectively More Pleasant Due to Finely Tuned Contact Interactions.IEEE transactions on hapticsArticle
- Mechanoreceptive Aβ primary afferents discriminate naturalistic social touch inputs at a functionally relevant time scale.IEEE transactions on affective computingArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
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.
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Registered trials
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