{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T12:17:27Z","timestamp":1783426647483,"version":"3.54.6"},"reference-count":25,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T00:00:00Z","timestamp":1781654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>While emotions affect perception, their influence on physical interaction remains underexplored. This study investigated how the emotional valence of everyday objects manifests in hand kinematics during natural grasping.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Hand movements were recorded from 40 participants using an overhead smartphone camera (1080p; 30 fps), combined with MediaPipe and OpenCV. Participants were randomly assigned to either a Visual Modality (\n                      <jats:italic>n<\/jats:italic>\n                      = 20) or a Non-Visual Modality (\n                      <jats:italic>n<\/jats:italic>\n                      = 20) and were instructed to grasp five objects designed to evoke distinct emotional responses (fear, disgust, neutrality, and happiness). Kinematic measures, including grasping frame rate (frames\/s) and hand velocity (px\/frame), were extracted alongside self-reported emotional ratings.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Results revealed that motor behavior is not merely functional but emotionally reactive: threat-based objects (e.g., a spider) elicited significantly higher grasping frame rates, indicating more sustained interaction with these stimuli, potentially reflecting heightened monitoring or cautious engagement. A linear mixed-effects model identified a significant Modality \u00d7 Object interaction, indicating that visual access influenced object-related effects selectively rather than uniformly. Notably, these affect-related changes were captured in grasping frame rate (a temporal-density measure) rather than in hand velocity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>The emotional properties of objects systematically modulate motor behavior during grasping. These findings help bridge the gap between affect and physical action. They also show that consumer-grade smartphone technology can detect subtle variations in natural hand interaction, opening the door for affect-aware interfaces and scalable studies of motor-affective behavior in naturalistic environments.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpsyg.2026.1823532","type":"journal-article","created":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T05:52:07Z","timestamp":1781675527000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Emotional modulation of temporal density in natural grasping: a vision-based kinematic study"],"prefix":"10.3389","volume":"17","author":[{"given":"Hakki Egemen","family":"G\u00fclpinar","sequence":"first","affiliation":[{"name":"Department of Technology, Bielefeld University","place":["Bielefeld, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anastasiia","family":"Skryzhadlovska","sequence":"additional","affiliation":[{"name":"Department of Cognitive Neuroscience, Bielefeld University","place":["Bielefeld, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Haschke","sequence":"additional","affiliation":[{"name":"Department of Technology, Bielefeld University","place":["Bielefeld, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olga","family":"Abramov","sequence":"additional","affiliation":[{"name":"Department of Technology, Bielefeld University","place":["Bielefeld, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amir","family":"Jahanian Najafabadi","sequence":"additional","affiliation":[{"name":"Department of Technology, Bielefeld University","place":["Bielefeld, Germany"]},{"name":"Department of Cognitive Neuroscience, Bielefeld University","place":["Bielefeld, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,17]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2412.13187","article-title":"HandsOnVLM: vision-language models for hand-object interaction prediction","author":"Bao","year":"2024","journal-title":"arXiv [preprint]"},{"key":"B2","volume-title":"Statistical Power Analysis for the Behavioral Sciences, 2nd Edn.","author":"Cohen","year":"1988"},{"key":"B3","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1146\/annurev-control-060117-105043","article-title":"Haptics: the present and future of artificial touch sensation","volume":"1","author":"Culbertson","year":"2018","journal-title":"Annu. 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