A Mobile Application Program that Configures Right-Left Hand Recognition According to the Degree of Mental Rotation Difficulty
| dc.contributor.author | Dilek, Burcu | |
| dc.contributor.author | Tavli, Elif Yaren | |
| dc.contributor.author | Yilmaz, Emre | |
| dc.contributor.author | Yasar, Eray | |
| dc.contributor.author | Ocal, Tugsad | |
| dc.contributor.author | Cetinkaya, Okkes | |
| dc.contributor.author | Akbas, Senanur | |
| dc.date.accessioned | 2025-10-29T11:13:57Z | |
| dc.date.issued | 2024 | |
| dc.department | Gebze Teknik Üniversitesi | |
| dc.description | 2024 Medical Technologies Congress -- OCT 10-12, 2024 -- Bodrum, TURKIYE | |
| dc.description.abstract | Right-left discrimination is evaluated with hand lateralization and accepted as a criterion of body recognition. In this study, a mobile application assessment method was developed in which the right-left discrimination was categorized within the concept of mental rotation. The objective was to elucidate the variations in users' responses to hand images presented at varying degrees of rotation. Participants' accuracy rates, reaction times, and test completion times were compared across the different difficulty levels in the mobile application. The findings revealed that as the task progressed from easier to more challenging categories, the accuracy rate declined, while both reaction time and test completion time increased. Assessing hand lateralization by presenting a software program where mental rotation tasks are categorized from easy to difficult may guide clinicians to follow the individuals' performance. As a result, clinicians may have a chance to assess their patients' potential on this performance and to integrate them to a particular therapeutic training program. | |
| dc.description.sponsorship | Izmir Ekonomi Universitesi | |
| dc.description.sponsorship | Scientific and Technological Research Council of Turkiye (TUBITAK) [222S133] | |
| dc.description.sponsorship | TUBITAK | |
| dc.description.sponsorship | This study was supported by Scientific and Technological Research Council of Turkiye (TUBITAK) under Grant Number 222S133. The authors thank TUBITAK for their Support. | |
| dc.identifier.doi | 10.1109/TIPTEKNO63488.2024.10755311 | |
| dc.identifier.isbn | 979-8-3315-2981-9 | |
| dc.identifier.isbn | 979-8-3315-2982-6 | |
| dc.identifier.issn | 2687-7775 | |
| dc.identifier.uri | https://doi.org/10.1109/TIPTEKNO63488.2024.10755311 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14854/7000 | |
| dc.identifier.wos | WOS:001454367500026 | |
| dc.identifier.wosquality | N/A | |
| dc.indekslendigikaynak | Web of Science | |
| dc.language.iso | en | |
| dc.publisher | IEEE | |
| dc.relation.ispartof | 2024 Medical Technologies Congress, Tiptekno | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_WOS_20251020 | |
| dc.subject | right-left discrimination | |
| dc.subject | laterality judgment | |
| dc.subject | body image | |
| dc.subject | body recognition | |
| dc.title | A Mobile Application Program that Configures Right-Left Hand Recognition According to the Degree of Mental Rotation Difficulty | |
| dc.type | Conference Object |








