Development, reliability, and concurrent validity of the virtual box and block test for manual dexterity and kinematic analysis in stroke patients and healthy adults.

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Title: Development, reliability, and concurrent validity of the virtual box and block test for manual dexterity and kinematic analysis in stroke patients and healthy adults.
Authors: Kim, Subok1 (AUTHOR), Kim, Sunmin2 (AUTHOR), Jang, Sanghun3 (AUTHOR), Lee, Onseok1,4 (AUTHOR) leeos@sch.ac.kr
Source: Virtual Reality. Jun2026, Vol. 30 Issue 2, p1-13. 13p.
Subjects: Kinematics, Test validity, Three-dimensional imaging, Motion capture (Human mechanics), Statistical reliability, Motor ability, Stroke patients
Abstract: We developed a hand kinematics analysis method for manual dexterity in post-stroke patients, utilizing real-time tracking and three-dimensional (3D) visualization of movement performance through a virtual box and block test (BBT) with a leap motion controller; additionally, we validated its reliability and concurrent validity to propose it as a valuable evaluation tool. We performed virtual-BBT for 1 min in a stroke patient group (SPG, n = 15) and a healthy adult group (HAG, n = 15). Virtual-BBT was tracked in real time, and cubes were counted by holding the virtual cube and performing hand movements. The test–retest reliability by number of trials showed significant correlation in the SPG (less paretic: intraclass correlation coefficient (ICC) = 0.582, 95% confidence interval (CI) [0.104–0.839], p < 0.01; more paretic: ICC = 0.634, 95% CI [0.191–0.861], p < 0.001) and in the HAG (dominant: ICC = 0.605, 95% CI [0.134–0.851], p < 0.01; non-dominant: ICC = 0.739, 95% CI [0.379–0.904], p < 0.01). The concurrent validity of virtual and real-BBT showed large correlation for less paretic (r = 0.76, p < 0.001) and paretic (r = 0.86, p < 0.001) hands in the SPG. The dominant (r = 0.73, p = 0.002) and non-dominant (r = 0.75, p < 0.001) hands in the HAG showed large correlation. Virtual-BBT analyzes manual dexterity characteristics in 3D by holding a virtual cube and tracking movement performance, and reduces the subjectivity of classical evaluation. [ABSTRACT FROM AUTHOR]
Copyright of Virtual Reality is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Development, reliability, and concurrent validity of the virtual box and block test for manual dexterity and kinematic analysis in stroke patients and healthy adults.
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22Virtual+Reality%22&quot;&gt;Virtual Reality&lt;/searchLink&gt;. Jun2026, Vol. 30 Issue 2, p1-13. 13p.
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  Data: We developed a hand kinematics analysis method for manual dexterity in post-stroke patients, utilizing real-time tracking and three-dimensional (3D) visualization of movement performance through a virtual box and block test (BBT) with a leap motion controller; additionally, we validated its reliability and concurrent validity to propose it as a valuable evaluation tool. We performed virtual-BBT for 1 min in a stroke patient group (SPG, n = 15) and a healthy adult group (HAG, n = 15). Virtual-BBT was tracked in real time, and cubes were counted by holding the virtual cube and performing hand movements. The test–retest reliability by number of trials showed significant correlation in the SPG (less paretic: intraclass correlation coefficient (ICC) = 0.582, 95% confidence interval (CI) [0.104–0.839], p &lt; 0.01; more paretic: ICC = 0.634, 95% CI [0.191–0.861], p &lt; 0.001) and in the HAG (dominant: ICC = 0.605, 95% CI [0.134–0.851], p &lt; 0.01; non-dominant: ICC = 0.739, 95% CI [0.379–0.904], p &lt; 0.01). The concurrent validity of virtual and real-BBT showed large correlation for less paretic (r = 0.76, p &lt; 0.001) and paretic (r = 0.86, p &lt; 0.001) hands in the SPG. The dominant (r = 0.73, p = 0.002) and non-dominant (r = 0.75, p &lt; 0.001) hands in the HAG showed large correlation. Virtual-BBT analyzes manual dexterity characteristics in 3D by holding a virtual cube and tracking movement performance, and reduces the subjectivity of classical evaluation. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Virtual Reality is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1007/s10055-026-01329-y
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      – Code: eng
        Text: English
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        PageCount: 13
        StartPage: 1
    Subjects:
      – SubjectFull: Kinematics
        Type: general
      – SubjectFull: Test validity
        Type: general
      – SubjectFull: Three-dimensional imaging
        Type: general
      – SubjectFull: Motion capture (Human mechanics)
        Type: general
      – SubjectFull: Statistical reliability
        Type: general
      – SubjectFull: Motor ability
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      – SubjectFull: Stroke patients
        Type: general
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      – TitleFull: Development, reliability, and concurrent validity of the virtual box and block test for manual dexterity and kinematic analysis in stroke patients and healthy adults.
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            NameFull: Kim, Subok
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            NameFull: Kim, Sunmin
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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