Reliability and agreement of Azure Kinect and Kinect v2 depth sensors in the shoulder joint range of motion estimation
| Autor: | Umut Özsoy, Yılmaz Yıldırım, Sezen Karaşin, Rahime Şekerci, Lütfiye Bikem Süzen |
|---|---|
| Přispěvatelé: | 3475 [Süzen, Lütfiye Bikem], 56320355200 [Süzen, Lütfiye Bikem] |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Derinlik sensörleri
Digital analysis Shoulder Shoulder Joint Drinking Water Dijital analiz Marker-based motion analysis Depth sensors Reproducibility of Results General Medicine Poz tahmini Biomechanical Phenomena 3D motion capture Markerless motion analysis Humans Orthopedics and Sports Medicine Surgery Range of Motion Articular İşaretçi tabanlı hareket analizi 3D hareket yakalama Pose estimation İşaretsiz hareket analizi |
| Popis: | Background: Depth sensor–based motion analysis systems are of interest to researchers with low cost, fast analysis capabilities, and portability; thus, their reliability is a matter of interest. Our study examined the agreement and reliability in estimating the basic shoulder movements of Azure Kinect, Microsoft’s state-of-the-art depth sensor, and its predecessor, Kinect v2, by comparing them with the gold standard marker-based motion analysis system. Methods: In our study, the shoulder joint ranges of motion of 20 healthy individuals were analyzed during dominant-side flexion, abduction, and rotation movements. The reliability and agreement between methods were evaluated using the intraclass correlation co- efficient (ICC) and the Bland-Altman method. Results: Compared to the gold standard method, the old- and new-generation Kinect showed similar performance in terms of reliability in the estimation of flexion (ICC ¼ 0.86 vs. 0.82) and abduction (ICC ¼ 0.78 vs. 0.79) movements, respectively. In contrast, the new- generation sensor showed higher reliability than its predecessor in internal (ICC ¼ 0.49 vs. 0.75) and external rotation (ICC ¼ 0.38 vs. 0.67) movement. Conclusion: Compared to its predecessor, Kinect Azure has higher reliability in analyzing movements in a lower range and variability, thanks to its state-of-the-art hardware. However, the sensor should also be tested on multiaxial movements, such as combing hair, drink- ing water, and reaching back, which are the tasks that simulate extremity movements in daily life. No sponsor |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|