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Microsoft Kinect V2 tabanlı yenilikçi bir yöntem ile ROM ölçümlerine ait geçerlilik ve güvenirlik çalışması

Year 2018, Volume: 24 Issue: 5, 915 - 920, 12.10.2018

Abstract

Hareket
aralığı ölçümü fizik tedavinin ilk aşamasını oluşturmaktadır. Bu çalışmada,
derinlik bilgisi veren bir kamera türü olan Kinect V2 kullanılarak yeni bir
hareket aralığı ölçüm yöntemi önerilmiştir. İlgili uzva renkli işaretçiler
yapıştırılıp bu işaretçilerin her birinin ağırlık merkezine ait kamera merkezli
üç boyutlu dünya koordinatları bulunmuştur. Bu koordinatlar kullanılarak eklem
açıları ve hareket aralığı ölçülmüştür. Yöntemin geçerlilik ve güvenirliğini
test etmek amacıyla 10 katılımcının sağ ve sol dirsek açıları standart
gönyometre ve Kinect ile ayrı ayrı ölçülmüştür. Gözlemci içi güvenirliklerin
test edilmesi için ölçümler üç oturumda her biri en az 10 yıl tecrübeli üç
fizik tedavi uzmanı ve Kinect ile alınmıştır.  Güvenirlik analizlerinde
ölçümlere ait sınıf içi korelasyon katsayısı (ICC), Ölçüm standart hatası (SEM)
ve tespit edilebilir minimal değişim (MDC) hesaplanmıştır. Cihaz ile yapılan
ölçümlerin mutlak doğruluğunu gözlemlemek için gönyometre üzerine işaretçiler
yapıştırılıp dört farklı açıya (45, 90, 135 ve 180°) ayarlanarak altışar
oturumda ölçüm alınmıştır.  Her bir açı ve oturum için ölçümlere ait
ortalama, standart sapma, ortalama karesel hata (RMSE) ve karar sınırları (LOA)
bulunmuştur. Mutlak doğruluk için yapılan ölçümlerde kullanılan yöntemin 1-3°
hata payı ve 1° altında
standart sapması olduğu görülmüştür. Fizik tedavi uzmanlarının yaptığı
ölçümlerde sağ ve sol kol için sınıf içi korelasyon katsayıları sırasıyla 0.78
ve 0.81 olarak bulunurken bu değerler Kinect için 0.94 ve 0.93
olarak elde edilmiştir. Bu çalışmada önerilen yöntemin
yapılan analizler sonrası geçerli ve güvenilir olduğu anlaşılıp klinik
uygulamalarda kullanılabileceği görülmüştür.

References

  • Nussbaumer S, Leunig M, Glatthorn JF, Stauffacher S, Gerber H, Maffiuletti NA. “Validity and test-retest reliability of manual goniometers for measuring passive hip range of motion in femoroacetabular impingement patients”. BMC Musculoskeletal Disorder, 11(194), 2-11, 2010.
  • Gajdosik RL, Bohannon RW. “Clinical measurement of range of motion. Review of goniometry emphasizing reliability and validity”. Physical Therapy, 67(12), 1867-72, 1987.
  • Zhou H, Hu H. “Human motion tracking for rehabilitation-a survey”. Biomedical Signal Processing and Control, 3(1), 1-18, 2008.
  • Morris RG, Lawson SEM. “A review and evaluation of available gait analysis technologies and their potential for the measurement of impact transmission”. 2010.
  • Huber M, Seitz AL, Leeser M, Sternad D. “Validity and reliability of Kinect skeleton for measuring shoulder joint angles: a feasibility study”. Physiotherapy, 101(4), 389–393, 2015.
  • Bo APL, Hayashibe M, Poignet P. “Joint angle estimation in rehabilitation with inertial sensors and its integration with kinect”. 33rd Annual International Conference of the IEEE EMBS, Boston, Massachustts, USA, 30 August-03 September 2011.
  • Choppin SB, Lane B, Wheat JS. “The accuracy of the Microsoft Kinect in joint angle measurement”. Sports Technology, 7(1-2), 98-105, 2014.
  • Schmitz A, Boggess MY, Shapiro GR, Yang R, Noehren B. “The measurement of in vivo joint angles during a squat using a single camera markerless motion capture system as compared to a marker based system”. Gait Posture, 41(2), 694–698, 2015.
  • Schmitz A, Ye M, Shapiro R, Yang R, Noehren B. “Accuracy and repeatability of joint angles measured using a single camera markerless motion capture system”. Journal of Biomechanics, 47(2), 587-591, 2014.
  • Milani P, Coccetta CA, Rabini A, Sciarra T, Massazza G, Ferriero G. “Mobile smartphone applications for body position measurement in rehabilitation: a review of goniometric tools”. PM&R, 6(11), 1038-1043, 2014.
  • Mourcou Q, Fleury A, Diot B, Franco C, Vuillerme N. “Mobile phone-based joint angle measurement for functional assessment and rehabilitation of proprioception”. BioMed Research International, 2015, 1-15, 2015.
  • Quek J, Brauer SG, Treleaven J, Pua YH, Mentiplay B, Clark RA. “Validity and intra-rater reliability of an android phone application to measure cervical range-of-motion”. Journal of neuroengineering and rehabilitation, 11(1), 65, 2014.
  • Stone E, Skubic M. “Evaluation of an ınexpensive depth camera for passive ın-home fall risk assessment”. 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, Dublin, Ireland, 23-26 May 2011.
  • Stone EE, Skubic M. “Passive in-home measurement of stride-to-stride gait variability comparing vision and Kinect sensing”. 33rd Annual International Conference of the IEEE EMBS, Boston, Massachusetts, USA, 30 August-3 September 2011.
  • Gabel M, Gilad-Bachrach R, Renshaw E, Schuster A. “Full body gait analysis with kinect”. 34th Annual International Conference of the IEEE EMBS, San Diego, California, USA, 28 August - 01 September 2012.
  • Destelle F, Ahmadi A, O'Connor NE, Moran K, Chatzitofis A, Zarpalas D, Daras P. "Low-cost accurate skeleton tracking based on fusion of kinect and wearable inertial sensors". 22nd European Signal Processing Conference (EUSIPCO), Lisbon, Portugal, 1-5 September 2014.
  • Otman, SA, Demirel H, Sade A. Tedavi Hareketlerinde Temel Değerlendirme Prensipleri, 2. Baskı, Ankara, Türkiye, Hacettepe Üniversitesi Fizik Tedavi ve Rehabilitasyon Yayınları, 1998.
  • Corti A, et al. "A metrological characterization of the Kinect V2 time-of-flight camera". Robotics and Autonomous Systems, 75, 584-594, 2015.
  • Khoshelham K, Sander OE. "Accuracy and resolution of kinect depth data for indoor mapping applications". Sensors, 12(2), 1437-1454, 2015.
  • Landis JR, Gary GK. "The measurement of observer agreement for categorical data". Biometrics, 33(1), 159-174, 1977.
  • Zaki R, Bulgiba A, Ismail R, Ismail NA. “Statistical methods used to test for agreement of medical instruments measuring continuous variables in method comparison studies: a systematic review”. PloS one, 7(5), 37908, 2012.
  • Li L, Zeng L, Lin ZJ, Cazzell M, Liu H. “Tutorial on use of intraclass correlation coefficients for assessing intertest reliability and its application in functional near-infrared spectroscopy-based brain imaging". Journal of Biomedical Optics, 20(5), 050801-050801, 2015.
  • Fernandez R, Fernandez G. “Validating the bland-altman method of agreement”. Annual Conference of Western Users of SAS Software, San Jose, USA, 2009.
  • De Vet HC, Terwee CB, Mokkink LB, Knol DL. Measurement in Medicine: A Practical Guide. New York, USA, Cambridge University Press, 2011
  • Khoshelham K. "Accuracy analysis of kinect depth data". International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences, 38(5), 133-138, 2012.

Reliability and validity of an innovative method of ROM measurement using Microsoft Kinect V2

Year 2018, Volume: 24 Issue: 5, 915 - 920, 12.10.2018

Abstract

Measuring
Range of Motion (ROM) is the first step of physical therapy. A new method to
measure ROM by Kinect V2 whose camera type is time of flight is proposed.
Colored markers are attached to related joints and then their camera centered
three-dimensional world coordinates are located by Kinect. Using these coordinates,
joint angle, and ROM can be accurately calculated. To analyze reliability and
validity of the method, ROM measurements of right and left elbow from ten
participants are taken by standard goniometer and Kinect separately. For
inter-observer reliability, measurements were taken in two sessions by three
physiotherapists. The reliability tests Intra-class Correlation Coefficient
(ICC), Standard Error of Measure (SEM), and Minimal Detectable Change (MDC)
belonging to the measurements have been obtained. To compute absolute accuracy
of the method, a goniometer marked with colors has been recorded at four
different angles (45, 90, 135, and 180° ) by Kinect in six sessions having
50-frame periods each. Mean, Standard Deviation (SD), Root Mean Square Error
(RMSE), and Limits of Agreement (LOA) values are given for each angle and
session. The measurements taken for absolute accuracy clearly shows that Kinect
has 1- to 3-degree error rate and below 1-degree standard deviation. Analyzing
the collected data, the ICC values of Kinect measurements that are 0.94 for
right arm and 0.93 for left arm in contrast with the ICC values of goniometric
measurements taken by observers are 0.78 for the right arm and 0.81 for the
left arm. This study indicates the proposed method has a high level of accuracy
and reliability, and it can be efficiently used to measure ROM accurately.

References

  • Nussbaumer S, Leunig M, Glatthorn JF, Stauffacher S, Gerber H, Maffiuletti NA. “Validity and test-retest reliability of manual goniometers for measuring passive hip range of motion in femoroacetabular impingement patients”. BMC Musculoskeletal Disorder, 11(194), 2-11, 2010.
  • Gajdosik RL, Bohannon RW. “Clinical measurement of range of motion. Review of goniometry emphasizing reliability and validity”. Physical Therapy, 67(12), 1867-72, 1987.
  • Zhou H, Hu H. “Human motion tracking for rehabilitation-a survey”. Biomedical Signal Processing and Control, 3(1), 1-18, 2008.
  • Morris RG, Lawson SEM. “A review and evaluation of available gait analysis technologies and their potential for the measurement of impact transmission”. 2010.
  • Huber M, Seitz AL, Leeser M, Sternad D. “Validity and reliability of Kinect skeleton for measuring shoulder joint angles: a feasibility study”. Physiotherapy, 101(4), 389–393, 2015.
  • Bo APL, Hayashibe M, Poignet P. “Joint angle estimation in rehabilitation with inertial sensors and its integration with kinect”. 33rd Annual International Conference of the IEEE EMBS, Boston, Massachustts, USA, 30 August-03 September 2011.
  • Choppin SB, Lane B, Wheat JS. “The accuracy of the Microsoft Kinect in joint angle measurement”. Sports Technology, 7(1-2), 98-105, 2014.
  • Schmitz A, Boggess MY, Shapiro GR, Yang R, Noehren B. “The measurement of in vivo joint angles during a squat using a single camera markerless motion capture system as compared to a marker based system”. Gait Posture, 41(2), 694–698, 2015.
  • Schmitz A, Ye M, Shapiro R, Yang R, Noehren B. “Accuracy and repeatability of joint angles measured using a single camera markerless motion capture system”. Journal of Biomechanics, 47(2), 587-591, 2014.
  • Milani P, Coccetta CA, Rabini A, Sciarra T, Massazza G, Ferriero G. “Mobile smartphone applications for body position measurement in rehabilitation: a review of goniometric tools”. PM&R, 6(11), 1038-1043, 2014.
  • Mourcou Q, Fleury A, Diot B, Franco C, Vuillerme N. “Mobile phone-based joint angle measurement for functional assessment and rehabilitation of proprioception”. BioMed Research International, 2015, 1-15, 2015.
  • Quek J, Brauer SG, Treleaven J, Pua YH, Mentiplay B, Clark RA. “Validity and intra-rater reliability of an android phone application to measure cervical range-of-motion”. Journal of neuroengineering and rehabilitation, 11(1), 65, 2014.
  • Stone E, Skubic M. “Evaluation of an ınexpensive depth camera for passive ın-home fall risk assessment”. 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, Dublin, Ireland, 23-26 May 2011.
  • Stone EE, Skubic M. “Passive in-home measurement of stride-to-stride gait variability comparing vision and Kinect sensing”. 33rd Annual International Conference of the IEEE EMBS, Boston, Massachusetts, USA, 30 August-3 September 2011.
  • Gabel M, Gilad-Bachrach R, Renshaw E, Schuster A. “Full body gait analysis with kinect”. 34th Annual International Conference of the IEEE EMBS, San Diego, California, USA, 28 August - 01 September 2012.
  • Destelle F, Ahmadi A, O'Connor NE, Moran K, Chatzitofis A, Zarpalas D, Daras P. "Low-cost accurate skeleton tracking based on fusion of kinect and wearable inertial sensors". 22nd European Signal Processing Conference (EUSIPCO), Lisbon, Portugal, 1-5 September 2014.
  • Otman, SA, Demirel H, Sade A. Tedavi Hareketlerinde Temel Değerlendirme Prensipleri, 2. Baskı, Ankara, Türkiye, Hacettepe Üniversitesi Fizik Tedavi ve Rehabilitasyon Yayınları, 1998.
  • Corti A, et al. "A metrological characterization of the Kinect V2 time-of-flight camera". Robotics and Autonomous Systems, 75, 584-594, 2015.
  • Khoshelham K, Sander OE. "Accuracy and resolution of kinect depth data for indoor mapping applications". Sensors, 12(2), 1437-1454, 2015.
  • Landis JR, Gary GK. "The measurement of observer agreement for categorical data". Biometrics, 33(1), 159-174, 1977.
  • Zaki R, Bulgiba A, Ismail R, Ismail NA. “Statistical methods used to test for agreement of medical instruments measuring continuous variables in method comparison studies: a systematic review”. PloS one, 7(5), 37908, 2012.
  • Li L, Zeng L, Lin ZJ, Cazzell M, Liu H. “Tutorial on use of intraclass correlation coefficients for assessing intertest reliability and its application in functional near-infrared spectroscopy-based brain imaging". Journal of Biomedical Optics, 20(5), 050801-050801, 2015.
  • Fernandez R, Fernandez G. “Validating the bland-altman method of agreement”. Annual Conference of Western Users of SAS Software, San Jose, USA, 2009.
  • De Vet HC, Terwee CB, Mokkink LB, Knol DL. Measurement in Medicine: A Practical Guide. New York, USA, Cambridge University Press, 2011
  • Khoshelham K. "Accuracy analysis of kinect depth data". International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences, 38(5), 133-138, 2012.
There are 25 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Article
Authors

İrfan Kösesoy 0000-0001-5219-5397

Cemil Öz 0000-0001-9742-6021

Fatih Aslan 0000-0002-5948-6979

Fahri Köroğlu This is me 0000-0002-3917-9832

Mustafa Yığılıtaş This is me 0000-0001-6669-2132

Publication Date October 12, 2018
Published in Issue Year 2018 Volume: 24 Issue: 5

Cite

APA Kösesoy, İ., Öz, C., Aslan, F., Köroğlu, F., et al. (2018). Reliability and validity of an innovative method of ROM measurement using Microsoft Kinect V2. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 24(5), 915-920.
AMA Kösesoy İ, Öz C, Aslan F, Köroğlu F, Yığılıtaş M. Reliability and validity of an innovative method of ROM measurement using Microsoft Kinect V2. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. October 2018;24(5):915-920.
Chicago Kösesoy, İrfan, Cemil Öz, Fatih Aslan, Fahri Köroğlu, and Mustafa Yığılıtaş. “Reliability and Validity of an Innovative Method of ROM Measurement Using Microsoft Kinect V2”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 24, no. 5 (October 2018): 915-20.
EndNote Kösesoy İ, Öz C, Aslan F, Köroğlu F, Yığılıtaş M (October 1, 2018) Reliability and validity of an innovative method of ROM measurement using Microsoft Kinect V2. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 24 5 915–920.
IEEE İ. Kösesoy, C. Öz, F. Aslan, F. Köroğlu, and M. Yığılıtaş, “Reliability and validity of an innovative method of ROM measurement using Microsoft Kinect V2”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 24, no. 5, pp. 915–920, 2018.
ISNAD Kösesoy, İrfan et al. “Reliability and Validity of an Innovative Method of ROM Measurement Using Microsoft Kinect V2”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 24/5 (October 2018), 915-920.
JAMA Kösesoy İ, Öz C, Aslan F, Köroğlu F, Yığılıtaş M. Reliability and validity of an innovative method of ROM measurement using Microsoft Kinect V2. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2018;24:915–920.
MLA Kösesoy, İrfan et al. “Reliability and Validity of an Innovative Method of ROM Measurement Using Microsoft Kinect V2”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 24, no. 5, 2018, pp. 915-20.
Vancouver Kösesoy İ, Öz C, Aslan F, Köroğlu F, Yığılıtaş M. Reliability and validity of an innovative method of ROM measurement using Microsoft Kinect V2. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2018;24(5):915-20.

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