OMUZ HASARLI HASTALAR İÇİN COCOMODEL İLE TELEREHABİLİTASYON UYGULAMASI
Year 2022,
, 53 - 60, 15.04.2022
Sedef Kılıççeken
,
Burakhan Çubukçu
,
Uğur Yüzgeç
Abstract
Dünyada engelli sayısının artmasıyla birlikte fizyoterapiye ihtiyaç duyan insanların sayısı da artmaktadır. Gelişmiş teknolojileri kullanan telerehabilitasyon sistemleri, geleneksel fizyoterapi yöntemlerine göre avantajlara sahiptir. Telerehabilitasyon sayesinde insan iskelet sistemi izlenebilmekte ve hastalara rehabilitasyon yaptırılabilmektedir. Bununla birlikte 3 boyutlu hareket izleme sistemlerinin, Kinect gibi sistemlerin donanım maliyetleri bulunmaktadır. Bu çalışmada herhangi bir kamera ile alınan görüntüler üzerinde 2D olarak insan vücut eklemleri ve eklem koordinatları tespit edilmiştir. Elde edilen eklem bilgileri ile omuz eklemi, kas ve tendon hasarlı hastalar için fizyoterapi uygulaması geliştirilip fizik tedavi merkezlerine gidemeyen hastalara kolaylık sağlanması amaçlanmıştır. Önerilen bu sistemin Kinect, 3D hareket izleme sistemlerine göre avantaj ve dezavantajları değerlendirilmiştir.
References
- Bidargaddi, N. P. ve Sarela, A. (2008). Activity and heart rate-based measures for outpatient cardiac rehabilitation. Methods of Information in Medicine, 47(3), 208–216. doi:10.3414/ME9112
- Cao, Z., Simon, T., Wei, S. E. ve Sheikh, Y. (2017). Realtime multi-person 2D pose estimation using part affinity fields. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017-Janua(Xxx), 1302–1310. doi:10.1109/CVPR.2017.143
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- Çubukçu, B. ve Yüzgeç, U. (2017). A Physiotherapy Application with MS Kinect for Patients with Shoulder Joint , Muscle and Tendon Damage. The 9th International Conference on Computational Intelligence and Communication Networks (CICN 2017) içinde (ss. 225–228). Girne, Kıbrıs. doi:10.1109/CICN.2017.49
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- Çubukçu, B., Yüzgeç, U., Zİlelİ, R. ve Zİlelİ, A. (2018). A Kinect 2 Based Telerehabilitation Method for Shoulder Rehabilitation Exercises. International Conference on Advanced Technologies, Computer Engineering and Science (ICATCES’18) içinde (ss. 53–56).
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- Müller, B., Ilg, W., Giese, M. A. ve Ludolph, N. (2017). Validation of enhanced kinect sensor based motion capturing for gait assessment. bioRxiv, 14–16. doi:10.1101/098863
- Paffenbarger, R. S., Hyde, R., Wing, A. L. ve Hsieh, C. (1986). Physical Activity, All-Cause Mortality, and Longevity of College Alumni. New England Journal of Medicine, 314(10), 605–613. doi:10.1056/NEJM198603063141003
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- Shaughnessy, M., Resnick, B. M. ve Macko, R. F. (2006). Testing a model of post-stroke exercise behavior. Rehabilitation Nursing, 31(1), 15–21. doi:10.1002/j.2048-7940.2006.tb00005.x
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- Tino, D. ve Hillis, C. (2010). The full can exercise as the recommended exercise for strengthening the supraspinatus while minimizing impingement. Strength and Conditioning Journal, 32(5), 33–35. doi:10.1519/SSC.0b013e3181d54721
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TELEREHABILITATION APPLICATION WITH COCOMODEL FOR PATIENTS WITH SHOULDER DAMAGE
Year 2022,
, 53 - 60, 15.04.2022
Sedef Kılıççeken
,
Burakhan Çubukçu
,
Uğur Yüzgeç
Abstract
With the increase in the number of disabled people in the world, the number of people who need physiotherapy is also increasing. Telerehabilitation systems using advanced technologies have advantages over traditional physiotherapy methods. Thanks to telerehabilitation, the human skeletal system can be monitored and patients can be rehabilitated. However, systems such as 3D motion tracking systems and Kinect have hardware costs. In this study, human body joints and joint coordinates were determined in 2D on images taken with any camera. With the joint information obtained, it is aimed to develop a physiotherapy application for patients with shoulder joint, muscle and tendon damage and to provide convenience to patients who cannot go to physical therapy centers. The advantages and disadvantages of this proposed system compared to Kinect, 3D motion tracking systems have been evaluated.
References
- Bidargaddi, N. P. ve Sarela, A. (2008). Activity and heart rate-based measures for outpatient cardiac rehabilitation. Methods of Information in Medicine, 47(3), 208–216. doi:10.3414/ME9112
- Cao, Z., Simon, T., Wei, S. E. ve Sheikh, Y. (2017). Realtime multi-person 2D pose estimation using part affinity fields. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017-Janua(Xxx), 1302–1310. doi:10.1109/CVPR.2017.143
- Çubukçu, B. ve Çetin, A. (2016). Ms Kinect Applications And Opportunities For People. International Multidisciplinary Conference içinde (ss. 459–465).
- Çubukçu, B. ve Yüzgeç, U. (2017). A Physiotherapy Application with MS Kinect for Patients with Shoulder Joint , Muscle and Tendon Damage. The 9th International Conference on Computational Intelligence and Communication Networks (CICN 2017) içinde (ss. 225–228). Girne, Kıbrıs. doi:10.1109/CICN.2017.49
- Çubukçu, B., Yüzgeç, U., Zileli, R. ve Zileli, A. (2020). Reliability and validity analyzes of Kinect V2 based measurement system for shoulder motions. Medical Engineering and Physics, 76, 20–31. doi:10.1016/j.medengphy.2019.10.017
- Çubukçu, B., Yüzgeç, U., Zİlelİ, R. ve Zİlelİ, A. (2018). A Kinect 2 Based Telerehabilitation Method for Shoulder Rehabilitation Exercises. International Conference on Advanced Technologies, Computer Engineering and Science (ICATCES’18) içinde (ss. 53–56).
- Çubukçu, B., Yüzgeç, U., Zı̇lelı̇, A. ve Zı̇lelı̇, R. (2021). Kinect-based integrated physiotherapy mentor application for shoulder damage. Future Generation Computer Systems, 122, 105–116. doi:10.1016/j.future.2021.04.003
- Dinvar, Y., Çubukçu, B. ve Yüzgeç, U. (2017). MS Kinect Based Tracking Application for Knee Anterior Cruciate Ligament Physical Therapy. 2017 International Conference on Computer Science and Engineering (UBMK) içinde .
- Duarte, N., Postolache, O. ve Sharcanski, J. (2014). KSGphysio – Kinect Serious Game for Physiotherapy. International Conference and Exposition on Electrical and Power Engineering, (Epe), 16–18. doi:10.1109/ICEPE.2014.6969981
- Han, J., Shao, L., Xu, D. ve Shotton, J. (2013). Enhanced Computer Vision With Microsoft Kinect Sensor: A Review. IEEE Transactions on Cybernetics, 43(5), 1318–1334. doi:10.1109/TCYB.2013.2265378
- http://cocodataset.org/. Erişim: 11 Eylül 2019
- https://arvrjourney.com/human-pose-estimation-using-openpose-with-tensorflow-part-2-e78ab9104fc8. Erişim: 11 Mayıs 2019
- https://pdfs.semanticscholar.org/dfad/8f616bd2a05c8cae5f61060f743f966ece85.pdf. Erişim: 11 Mayıs 2019
- Lee, I.-M., Hsieh, C. ve Paffenbarger Jr, R. S. (1995). Exercise Intensity and Longevity in Men: The Harvard Alumni Health Study. JAMA, 273(15), 1179–1184. doi:10.1001/jama.1995.03520390039030
- Müller, B., Ilg, W., Giese, M. A. ve Ludolph, N. (2017). Validation of enhanced kinect sensor based motion capturing for gait assessment. bioRxiv, 14–16. doi:10.1101/098863
- Paffenbarger, R. S., Hyde, R., Wing, A. L. ve Hsieh, C. (1986). Physical Activity, All-Cause Mortality, and Longevity of College Alumni. New England Journal of Medicine, 314(10), 605–613. doi:10.1056/NEJM198603063141003
- Pedraza-Hueso, M., Martín-Calzón, S., Díaz-Pernas, F. J. ve Martínez-Zarzuela, M. (2015). Rehabilitation Using Kinect-based Games and Virtual Reality. Procedia Computer Science, 75(Vare), 161–168. doi:10.1016/j.procs.2015.12.233
- Rizzo, A. ve Kim, G. J. (2005). A SWOT analysis of the field of virtual reality rehabilitation and therapy. Presence: Teleoperators and Virtual Environments, 14(2), 119–146. doi:10.1162/1054746053967094
- Roy, A. K., Soni, Y. ve Dubey, S. (2013). Enhancing effectiveness of motor rehabilitation using kinect motion sensing technology. 2013 IEEE Global Humanitarian Technology Conference: South Asia Satellite (GHTC-SAS), 298–304. doi:10.1109/GHTC-SAS.2013.6629934
- Russell, T. G. (2007). Physical rehabilitation using telemedicine. Journal of Telemedicine and Telecare, 13, 217–220. doi:https://doi.org/10.1258/135763307781458886
- Sadeghi Esfahlani, S., Muresan, B., Sanaei, A. ve Wilson, G. (2018). Validity of the Kinect and Myo armband in a serious game for assessing upper limb movement. Entertainment Computing, 27, 150–156. doi:https://doi.org/10.1016/j.entcom.2018.05.003
- Shaughnessy, M., Resnick, B. M. ve Macko, R. F. (2006). Testing a model of post-stroke exercise behavior. Rehabilitation Nursing, 31(1), 15–21. doi:10.1002/j.2048-7940.2006.tb00005.x
- Spear, B. A., Barlow, S. E., Ervin, C., Ludwig, D. S. ve Saelens, B. E. (2007). Recommendations for Treatment of Child and Adolescent Overweight and Obesity. doi:10.1542/peds.2007-2329F
- Tino, D. ve Hillis, C. (2010). The full can exercise as the recommended exercise for strengthening the supraspinatus while minimizing impingement. Strength and Conditioning Journal, 32(5), 33–35. doi:10.1519/SSC.0b013e3181d54721
- Weiss, P. L., Rand, D., Katz, N. ve Kizony, R. (2004). Video capture virtual reality as a flexible and effective rehabilitation tool. Journal of NeuroEngineering and Rehabilitation, 1, 1–12. doi:10.1186/1743-0003-1-12