ENGELLİ İNSANLAR İÇİN AKILLI TEKERLEKLİ SANDALYENİN BAŞ HAREKETLERİ İLE KONTROLÜNÜN GERÇEKLEŞTİRİLMESİ

Year 2020, Volume: 2 Issue: 1, 19 - 32, 30.06.2020

Muhammed Oguz Tas , Didem Ozupek Tas , Hasan Serhan Yavuz

Abstract

Felç, MS, ALS gibi fizyolojik sınırlamalara neden olan hastalıklara sahip insanlar, hareket kabiliyetlerini kaybettikleri için, tekerlekli sandalyeye bağlı bir hayat sürmektedirler. Kavrama, tutma gibi becerilerini kaybeden bireyler, tekerlekli sandalyeleri kullanmakta zorlandıkları için, başka insanların yardımlarına ihtiyaç duyabilirler. Bu durum, kişilerin özgürlüklerini ve rahat hareket etmelerini kısıtlamaktadır. Son yıllarda, içinde birçok sensörü barındıran ve engelleri algılama, otonom sürüş gibi özelliklere sahip akıllı robotik tekerlekli sandalyeler üzerinde birçok çalışma gerçekleştirilmektedir. Bu çalışmada, hareket kabiliyetleri kısıtlı bireyler için, benzetim ortamında hazırlanan akıllı tekerlekli sandalye kullanılmış ve sadece baş hareketlerine dayanan bir kontrol mekanizması sunulmuştur. Çalışmada, tekerlekli sandalyenin kontrolü düşük maliyetli bir web kamera kullanılarak gerçekleştirilmiş ve herhangi bir giyilebilir donanım kullanılmasını gerekli kılmamıştır. Gerçekleştirilen çalışmada tekerlekli sandalye otonom ve yarı otonom modlarda kullanılabilmektedir. Kullanıcının baş hareketlerinin web kamera üstünden tespit edilmesinden sonra, tekerlekli sandalyenin hareketi benzetim ortamında gerçekleştirilmektedir. Çalışma sonucunda, baş hareketleri ile tekerlekli sandalyenin benzetim ortamında her iki modda kolaylıkla kontrol edilebildiği gözlenmiştir.

Keywords

akıllı tekerlekli sandalye;, baş kontrollü robot, robot işletim sistemi

IMPLEMENTATION OF SMART WHEELCHAIR CONTROL BY USING HEAD MOVEMENTS FOR DISABLED PEOPLE

Abstract

People with diseases such as stroke MS, ALS that cause physical limitations lead a wheelchair-dependent life as they lose their movement capability. Individuals who lose their skills such as grip and hold may need other people's help as they have difficulty using wheelchairs. This situation restricts the freedom and comfortable movement of disabled people. In recent years, many studies have been carried out on smart wheelchairs with many sensors and features such as obstacle detection and autonomous driving. In this study, we present a control mechanism based on head movements for individuals with limited movement capacity using the smart wheelchair model prepared in a simulation environment. Here, the control of the wheelchair was realized by using a low-cost webcam and did not require the use of any wearable hardware. The designed wheelchair in the study can be used in autonomous and semi-autonomous modes. After the user's head movements are detected on the webcam, the movement of the wheelchair has been observed in the simulation environment. As a result of the study, we verified that the wheelchair can easily be controlled in both modes in simulation environment with head movements. 

Keywords

Smart wheelchair, head controlled robot, robot operating system

References

• 3D Warehouse (2020), Wheelchair, https://3dwarehouse.sketchup.com/ model/3b37f4a8461555d81fabf3cbd0fc77bc/Wheelchair, Erişim Tarihi: 13.03.2020.
• Chen, Y. L., Chen, S. C., Chen, W. L. ve Lin, J. F. (2003), A head orientated wheelchair for people with disabilities, Disability and Rehabilitation, 25(6), 249-253.
• Dey, P., Hasan, M. M., Mostofa, S. ve Rana, A. I. (2019), Smart wheelchair integrating head gesture navigation, In 2019 International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), 329-334.
• Eid, M. A., Giakoumidis, N. ve El Saddik, A. (2016), A novel eye-gaze-controlled wheelchair system for navigating unknown environments: Case study with a person with ALS, IEEE Access, 4, 558-573.
• GAZEBO (2013), Robot simulation, http://gazebosim.org/, Erişim Tarihi:13.03.2020.
• Kazemi, V. ve Sullivan, J. (2014), One millisecond face alignment with an ensemble of regression trees, In Proceedings of the IEEE conference on computer vision and pattern recognition, 1867-1874.
• Kim, J., Park, H., Bruce, J., Sutton, E., Rowles, D., Pucci, D. ve Laumann, A. (2013), The tongue enables computer and wheelchair control for people with spinal cord injury. Science translational medicine, 5(213).
• King D. (2020), dlib-models, https://github.com/davisking/dlib-models, Erişim Tarihi: 13.03.2020.
• Leonard, J. J. and Durrant-Whyte, H. F. (1991), Simultaneous map building and localization for an autonomous mobile robot, Intelligent Robots and Systems' IROS'91, IEEE/RSJ International Workshop, 1442-1447.
• Lund, M. E., Christiensen, H. V., Caltenco, H. A., Lontis, E. R., Bentsen, B., ve Struijk, L. N. A. (2010), Inductive tongue control of powered wheelchairs, In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 3361-3364.
• Machangpa, J. W., ve Chingtham, T. S. (2018), Head Gesture Controlled Wheelchair for Quadriplegic Patients, Procedia computer science, 132, 342-351.
• Marins, G., Carvalho, D., Marcato, A. ve Junior, I. (2017), Development of a control system for electric wheelchairs based on head movements, In 2017 Intelligent Systems Conference (IntelliSys), 996-1001.
• Mougharbel, I., El-Hajj, R., Ghamlouch, H. ve Monacelli, E. (2013), Comparative study on different adaptation approaches concerning a sip and puff controller for a powered wheelchair. In 2013 Science and Information Conference, 597-603.
• Nguyen, Q. X. ve Jo, S. (2012), Electric wheelchair control using head pose free eye-gaze tracker, Electronics Letters, 48(13), 750-752.
• Nishimori, M., Saitoh, T., ve Konishi, R. (2007), Voice controlled intelligent wheelchair, In SICE Annual Conference 2007, 336-340.
• Rabhi, Y., Mrabet, M. ve Fnaiech, F. (2018), A facial expression controlled wheelchair for people with disabilities. Computer methods and programs in biomedicine, 165, 89-105.
• Rechy-Ramirez, E. J., Hu, H., ve McDonald-Maier, K. (2012), Head movements based control of an intelligent wheelchair in an indoor environment, In 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO),1464-1469.
• Sagonas, C., Tzimiropoulos, G., Zafeiriou, S. ve Pantic, M. (2013), 300 faces in-the-wild challenge: The first facial landmark localization challenge, In Proceedings of the IEEE International Conference on Computer Vision Workshops, 397-403.
• Shinde, K. D., Tarannum, S., Veerabhadrappa, T., Gagan, E.,ve Kumar, P. V. (2018), Implementation of Low Cost, Reliable, and Advanced Control with Head Movement, Wheelchair for Physically Challenged People, In Progress in Advanced Computing and Intelligent Engineering, 313-328, Springer, Singapore.
• Sivakumar, M. S., Murji, J., Jacob, L. D., Nyange, F. and Banupriya, M. (2013), Speech controlled automatic wheelchair, In 2013 Pan African International Conference on Information Science, Computing and Telecommunications (PACT), 70-73.
• Tanaka, K., Matsunaga, K. ve Wang, H. O. (2005), Electroencephalogram-based control of an electric wheelchair, IEEE transactions on robotics, 21(4), 762-766.
• Viola P. and Jones M. (2001), Robust Real-time Object Detection, In International Journal of Computer Vision 57 (2).