Design of a robotic hand imitating hand and finger gestures for rehabilitation applications
Yıl 2023,
Cilt: 12 Sayı: 4, 1385 - 1391, 15.10.2023
Yağmur Çiğdem Kalan
,
Eda Akman Aydın
Öz
Rehabilitation is a therapy process that helps people who have lost their motor abilities partially or completely to restore their lost functions. Accuracy and continuity of the repetitive movements in the therapy process are important for the success of the rehabilitation process. Therefore, in order to ensure the continuity of the rehabilitation process, it is necessary to develop systems where exercises can be continued without going to rehabilitation centers. In this study, a robot hand prototype application that imitates both hand and finger movements has been developed for hand rehabilitation applications. An Inertial Measurement Unit (IMU) sensor is used to detect hand movements and a flexible sensor is used to detect finger movements. The hand movements are used to control the two motors on the robot hand prototype, while the flexibility sensor controls the gripper on the robot, allowing the robot hand prototype to grip. The task completion times were recorded by giving the participants the task of moving a cylindrical object to the target point using the robot hand prototype.
Kaynakça
- A. Mandeljc, A. Rajhard, M. Munih, R. Kamnik, Robotic Device for Out-of-Clinic Post-Stroke Hand Rehabilitation. Applied Sciences, 12 (3), 1092, 2022. https://doi.org/10.3390/app12031092.
- P. Polygerinos, Z. Wang, K.C. Galloway, R. J. Wood, C.J. Walsh, Soft robotic glove for combined assistance and at-home rehabilitation. Robotics and Autonomous Systems, 73, 135-143, 2015. https://doi.org/10.1016 /j.robot.2014.08.014.
- M. Mulas, M. Folgheraiter, G. Gini, An EMG-controlled exoskeleton for hand rehabilitation. 9th International Conference on Rehabilitation Robotics, 2005. 371-374, 2005. https://doi.org/10.1109/ICORR .2005.1501122.
- S. Almasi, H. Ahmadi, F. Asadi, L. Shahmoradi, G. Arji, M. Alizadeh, H. Kolivand, Kinect-Based Rehabilitation Systems for Stroke Patients: A Scoping Review. BioMed Research International, 4339054, 2022. https://doi.org/10.1155/2022/4339054.
- Y.X. Hung, P.C. Huang, K.T. Chen, W.C. Chu, What Do Stroke Patients Look for in Game-Based Rehabilitation: A Survey Study. Medicine (Baltimore), 95 (11), e3032, 2016. https://doi.org/10 .1097/MD.0000000000003032.
- D. Esposito, J. Centracchio, E. Andreozzi, G.D. Gargiulo, G.R. Naik, P. Bifulco, Biosignal-Based Human-Machine Interfaces for Assistance and Rehabilitation: A Survey. Sensors (Basel), 15, 21(20), 6863, 2021. https://doi.org/10.3390/s21206863.
- H.P. Singh, P. Kumar, Developments in the Human Machine Interface Technologies and Their Applications: A Review. J. Med. Eng. Technol, 45, 552–573, 2021. https://doi.org/10.1080/03091902.202 1.1936237.
- Z. Yue, X. Zhang, J. Wang, Hand Rehabilitation Robotics on Poststroke Motor Recovery. Behav Neurol, 2017:3908135, 2017. https://doi.org/10.1155 /2017/3908135.
- Kabir R, Sunny MSH, Ahmed HU, Rahman MH. Hand Rehabilitation Devices: A Comprehensive Systematic Review. Micromachines (Basel). 2022 Jun 29;13(7):1033. https://doi.org/10.3390/mi13071033.
- H. Feng, C. Li, J. Liu, L. Wang, J. Ma, G. Li, L. Gan, X. Shang, Z. Wu, Virtual Reality Rehabilitation Versus Conventional Physical Therapy for Improving Balance and Gait in Parkinson's Disease Patients: A Randomized Controlled Trial. Med Sci Monit, 25, 4186-4192, 2019. https://doi.org/10.12659/MSM.916 455.
- P. Tokgöz, S. Stampa, D. Wähnert, T. Vordemvenne, C. Dockweiler, Virtual Reality in the Rehabilitation of Patients with Injuries and Diseases of Upper Extremities. Healthcare (Basel), 10, 6, 1124, 2022. https://doi.org/10.3390/healthcare10061124.
- R. Feingold-Polak, O. Barzel, S.A. Levy-Tzedek, A robot goes to rehab: a novel gamified system for long-term stroke rehabilitation using a socially assistive robot—methodology and usability testing. Journal NeuroEngineering Rehabilitation, 18, 122, 2021. https://doi.org/10.1186/s12984-021-00915-2.
- Y. Chen, K.T. Abel, J.T. Janecek, Y. Chen, K. Zheng, S.C. Cramer, Home-based technologies for stroke rehabilitation: A systematic review. Int J Med Inform, 123, 11-22, 2019. https://doi.org/10.1016/j.ijmedin f.2 018.12.01
- N. T. Fitter, K.J. Kuchenbecker, Teaching a Robot Bimanual Hand-Clapping Games via Wrist-Worn IMUs. Frontiers in Robotics and AI, 5, 85, 2018. https ://doi.org/10.3389/frobt.2018.00085.
- A.D. Segal, M.C. Lesak, A. K. Silverman, A.J. Petruska, A Gesture-Controlled Rehabilitation Robot to Improve Engagement and Quantify Movement Performance. Sensors, 20, 15, 4269, 2020. https://doi .org/10.3390/s20154269.
- C. Liu, J. Lu, H. Yang, K. Guo, Current State of Robotics in Hand Rehabilitation after Stroke: A Systematic Review. Applied Sciences, 12, 9, 4540, 20 22. https://doi.org/10.3390/app12094540.
- A. Norhafizan, R.A.R. Ghazilla, N.M. Khairi, V. Kasi, Reviews on Various Inertial Measurement Unit (IMU) Sensor Applications. International Journal of Signal Processing Systems, 1, 2, 256-262, 2013. https:// doi.org/10.12720/ijsps.1.2.256-262.
- S. Li et al., "A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 10900-10906, Las Vegas, NV, USA, 2020. https://doi.org/10.1109/IR OS45743.2020.9340738.
- M. Kim, J. Cho, S. Lee, Y. Jung, IMU Sensor-Based Hand Gesture Recognition for Human-Machine Interfaces. Sensors, 19, 18, 3827, 2019. https://doi.o rg/10.3390/s19183827.
- M. Meghana et.al., Hand gesture recognition and voice controlled robot. Materials Today: Proceedings, 33, 7, 4121-4123, 2020. https://doi.org/10.1016/j.Ma tpr.2020.06.553.
- Y. Ozlük, E.A. Aydin, Fuzzy Logic Control of a Head-movement Based Semi-autonomous Human–machine Interface. Journal of Bionic Engineering, 20, 645–655, 2023. https://doi.org/10.1007/s42235-022-0 0272-3.
- X. Song, V. De Ven SS, L. Liu, F.J. Wouda, H. Wang, P.B. Shull, Activities of Daily Living-Based Rehabilitation System for Arm and Hand Motor Function Retraining After Stroke. IEEE Trans Neural Syst Rehabil Eng, 30, 621-631, 2022. https://doi.org /10.1109/TNSRE.2022.3156387.
- K.M. Triandafilou, D. Tsoupikova, A.J. Barry, Development of a 3D, networked multi-user virtual reality environment for home therapy after stroke. J NeuroEngineering Rehabil, 15, 88, 2018. https://doi .org/10.1186/s12984-018-0429-0.
- A. Raheimi, N.A.C. Zakaria, Integration of Flex Sensor into Wrist Exoskeleton for Rehabilitation of Stroke Patient. Basic Engineering Procedia, 1, 1, 48-57, 2020.
- Y.R. Garda et al, Flex Sensor Based Biofeedback Monitoring for Post-Stroke Fingers Myopathy Patients. J. Phys. Conf. Ser. 1007, 012069, 2018. http s://doi.org/10.1088/1742-6596/1007/1/012069.
Rehabilitasyon uygulamalarına yönelik el ve parmak hareketlerini taklit eden robot el tasarımı
Yıl 2023,
Cilt: 12 Sayı: 4, 1385 - 1391, 15.10.2023
Yağmur Çiğdem Kalan
,
Eda Akman Aydın
Öz
Rehabilitasyon, motor yeteneklerini kısmen ya da tamamen kaybeden kişilerin, kayıp fonksiyonlarını geri kazanmalarını sağlamalarına yardımcı olan bir terapi sürecidir. Terapi sürecinde tekrarlanan hareketlerin doğruluğu ve sürekliliği rehabilitasyon sürecinin başarısı açısından önem taşımaktadır. Bu nedenle, rehabilitasyon sürecinin devamlılığını sağlayabilmek adına, egzersizlerin rehabilitasyon merkezlerine gitmeksizin devam ettirilebileceği sistemlerin geliştirilmesi gerekmektedir. Bu çalışmada, el rehabilitasyonu uygulamalarına yönelik hem el ve hem de parmak hareketlerini taklit eden bir robot el prototipi uygulaması geliştirilmiştir. El hareketlerini algılamak için Atalet Ölçüm Sistemi (IMU) sensörü, parmak hareketini algılamak için ise bir esneklik sensörü kullanılmıştır. El hareketleri ile robot el prototipi üzerindeki iki motoru kontrol edilmesi, esneklik sensörü ile ise robot üzerindeki kıskacın kontrol edilmesi ve robot el prototipinin kavrama hareketinin yaptırılması sağlanmaktadır. Katılımcılara, robot el prototipi kullanarak silindirik bir nesneyi hedef noktaya taşıma görevi verilerek, görev tamamlama süreleri kaydedilmiştir.
Destekleyen Kurum
TÜBİTAK
Teşekkür
Bu çalışma TÜBİTAK Bilim İnsanı Destek Programları Başkanlığı tarafından 2209-A Üniversite Öğrencileri Araştırma Projeleri Destekleme Programı kapsamında desteklenmiştir.
Kaynakça
- A. Mandeljc, A. Rajhard, M. Munih, R. Kamnik, Robotic Device for Out-of-Clinic Post-Stroke Hand Rehabilitation. Applied Sciences, 12 (3), 1092, 2022. https://doi.org/10.3390/app12031092.
- P. Polygerinos, Z. Wang, K.C. Galloway, R. J. Wood, C.J. Walsh, Soft robotic glove for combined assistance and at-home rehabilitation. Robotics and Autonomous Systems, 73, 135-143, 2015. https://doi.org/10.1016 /j.robot.2014.08.014.
- M. Mulas, M. Folgheraiter, G. Gini, An EMG-controlled exoskeleton for hand rehabilitation. 9th International Conference on Rehabilitation Robotics, 2005. 371-374, 2005. https://doi.org/10.1109/ICORR .2005.1501122.
- S. Almasi, H. Ahmadi, F. Asadi, L. Shahmoradi, G. Arji, M. Alizadeh, H. Kolivand, Kinect-Based Rehabilitation Systems for Stroke Patients: A Scoping Review. BioMed Research International, 4339054, 2022. https://doi.org/10.1155/2022/4339054.
- Y.X. Hung, P.C. Huang, K.T. Chen, W.C. Chu, What Do Stroke Patients Look for in Game-Based Rehabilitation: A Survey Study. Medicine (Baltimore), 95 (11), e3032, 2016. https://doi.org/10 .1097/MD.0000000000003032.
- D. Esposito, J. Centracchio, E. Andreozzi, G.D. Gargiulo, G.R. Naik, P. Bifulco, Biosignal-Based Human-Machine Interfaces for Assistance and Rehabilitation: A Survey. Sensors (Basel), 15, 21(20), 6863, 2021. https://doi.org/10.3390/s21206863.
- H.P. Singh, P. Kumar, Developments in the Human Machine Interface Technologies and Their Applications: A Review. J. Med. Eng. Technol, 45, 552–573, 2021. https://doi.org/10.1080/03091902.202 1.1936237.
- Z. Yue, X. Zhang, J. Wang, Hand Rehabilitation Robotics on Poststroke Motor Recovery. Behav Neurol, 2017:3908135, 2017. https://doi.org/10.1155 /2017/3908135.
- Kabir R, Sunny MSH, Ahmed HU, Rahman MH. Hand Rehabilitation Devices: A Comprehensive Systematic Review. Micromachines (Basel). 2022 Jun 29;13(7):1033. https://doi.org/10.3390/mi13071033.
- H. Feng, C. Li, J. Liu, L. Wang, J. Ma, G. Li, L. Gan, X. Shang, Z. Wu, Virtual Reality Rehabilitation Versus Conventional Physical Therapy for Improving Balance and Gait in Parkinson's Disease Patients: A Randomized Controlled Trial. Med Sci Monit, 25, 4186-4192, 2019. https://doi.org/10.12659/MSM.916 455.
- P. Tokgöz, S. Stampa, D. Wähnert, T. Vordemvenne, C. Dockweiler, Virtual Reality in the Rehabilitation of Patients with Injuries and Diseases of Upper Extremities. Healthcare (Basel), 10, 6, 1124, 2022. https://doi.org/10.3390/healthcare10061124.
- R. Feingold-Polak, O. Barzel, S.A. Levy-Tzedek, A robot goes to rehab: a novel gamified system for long-term stroke rehabilitation using a socially assistive robot—methodology and usability testing. Journal NeuroEngineering Rehabilitation, 18, 122, 2021. https://doi.org/10.1186/s12984-021-00915-2.
- Y. Chen, K.T. Abel, J.T. Janecek, Y. Chen, K. Zheng, S.C. Cramer, Home-based technologies for stroke rehabilitation: A systematic review. Int J Med Inform, 123, 11-22, 2019. https://doi.org/10.1016/j.ijmedin f.2 018.12.01
- N. T. Fitter, K.J. Kuchenbecker, Teaching a Robot Bimanual Hand-Clapping Games via Wrist-Worn IMUs. Frontiers in Robotics and AI, 5, 85, 2018. https ://doi.org/10.3389/frobt.2018.00085.
- A.D. Segal, M.C. Lesak, A. K. Silverman, A.J. Petruska, A Gesture-Controlled Rehabilitation Robot to Improve Engagement and Quantify Movement Performance. Sensors, 20, 15, 4269, 2020. https://doi .org/10.3390/s20154269.
- C. Liu, J. Lu, H. Yang, K. Guo, Current State of Robotics in Hand Rehabilitation after Stroke: A Systematic Review. Applied Sciences, 12, 9, 4540, 20 22. https://doi.org/10.3390/app12094540.
- A. Norhafizan, R.A.R. Ghazilla, N.M. Khairi, V. Kasi, Reviews on Various Inertial Measurement Unit (IMU) Sensor Applications. International Journal of Signal Processing Systems, 1, 2, 256-262, 2013. https:// doi.org/10.12720/ijsps.1.2.256-262.
- S. Li et al., "A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 10900-10906, Las Vegas, NV, USA, 2020. https://doi.org/10.1109/IR OS45743.2020.9340738.
- M. Kim, J. Cho, S. Lee, Y. Jung, IMU Sensor-Based Hand Gesture Recognition for Human-Machine Interfaces. Sensors, 19, 18, 3827, 2019. https://doi.o rg/10.3390/s19183827.
- M. Meghana et.al., Hand gesture recognition and voice controlled robot. Materials Today: Proceedings, 33, 7, 4121-4123, 2020. https://doi.org/10.1016/j.Ma tpr.2020.06.553.
- Y. Ozlük, E.A. Aydin, Fuzzy Logic Control of a Head-movement Based Semi-autonomous Human–machine Interface. Journal of Bionic Engineering, 20, 645–655, 2023. https://doi.org/10.1007/s42235-022-0 0272-3.
- X. Song, V. De Ven SS, L. Liu, F.J. Wouda, H. Wang, P.B. Shull, Activities of Daily Living-Based Rehabilitation System for Arm and Hand Motor Function Retraining After Stroke. IEEE Trans Neural Syst Rehabil Eng, 30, 621-631, 2022. https://doi.org /10.1109/TNSRE.2022.3156387.
- K.M. Triandafilou, D. Tsoupikova, A.J. Barry, Development of a 3D, networked multi-user virtual reality environment for home therapy after stroke. J NeuroEngineering Rehabil, 15, 88, 2018. https://doi .org/10.1186/s12984-018-0429-0.
- A. Raheimi, N.A.C. Zakaria, Integration of Flex Sensor into Wrist Exoskeleton for Rehabilitation of Stroke Patient. Basic Engineering Procedia, 1, 1, 48-57, 2020.
- Y.R. Garda et al, Flex Sensor Based Biofeedback Monitoring for Post-Stroke Fingers Myopathy Patients. J. Phys. Conf. Ser. 1007, 012069, 2018. http s://doi.org/10.1088/1742-6596/1007/1/012069.