Kyushu University Academic Staff Educational and Research Activities Database
List of Presentations
Sanjaya Vipula Bandara Danwatta Last modified date:2023.12.19

Assistant Professor / Department of Mechanical Engineering / Faculty of Engineering


Presentations
1. Zhu Junda、D.S.V. Bandara、Arata Jumpei, SVM based classifi cation of motor imagery tasks for rehabilitation using moving windowSTFT features with EEG signals., 第24回計測自動制御学会システムインテグレーション部門講演会, 2023.12.
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3. D.S.V. Bandara, Jumpei Arata, Active Range of Motion Measurement System Using an Optical Sensor to Evaluate HandFunctions, EMBC 2023, 2023.07, [URL].
4. Chongzaijiao He, D.S.V Bandara, Hirofumi Nogami, Jumpei Arata, Prediction of finger motions based on high-density electromyographic signals using two-dimensional convolutional neural networks, ロボティクス・メカトロニクス 講演会 2023 in Nagoya, 2023.06.
5. Ren Jiawei, D.S.V Bandara, Jumpei Arata, Introducing superelasticity into Cosserat theory for modeling a compliant surgical manipulator, Asian Conference on Computer Aided Surgery 2023, 2023.05.
6. D.S.V Bandara, He Chongzaijiao, Jumpei Arata, Motion Intention Estimation of Finger Motions with Spatial Variations of HD EMG Signals, 15th International Conference on Computer and Automation Engineering (ICCAE 2023), 2023.03, Estimation of motion intention of human hand has many applications in robotics and other human centred areas. Especially with wearable robotic applications biosignal based estimation of human hand motions are widely used. However, based on the construction of the muscles for finger motions, and the higher number of independent motions of the human hand, estimation of finger motions accurately and effectively remains a challenge with current techniques. On the other hand, high density electromyography (HDEMG), has the capability to provide a high resolution spatial activation image of the muscle group under its measurement. In this study HDEMG signals were used to estimate the finger motions, by using the spatial variations of the surface HDEMG signals during the different finger motions. Thus, features of Gabor filters and error- correcting output codes method was used to classify six motion classes of finger motions. Results show the proposed methodology can successfully classify the motions with a higher accuracy..
7. Yoshinori Furukawa, D. S. V. Bandara, Hirofumi Nogami and Jumpei Arata, Realtime EMG signal processing with OneClassSVM to extract motion intentions for a hand rehabilitation robot, 2023 International Symposium on System Integration (SII2023), 2023.01, Neurorehabilitation with robot has a potential to improve the motor function of post stroke patients. We are developing a rehabilitation robot to provide hand open and close training for patients. The robot is triggered by upper limb forearm surface electromyography(EMG). However, owing to complex arrangement of the muscle layers and muscle cross talk during the both open and close motions of the hand, traditional classification techniques of motion intention does not perform successfully in its implementation. Further, presence of motion artifacts such as natural supination/pronation, wrist flexion/extension also has become a challenge to overcome in classifying hand open/close and relax states successfully. Thus in this study, we propose a real-time classification method that uses OneClass SVM to extract hand open/close and relax motions and enables to cater for the individual differences of the different users. In the evaluation experiments with 5 different subjects, the proposed method could successfully classify motion intention of hand open/close and relax in the presence of different motion artifacts..
8. D.S.V BANDARA, #WU Zongpeng, Jumpei ARATA, Modified design of a 2 mm surgical robotic forceps for improved ROM and a longer lifespan, Asian Conference on Computer Aided Surgery, 2020.11.
9. D.S.V BANDARA, #WU Zongpeng, #Wataru KAJIHARA, Jumepi ARATA, Novel design to improve the lifespan and range of motion of 3.5 mm surgical manipulator comprises of elastic elements, through stress management, International Conference of Computer Assisted Radiology and Surgery 2020, 2020.06.
10. #WU Zongpeng, D.S.V BANDARA, Jumpei ARATA, Design strategy for a surgical manipulator based on a compliant mechanism- rigidity and range of motion: finding the optimized balance, IEEE International Conference on Robotics and Biomimetics, 2019.12.
11. WU Zongpeng, D.S.V BANDARA, Jumpei ARATA, Design improvement and evaluation of a surgical manipulator that contains largely deformable elements, Asian Conference on Computer Aided Surgery, 2019.11.
12. Takefumi ISHII, Kanako HARADA, Mamoru MITSUISHI, Sanjaya V. BANDARA, WU Zongpeng, Jumpei ARATA, Fast shape computation for a surgical manipulator that contains largely deformable elements, Asian Conference on Computer Aided Surgery, 2019.11.
13. Jumpei ARATA, D.S.V. BANDARA, Wataru KAJIHARA, Ryu NAKADATE, Kanako HARADA, Mamoru MITSUISHI, Kazuo KIGUCHI, Makoto HASHIZUME, 2mm surgical manipulator with four degrees-of-freedom for transnasal endoscopy comprising elastic mechanical element, International conference on The International Conference of Computer Assisted Radiology and Surgery, 2019.06.
14. D.S.V BANDARA, Kazuo KIGUCHI, Brain signal acquisition methods in BCIs to estimate human motion intention – a survey, International Symposium on Micro-Nano Mechatronics and Human Science, 2018.12.
15. D.S.V BANDARA, Kazuo KIGUCH, Towards controlling of an upper-limb exoskeleton for motion assist with EEG signals – motion prediction, International Conference on Control, Automation and Systems, 2017.10.
16. R.A.R.C. GOPURA, D.S.V. BANDARA, N.P.A. GUNASEKERA, V.H. HAPUARACHCHI, B.S. ARIYARATHNA, A prosthetic hand with self-adaptive fingers, International Conference on Control Automation and Robotics, 2017.04.
17. D.S.V BANDARA, J. ARATA, K. KIGUCHI, Task based motion intention prediction with EEG signals, IEEE International Symposium on Robotics and Intelligent Sensors, 2016.12.
18. D.S.V BANDARA, J. ARATA, K. KIGUCHI, Detecting the motion intention of the humans with EEG signals, JSME International Conference on Advanced Mechatronics, 2015.12.
19. R.B GAYAN, Y. RAMESHKANNA, R. RATHEESAN, S.I SENEVIRATHNE, K.H MANGALA, D.S.V BANDARA , Process optimization of sri lankan saucepan manufacturing industry by time study analysis, Annual Technical Conference of The Institution of Engineering and Technology, 2015.07.
20. D.S.V BANDARA, R.A.R.C GOPURA, K.T.M.U HEMAPALA, K. KIGUCHI, A multi-DOF anthropomorphic transradial prosthetic arm, IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, 2014.08.
21. D.S.V. BANDARA, G. KAJANTHAN, M. BRUNTHAVAN, R.A.R.C. GOPURA, An under-actuated mechanism for finger designs in hand prosthesis, Peradeniya University International Research Sessions, 2014.07.
22. N.P.A. GUNASEKERA, V.H. HAPUARACHCHI, B.S. ARIYARATHNA, D.S.V. BANDARA, R.A.R.C. GOPURA, Development of a multifunctional hand prosthesis with a self-adaptive mechanism, Peradeniya University International Research Sessions, 2014.07.
23. D.S.V. BANDARA, R.A.R.C GOPURA, G. KAJANTHAN, M. BRUNTHAVAN,H.I.M.M. ABEYNAYAKE, An under-actuated mechanism for a robotic finger, IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, 2014.06.
24. G. KAJANTHAN, M. BRUNTHAVAN, D.S.V. BANDARA,R.A.R.C. GOPURA, An under actuated hand prosthesis with grasping adaptation, Mini Engineering Research Unit Symposium, 2013.06.
25. D.S.V. BANDARA, R.A.R.C GOPURA, G. KAJANTHAN, M. BRUNTHAVAN,H.I.M.M. ABEYNAYAKE , Upper extremity prosthetics: current status, challenges and future directions, International Conference on Artificial Life and Robotics, 2012.01.
26. @R. A. R. C. GOPURA, @K. KIGUCHI ,@D. S. V. BANDARA, A brief review on upper extremity robotic exoskeleton systems, International Conference on Industrial and Information Systems, 2011.08.