Basic research of upper limb work support system “My cybernic robot arm” for hemiplegic persons

Author(s):  
Hiroaki Toyama ◽  
Hiroaki Kawamoto ◽  
Yoshiyuki Sankai
2022 ◽  
Author(s):  
Madhav Rao

This study examines the system integration of a game engine with robotics middleware to drive an 8 degree offreedom (DoF) robotic upper limb to generate human-like motion for telerobotic applications. The developed architectureencompasses a pipeline execution design using Blender Game Engine (BGE) including the acquisition of real humanmovements via the Microsoft Kinect V2, interfaced with a modeled virtual arm, and replication of similar arm movements on the physical robotic arm. In particular, this study emphasizes the integration of a human “pilot” with ways to drive such a robotic arm through simulation and later, into a finished system. Additionally, using motion capture technology, a human upper limb action was recorded and applied onto the robot arm using the proposed architecture flow. Also, we showcase the robotic arm’s actions which include reaching, picking, holding, and dropping an object. This paper presentsa simple and intuitive kinematic modeling and 3D simulation process, which is validated using 8-DoF articulated robot to demonstrate methods for animation, and simulation using the designed interface.


2020 ◽  
Vol 40 (6) ◽  
pp. 790-797
Author(s):  
Koike Yuji ◽  
Suzuki Makoto ◽  
Okino Akihisa ◽  
Takeda Kazuhisa ◽  
Takanami Yasuhiro ◽  
...  

Abstract Purpose To clarify the feature values of exercise therapy that can differentiate students and expert therapists and use this information as a reference for exercise therapy education. Methods The participants were therapists with 5 or more years of clinical experience and 4th year students at occupational therapist training schools who had completed their clinical practices. The exercise therapy task included Samothrace (code name, SAMO) exercises implemented on the elbow joint based on the elbow flexion angle, angular velocity, and exercise interval recordings. For analyses and student/therapist comparisons, the peak flexion angle, peak velocity, and movement time were calculated using data on elbow angle changes acquired via SAMO. Subsequently, bootstrap data were generated to differentiate between the exercise therapy techniques adopted by therapists and students, and a support vector machine was used to generate four types of data combinations with the peak flexion angle, peak velocity, and movement time values. These data were used to estimate and compare the respective accuracies with the Friedman test. Results The peak flexion angles were significantly smaller in the case of students. Furthermore, the peak velocities were larger, the peak flexion angles were smaller, and the movement times were shorter compared with those of therapists. The combination of peak velocity and peak flexion angle yielded the highest diagnostic accuracies. Conclusion When students and therapists performed upper limb exercise therapy techniques based on the kinematics movement of a robot arm, the movement speeds and joint angles differed. The combination of peak velocity and peak flexion angle was the most effective classifier used for the differentiation of the abilities of students and therapists. The peak velocity and peak flexion angle of the therapist group can be used as a reference for students when they learn upper limb therapeutic exercise techniques.


Author(s):  
Tomohiro Fujisawa ◽  
Motoki Takagi ◽  
Yoshiyuki Takahashi ◽  
Kaoru Inoue ◽  
Takafumi Terada ◽  
...  

2007 ◽  
Vol 2007 (0) ◽  
pp. _2A2-D09_1-_2A2-D09_2
Author(s):  
Tomohiro FUJISAWA ◽  
Motoki TAKAGI ◽  
HOKYO Lee ◽  
Yoshiyuki TAKAHASHI ◽  
Kaoru INOUE ◽  
...  

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