• Journal of Industrial Technology
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• v.21 no.B
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• pp.265-272
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• 2001

The human arm is modeled by three rigid bodies(the upper arm, the forearm and the hand)with seven degree of freedom(three in the shoulder, two in the elbow and two in the wrist). The objective of this work is to present a method to determine the three-dimensional kinematics of the human elbow joint using a magnetic tracking device. Euler angle were used to determine the elbow flexion-extension, and the pronation-supination. The elbow motion for the various driving conditions is measured through the driving test using a simulator. Discomfort levels of elbow joint motions were obtained as discomfort functions, which were based on subjects' perceived discomfort level estimated by magnitude estimation. The results showed that the discomfort posture of elbow joint motions occurred in the driving motion.

• PNF and Movement
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• v.5 no.1
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• pp.49-56
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• 2007

Objectives : We find that the reaction force on the elbow joint during elbow flexion, extension with and without an object in the hand can be calculated the equations of motion that the sum of the torque and the sum of the force acting on the elbow joint must be zero and (moment of inertia x angular acceleration) and (mass x acceleration). Methods : we have calculated the equations of motion (${\Sigma}F=0$, ${\Sigma}{\tau}=0$, ${\Sigma}F=ma$, ${\Sigma}{\tau}=Ia$) to investigate the reaction force on the elbow joint during elbow flexion, extension by means of the simplified free-body technique for coplanar forces. Results : we found that the reaction force on the elbow joint during elbow flexion, extention as constant acceleration motion is more than constant velocity, static motion. Also, we found that the relation between during flexion and during extension like this ; $J_{flexion}$ < $J_{extension}$.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.49-55
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• 2002

A decrease in the birthrate and aging are progressing in Japan and several countries. In that society, it is important that physically weak persons such as elderly persons are able to take care of themselves. We have been developing exoskeletal robots for human (especially for physically weak persons) motion support. In this study, the controller controls the angular position and impedance of the exoskeltal robot system using multiple fuzzy-neuro controllers based on biological signals that reflect the human subject's intention. Skin surface electromyogram (EMG) signals and the generated wrist force by the human subject during the elbow motion have been used as input information of the controller. Since the activation level of working muscles tends to vary in accordance with the flexion angle of elbow, multiple fuzzy-neuro controllers are applied in the proposed method. The multiple fuzzy-neuro controllers are moderately switched in accordance with the elbow flexion angle. Because of the adaptation ability of the fuzzy-neuro controllers, the exoskeletal robot is flexible enough to deal with biological signal such as EMG. The experimental results show the effectiveness of the proposed controller.

• Journal of Biosystems Engineering
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• v.38 no.2
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• pp.138-148
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• 2013

Purpose: Determining an appropriate path is a top priority in order for a robot to maneuver in a dynamically efficient way especially in a pick-and-place task. In a non-standardized work environment, current robot arm executes its motion based on the kinematic displacements of joint variables, though resulting motion is not dynamically optimal. In this research we suggest analyzing and applying motion patterns of the human arm as an alternative to perform near optimum motion trajectory for arbitrary pick-and-place tasks. Methods: Since the motion of a human arm is very complicated and diverse, it was simplified into two links: one from the shoulder to the elbow, and the other from the elbow to the hand. Motion patterns were then divided into horizontal and vertical components and further analyzed using kinematic and dynamic methods. The kinematic analysis was performed based on the D-H parameters and the dynamic analysis was carried out to calculate various parameters such as velocity, acceleration, torque, and energy using the Newton-Euler equation of motion and Lagrange's equation. In an attempt to assess the efficacy of the analyzed human motion pattern it was compared to the virtual motion pattern created by the joint interpolation method. Results: To demonstrate the efficacy of the human arm motion mechanical and dynamical analyses were performed, followed by the comparison with the virtual robot motion path that was created by the joint interpolation method. Consequently, the human arm was observed to be in motion while the elbow was bent. In return this contributed to the increase of the manipulability and decrease of gravity and torque being exerted on the elbow. In addition, the energy required for the motion decreased. Such phenomenon was more apparent under vertical motion than horizontal motion patterns, and in shorter paths than in longer ones. Thus, one can minimize the abrasion of joints by lowering the stress applied to the bones, muscles, and joints. From the perspectives of energy and durability, the robot arm will be able to utilize its motor most effectively by adopting the motion pattern of human arm. Conclusions: By applying the motion pattern of human arm to the robot arm motion, increase in efficiency and durability is expected, which will eventually produce robots capable of moving in an energy-efficient manner.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.764-767
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• 2009

Motion capture systems allow to measure the precise position of markers on the human body in real time. These captured motion data, the marker position data, have to be fitted by a human skeleton model to represent the motion of the human. Typical human skeleton models approximate the joints using a ball joint model. However, because this model cannot represent the human skeleton precisely, errors between the motion data and the movements of the simplified human skeleton model happen. We propose in this paper a method for measuring a translation component of wrist, and elbow joints on upper limb using optical motion capture system. Then we study the errors between the ball joint model and acquired motion data. In addition, we discuss the problem to estimate motion of human joint using optical motion capture system.

• Korean Journal of Applied Biomechanics
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• v.20 no.2
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• pp.117-127
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• 2010

The axes of upper forearm coordinate system have been considered as principal axis of each segment which was component of elbow joint. The purpose of this study was to verify whether the mean direction(principal axis) of instantaneous axes of rotation for pure flexion/extension motion coincided with the flexion/extension axis of upper forearm coordinate system. The same procedure was done for pronation/supination motion. Furthermore, it was tested indirectly that there was an interaction effect between the two rotational motions. The results showed that most segment coordinate axes statistically were not consistent with the mean directions of flexion/extension and pronation/supination axes of rotation. From the results, it would be concluded that the ISB coordinate systems was proved to be a little valid for human movement analysis. There also was an effect of pronation/supination angles on flexion/extension motion.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.205-211
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• 2007

In this paper, the prototype of surface EMG (ElectroMyoGram) sensor is developed for the robotic rehabilitation applications, and the developed sensor is composed of the electrodes, analog signal amplifiers, analog filters, ADC (analog to digital converter), and DSP (digital signal processor) for coding the application example. Since the raw EMG signal is very low voltage, it is amplified by about one thousand times. The artifacts of amplified EMG signal are removed by using the band-pass filter. Also, the processed analog EMG signal is converted into the digital form by using ADC embedded in DSP. The developed sensor shows approximately the linear characteristics between the amplitude values of the sensor signals measured from the biceps brachii of human upper arm and the joint angles of human elbow. Finally, to show the performance of the developed EMG sensor, we suggest the application example about the real-time human elbow motion acquisition by using the developed sensor.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.199-202
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• 2002

We described a real-time 3D computer vision system called MIMIC(Motion interface f Motion information Capture system) that can capture and save motion of an actor. This system analyzes input images from vision sensors and searches feature information like a head, hands, and feet. Moreover, this estimates intermediated joints as an elbow and hee using feature information and makes 3D human model having 20 joints. This virtual human model mimics the motion of an actor in real-time. Therefore this system can realize the movement of an actor unaffectedly because of making intermediated joint for complete human body contrary to other marker-free motion capture system.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.188-196
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• 2006

During the communication and interaction with a human using motions or gestures, a humanoid robot needs not only to look like a human but also to behave like a human to make sure the meanings of the motions or gestures. Among various human-like behaviors, arm motions of the humanoid robot are essential for the communication with people through motions. In this work, a mathematical representation for characterizing human arm motions is first proposed. The human arm motions are characterized by the elbow elevation angle which is determined using the position and orientation of human hands. That representation is mathematically obtained using an approximation tool, Response Surface Method (RSM). Then a method to generate human-like arm motions in real time using the proposed representation is presented. The proposed method was evaluated to generate human-like arm motions when the humanoid robot was asked to move its arms from a point to another point including the rotation of its hand. The example motion was performed using the KIST humanoid robot, MAHRU.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.24-29
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• 2014

This paper proposes a kinect-based human motion recognition model for the 3D contents control after tracking the human body gesture through the camera in the infrared kinect project. The proposed human motion model in this paper computes the distance variation of the body movement from shoulder to right and left hand, wrist, arm, and elbow. The human motion model is classified into the movement directions such as the left movement, right movement, up, down, enlargement, downsizing. and selection. The proposed kinect-based human motion recognition model is very natural and low cost compared to other contact type gesture recognition technologies and device based gesture technologies with the expensive hardware system.