Analysis of Knob Traces Based on Changes in Armrest’s Length and Central Axis Location of Grahamizer

2012 ◽  
Author(s):  
Jong Hyun Kim ◽  
Keyoung Jin Chun ◽  
Jae Soo Hong ◽  
Chang Won Kim ◽  
Jung Hwa Hong
Keyword(s):  
Shoulder Joint ◽  
Central Axis ◽  
Upper Body ◽  
Upper Limb Rehabilitation ◽  
Arm Support ◽  
Medial Rotation ◽  
Lateral Rotation ◽  
Joint Motions ◽  
Limb Rehabilitation ◽  
Rehabilitation Exercise

The hemiparalysis, which is a widely known side effect of the disease, requires consistent and accurate rehabilitation exercise treatment. The Grahamizer is a representative piece of equipment for such treatment. Because it consists of a double pivot system, under exercise, the irregularly moving pivots could create an unintended movement and malfunction. Using the Grahamizer, this study analyzed movement patterns based on changes in the armrest’s length and the central axis location for a stable and accurate upper limb rehabilitation exercise. Eight healthy subjects participated in the study. The Grahamizer, which allows the length of the armrest and the central axis location to be adjusted, was used for experimental equipment. The length could be adjusted to five levels (280mm, 220mm, 160mm, 100mm, and 40mm), and the location ranged from 5 levels to 1 level based on the length of the arm support (280mm: 5positions, 220mm: 4positions, 160mm: 3positions, 100mm: 2positions, 40mm: 1position). A marker located above a knob traced the knob’s movements. The experiment was conducted three times. Each subject held the knob and implemented rotational movements passively, with an angular velocity of 30°/s. After integrating the subjects’ movement traces, the tendency was analyzed. A previous study provided an analysis of the elbow and shoulder joint movements under a normal upper-body rotation movement. This study on movement traces was conducted based on those results. Longer armrest lengths and greater distances between the central axis location and knob showed greater stability for the rotation movements. Remarkable results were found for changes in the axis location. However, smaller distances between the axis location and knob revealed larger movement traces. A previous study found, when a counterclockwise rotation was defined as 0°∼360°, that an elbow motion of 0°∼180° is flexion and 180°∼360° is extension. The shoulder joint motions are similar: 0°∼90°: medial rotation, 90°∼180°: lateral rotation, 180°∼270° medial rotation, and 270°∼360°: lateral rotation. According to the previous study, with a larger trace (smaller distance between the axis location and knob), the rotation movements of the elbow and shoulder are more accurate from 0° to 180° than from 180° to 360°. The experiment confirmed that the Grahamizer’s armrest axis location has an impact on movement traces, and changes in the traces prevented the intended joint exercise. Under the circumstances, the location is an important design variable when developing the Grahamizer.

Design and Development of Fun Lean Augmented and Virtual Reality Prototypes for Hand and Upper Limb Rehabilitation

2020 ◽  
Author(s):  
Chien-Sing Lee ◽  
Pei-Yee Tan ◽  
Hong-Wei Wong
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
Occupational Therapy ◽  
Activity Level ◽  
Leap Motion ◽  
Hand Rehabilitation ◽  
Cognitive Health ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation ◽  
Rehabilitation Exercise

Lack of motivation to carry out rehabilitation exercise from a hand injury or stroke is one of the most challenging aspects faced by Occupational Therapy (OT) and Certified Occupational Therapy Assistants (COTA). Some patients refuse to exercise due to behavioral, psychological, or cognitive reasons. We hypothesize that recovery to their former activity level and strength can be quickened if we develop Augmented Reality (AR)/Virtual Reality (VR) games which add fun into rehabilitative hand exercises. A physical card game for hand rehabilitation, which contains puzzle pieces and rehabilitative exercise instructions, is designed and developed to trigger the display of an Augmented Reality virtual reward upon completion of the puzzle. User testing results are promising. Users find it easy to use, supportive, efficient, exciting and interesting; suitable for either individual or collaborative play. Being object-oriented, it is also scalable, extensible and easily portable. An extended Leap-Motion-enhanced AR environment for limb rehabilitation is being developed. We hope that both will improve physical, mental and socio-cognitive health.

Musculoskeletal Analysis of Upper Limb Rehabilitation Robot Prototype

2016 ◽  
Vol 833 ◽  
pp. 196-201 ◽  
Author(s):  
Shahrol Mohamaddan ◽  
Annisa Jamali ◽  
Noor Aliah Abd Majid ◽  
Mohamad Syazwan Zafwan Mohamad Suffian
Keyword(s):  
Upper Limb ◽  
Vertical Movement ◽  
Human Model ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
The Third ◽  
Hardware Development ◽  
Limb Rehabilitation ◽  
Human Upper Limb ◽  
Rehabilitation Exercise

Stroke is the third largest cause of death in Malaysia. Different approaches including hardware development and simulation were conducted to support the conventional rehabilitation courses. New upper limb rehabilitation robot prototype was developed for this research. The prototype consists of horizontal and vertical movement exercise. The prototype was modeled and simulated using ergonomics optimization software known as AnyBody. This paper presents the analysis of human upper limb muscles during rehabilitation exercise using virtual human model. The result shows that eleven muscle areas were affected during the rehabilitation exercise using new prototype.

scholarly journals Configuration Design of an Upper Limb Rehabilitation Robot with a Generalized Shoulder Joint

2021 ◽  
Vol 11 (5) ◽  
pp. 2080
Author(s):  
Hao Yan ◽  
Hongbo Wang ◽  
Peng Chen ◽  
Jianye Niu ◽  
Yuansheng Ning ◽  
...  
Keyword(s):  
Upper Limb ◽  
Shoulder Joint ◽  
Configuration Model ◽  
Configuration Design ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Robots ◽  
Closed Chain ◽  
Limb Rehabilitation ◽  
Human Upper Limb

For stroke patients with upper limb motor dysfunction, rehabilitation training with the help of rehabilitation robots is a social development trend. Existing upper limb rehabilitation robots have difficulty fully fitting the complex motion of the human shoulder joint and have poor human–robot compatibility. In this paper, based on the anatomical structure of the human upper limb, an equivalent mechanism model of the human upper limb is established. The configuration synthesis of the upper limb rehabilitation mechanism was carried out, a variety of shoulder joint man–machine closed-chain Θs and shoulder elbow human–machine closed-chain Θse configuration combinations were synthesized, and the configuration model with compatibility and reduced moment conduction attenuation was selected from them. Two configurations, 2Pa1P3Ra and 5Ra1P, are proposed for the generalized shoulder joint mechanism of the robot. The closed-chain kinematic models of the two configurations are established, and the velocity Jacobian matrix is obtained. Motion performance analysis, condition reciprocal analysis and operability ellipsoid analysis of different configuration design schemes were carried out in different operation planes. The results show that in the normal upper limb posture of the human body, the 5Ra1P configuration of the shoulder joint has better kinematic performance. Finally, on this basis, an upper limb rehabilitation robot prototype with good human–computer compatibility is developed, and its moving space was verified.

scholarly journals Robotics in physical medicine and neurorehabilitation

2021 ◽  
Vol 74 (1-2) ◽  
pp. 50-53
Author(s):  
Vesna Pausic ◽  
Grigorije Jovanovic ◽  
Svetlana Simic
Keyword(s):  
Upper Limb ◽  
Rehabilitation Robotics ◽  
Robotic Systems ◽  
Upper Body ◽  
Physical Medicine ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Robots ◽  
Robotic Devices ◽  
The 1960S ◽  
Limb Rehabilitation

Introduction. Robots have been used for rehabilitation purposes since the 1960s. The aim of this paper is to present the application of robotics in physical medicine and rehabilitation with special reference to robotic devices used in rehabilitation. Material and Methods. The paper uses literature related to the application of robotics in medicine and rehabilitation. The literature review was conducted using the following databases: Serbian Library Consortium for Coordinated Acquisition, Medical Literature Analysis and Retrieval System, Google Scholar, Science Citation Index, and portal of Croatian scientific journals ?Hrcak?. Development of robotics in rehabilitation. Nowadays, there are a great number of different robotic systems for rehabilitation. Robotics in rehabilitation is of utter importance because it works on the principle of neuroplasticity. Robots for lower limb rehabilitation. These robotic systems are most often in the form of exoskeletons. Robots for upper limb rehabilitation. Upper limb rehabilitation robots are therapeutic devices that help or provide support for arm or hand movements. Robot for upper body rehabilitation. Robot ?Tymo?. Conclusion. By using robots in physical medicine and neurorehabilitation, a faster and more complete functional recovery of the patient can be achieved.

Kinematic Analysis of Elbow and Scapula Based on Changes in Arm Support Length and Central Axis Location Through Rotational Motion of Upper Limb

2012 ◽  
Author(s):  
Jae Soo Hong ◽  
Keyoung Jin Chun ◽  
Jong Hyun Kim ◽  
Jung Hwa Hong
Keyword(s):  
Upper Limb ◽  
Central Axis ◽  
Upper Body ◽  
Angular Width ◽  
Long Distance ◽  
Rotational Movement ◽  
Design Variables ◽  
Flexion Extension ◽  
Arm Support ◽  
Support Length

An increase in the aging population around the world and in degenerative diseases has caused an epidemic of stroke. Hence, rehab equipment for treating its after-effects has been actively developed. A repeated upper-body rehab exercise is required and this exercise can only yield good results when its accurate motion is guided by a therapist. However, few kinematics studies have been conducted based on design variables such as changes in the rotational central axis and body measurement. So, this study analyzed the angular changes in two motions of the elbow (Flexion-Extension: F-E, Pronation-Supination: P-S) and three motions of the scapula (Anterior-Posterior tilt: A-P, Internal-External rotation: I-E, Upward-Downward rotation: U-D) based on changes in the arm support length and central axis location. Eight healthy subjects participated in this study. Rehabilitation equipment for the upper limb, which can be adjusted to different arm support lengths and central axis locations, was used as the experimental equipment. The length could be adjusted to five levels (280 mm, 220 mm, 160 mm, 100 mm, and 40 mm). In the case of an experiment involving changes in the axis locations, the length was fixed as 280 mm, which allowed five different axis locations. Each subject implemented a rotational movement passively at an angular velocity of 30°/s. In this study, we observed changes in the motion patterns of the upper-limb rotational movement based on the length and the location. The patterns based on the two design variables revealed a consistent tendency under the elbow (forearm) and the scapula (shoulder rhythm). Yet, three scapula motions showed little changes in the angular width, and only I-E showed an angular width of 5°. First, with respect to the tendency of the five motions based on changes in the lengths, the prolonged length showed a decreased angular width. Second, in terms of the tendency of the five motions based on changes in the locations, a relatively long distance between the handle and the axis (Location 1 → Location 5) confirmed a decreased angular width owing to a relatively small rotational movement at Location 5. The F-E motion of the elbow clearly showed two time cycles per rotation. Other motions revealed one time cycle per rotation. With respect to the upper-body rotational movement, we confirmed that motions related to the forearm were more active than motions related to the shoulder.

scholarly journals Prediction of Passive Torque on Human Shoulder Joint Based on BPANN

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shuyang Li ◽  
Paolo Dario ◽  
Zhibin Song
Keyword(s):  
Shoulder Joint ◽  
Measurement Data ◽  
Prediction Method ◽  
Upper Limb Rehabilitation ◽  
Passive Resistance ◽  
Passive Torque ◽  
High Prediction ◽  
Robotic Devices ◽  
Limb Rehabilitation ◽  
Male Subjects

In upper limb rehabilitation training by exploiting robotic devices, the qualitative or quantitative assessment of human active effort is conducive to altering the robot control parameters to offer the patients appropriate assistance, which is considered an effective rehabilitation strategy termed as assist-as-needed. Since active effort of a patient is changeable for the conscious or unconscious behavior, it is considered to be more feasible to determine the distributions of the passive resistance of the patient’s joints versus the joint angle in advance, which can be adopted to assess the active behavior of patients combined with the measurement of robotic sensors. However, the overintensive measurements can impose a burden on patients. Accordingly, a prediction method of shoulder joint passive torque based on a Backpropagation neural network (BPANN) was proposed in the present study to expand the passive torque distribution of the shoulder joint of a patient with less measurement data. The experiments recruiting three adult male subjects were conducted, and the results revealed that the BPANN exhibits high prediction accurate for each direction shoulder passive torque. The results revealed that the BPANN can learn the nonlinear relationship between the passive torque and the position of the shoulder joint and can make an accurate prediction without the need to build a force distribution function in advance, making it possible to draw up an assist-as-needed strategy with high accuracy while reducing the measurement burden of patients and physiotherapists.

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