scholarly journals A New Skeleton Model and the Motion Rhythm Analysis for Human Shoulder Complex Oriented to Rehabilitation Robotics

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Song Zhibin ◽  
Ma Tianyu ◽  
Nie Chao ◽  
Niu Yijun
Keyword(s):  
Rehabilitation Robotics ◽  
Integrated System ◽  
Motor Dysfunction ◽  
Vector Method ◽  
Skeleton Model ◽  
Upper Limb Rehabilitation ◽  
Training Strategy ◽  
Biomechanical Models ◽  
Shoulder Complex ◽  
Robotics Design

Rehabilitation robotics has become a widely accepted method to deal with the training of people with motor dysfunction. In robotics medium training, shoulder repeated exercise training has been proven beneficial for improving motion ability of human limbs. An important and difficult paradigm for motor function rehabilitation training is the movement rhythm on the shoulder, which is not a single joint but complex and ingenious combination of bones, muscles, ligaments, and tendons. The most robots for rehabilitation were designed previously considering simplified biomechanical models only, which led to misalignment between robots and human shoulder. Current biomechanical models were merely developed for rehabilitation robotics design. This paper proposes a new hybrid spatial model based on joint geometry constraints to describe the movement of the shoulder skeletal system and establish the position analysis equation of the model by a homogeneous coordinate transformation matrix and vector method, which can be used to calculate the kinematics of human-robot integrated system. The shoulder rhythm, the most remarkable particularity in shoulder complex kinematics and important reference for shoulder training strategy using robotics, is described and analyzed via the proposed skeleton model by three independent variables in this paper. This method greatly simplifies the complexity of the shoulder movement description and provides an important reference for the training strategy making of upper limb rehabilitation via robotics.

Survey of Biomechanical Models for the Human Shoulder Complex

2008 ◽  
Author(s):  
Xuemei Feng ◽  
Jingzhou Yang ◽  
Karim Abdel-Malek
Keyword(s):  
Biomechanical Models ◽  
Shoulder Complex

scholarly journals Inertial-Robotic Motion Tracking in End-Effector-Based Rehabilitation Robots

2020 ◽  
Vol 7 ◽  
Author(s):  
Arne Passon ◽  
Thomas Schauer ◽  
Thomas Seel
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Inertial Sensor ◽  
Ground Truth ◽  
Rehabilitation Robotics ◽  
Measurement Information ◽  
Indoor Environments ◽  
Upper Arm ◽  
End Effector ◽  
Upper Limb Rehabilitation

End-effector-based robotic systems provide easy-to-set-up motion support in rehabilitation of stroke and spinal-cord-injured patients. However, measurement information is obtained only about the motion of the limb segments to which the systems are attached and not about the adjacent limb segments. We demonstrate in one particular experimental setup that this limitation can be overcome by augmenting an end-effector-based robot with a wearable inertial sensor. Most existing inertial motion tracking approaches rely on a homogeneous magnetic field and thus fail in indoor environments and near ferromagnetic materials and electronic devices. In contrast, we propose a magnetometer-free sensor fusion method. It uses a quaternion-based algorithm to track the heading of a limb segment in real time by combining the gyroscope and accelerometer readings with position measurements of one point along that segment. We apply this method to an upper-limb rehabilitation robotics use case in which the orientation and position of the forearm and elbow are known, and the orientation and position of the upper arm and shoulder are estimated by the proposed method using an inertial sensor worn on the upper arm. Experimental data from five healthy subjects who performed 282 proper executions of a typical rehabilitation motion and 163 executions with compensation motion are evaluated. Using a camera-based system as a ground truth, we demonstrate that the shoulder position and the elbow angle are tracked with median errors around 4 cm and 4°, respectively; and that undesirable compensatory shoulder movements, which were defined as shoulder displacements greater ±10 cm for more than 20% of a motion cycle, are detected and classified 100% correctly across all 445 performed motions. The results indicate that wearable inertial sensors and end-effector-based robots can be combined to provide means for effective rehabilitation therapy with likewise detailed and accurate motion tracking for performance assessment, real-time biofeedback and feedback control of robotic and neuroprosthetic motion support.

scholarly journals Robot-Assisted and Device-Based Rehabilitation of the Upper Extremity

2017 ◽  
Vol 01 (03) ◽  
pp. E242-E246 ◽  
Author(s):  
Michael Sailer ◽  
Catherine Sweeney-Reed ◽  
Juliane Lamprecht
Keyword(s):  
Upper Limb ◽  
Clinical Studies ◽  
Technological Progress ◽  
Motor Dysfunction ◽  
Robot Assisted ◽  
Central Nervous System Damage ◽  
Upper Limb Rehabilitation ◽  
Limited Health ◽  
Limb Rehabilitation

AbstractNeurorehabilitation of patients with upper limb motor dysfunction due to central nervous system damage still lacks adequate standardization. During the last decade, robot- and device-assisted rehabilitation has become more feasible for the treatment of functional disorders of the upper limb after stroke. Here we present an overview of technological aspects and differential use of devices for upper limb rehabilitation as well as a review of relevant clinical studies. We also discuss the potential for standardized evaluation in the context of limited health care resources. The effectiveness of device-assisted therapy, in comparison to conventional approaches, remains a matter of debate, largely due to the heterogeneous design of the available clinical studies. However, we believe that a better understanding of the timing, intensity, and quality of upper limb rehabilitation, as well as technological progress, will lead to the establishment of a central role for robot- and device-assisted rehabilitation in the next decade.

Review of biomechanical models for human shoulder complex

2010 ◽  
Vol 1 (3) ◽  
pp. 271 ◽  
Author(s):  
Jingzhoug Yang ◽  
Xuemei Feng ◽  
Joo H. Kim ◽  
Sudhakar Rajulu
Keyword(s):  
Biomechanical Models ◽  
Shoulder Complex

scholarly journals Upper limb rehabilitation robotics after stroke: A perspective from the University of Padua, Italy

2009 ◽  
Vol 41 (12) ◽  
pp. 981-985 ◽  
Author(s):  
S Masiero ◽  
E Carraro ◽  
C Ferraro ◽  
P Gallina ◽  
A Rossi ◽  
...  
Keyword(s):  
Upper Limb ◽  
Rehabilitation Robotics ◽  
Upper Limb Rehabilitation ◽  
University Of Padua ◽  
The University ◽  
Limb Rehabilitation
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