The rehabilitation process of human fingers is a coupling movement of wearable hand rehabilitation equipment and human fingers, and its design must be based on the kinematics of human fingers. In this paper, the forward kinematics and inverse kinematics models are established for the index finger. Kinematics analysis is carried out. Then a bionic finger rehabilitation robot is designed according to the movement characteristics of the finger, A parallelogram linkage mechanism is proposed to make the joint independent drive, realize the flexion/extension movement, and perform positive kinematics and inverse kinematics analysis on the mechanism. The results show that it conforms to the kinematics of the index finger and can be used as the mechanism model of the finger rehabilitation robot.
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via Design and Kinematics Analysis of a Bionic Finger Hand Rehabilitation Robot Mechanism – IEEE Conference Publication
Nowadays, a stroke is the fourth leading cause of death in the United States. In fact, every 40 seconds, someone in the US is having a stroke. Moreover, around 50% of stroke survivors suffer damage to the upper extremity –. Many actions of treating and recovering from a stroke have been developed over the years, but recent studies show that combining the recovery process with the existing rehabilitation plan provides better results and a raise in the patients quality of life –. Part of the stroke recovery process is a rehabilitation plan . The process can be difficult, intensive and long depending on how adverse the stroke and which parts of the brain were damaged. These processes usually involve working with a team of health care providers in a full extensive rehabilitation plan, which includes hospital care and home exercises.
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via Hand Rehabilitation via Gesture Recognition Using Leap Motion Controller – IEEE Conference Publication
Rehabiliation robotics combined with video game technology provides a means of assisting in the rehabilitation of patients with neuromuscular disorders by performing various facilitation movements. The current work presents ReHabGame, a serious game using a fusion of implemented technologies that can be easily used by patients and therapists to assess and enhance sensorimotor performance and also increase the activities in the daily lives of patients. The game allows a player to control avatar movements through a Kinect Xbox, Myo armband and rudder foot pedal, and involves a series of reach-grasp-collect tasks whose difficulty levels are learnt by a fuzzy interface. The orientation, angular velocity, head and spine tilts and other data generated by the player are monitored and saved, whilst the task completion is calculated by solving an inverse kinematics algorithm which orientates the upper limb joints of the avatar. The different values in upper body quantities of movement provide fuzzy input from which crisp output is determined and used to generate an appropriate subsequent rehabilitation game level. The system can thus provide personalised, autonomously-learnt rehabilitation programmes for patients with neuromuscular disorders with superior predictions to guide the development of improved clinical protocols compared to traditional theraputic activities.
Source: An adaptive self-organizing fuzzy logic controller in a serious game for motor impairment rehabilitation – IEEE Xplore Document
In the rehabilitation training and assessment of upper limbs, the conventional kinematic model treats the arm as a serial manipulator and maps the rotations in the joint space to movements in the Cartesian space. While this model brings simplicity and convenience, and thus has been overwhelming used, its accuracy is limited, especially for the distal parts of the upper limb that execute dexterous movements.
In this paper, a novel kinematic model of the arm has been proposed, which has been inspired by the biomechanical analysis of the forearm and wrist anatomy. One additional parameter is introduced into the conventional arm model, and then both the forward and inverse kinematic models of five parameters are derived for the motion of upper arm medial/lateral rotation, elbow flexion/extension, forearm pronation/supination, wrist flexion/extension and ulnar/radial deviation. Then, experiments with an advanced haptic interface have been designed and performed to examine the presented arm kinematic model. Data analysis revealed that accuracy and robustness can be significantly improved with the new model.
This extended arm kinematic model will help device development, movement training and assessment of upper limb rehabilitation.
Published in: Advanced Robotics and Mechatronics (ICARM), International Conference on
Source: An extended kinematic model for arm rehabilitation training and assessment – IEEE Xplore Document
This paper presents LIGHTarm, a passive gravity compensated exoskeleton for upper-limb rehabilitation suitable for the use both in the clinical environment and at home. Despite the low-cost and not actuated design, LIGHTarm aims at providing remarkable back-drivability in wide portions of the upper-limb workspace. The weight-support and back-drivability features are experimentally investigated on three healthy subjects through the analysis of the EMG activity recorded in static conditions and during functional movements. Kinematics is also monitored. Preliminary results suggest that LIGHTarm sharply reduces muscular effort required for limb support, quite uniformly in the workspace, and that remarkable back-drivability is achieved during the execution of functional movements.
Source: IEEE Xplore Abstract (Abstract) – Static and dynamic characterization of the LIGHTarm exoskeleton for rehabilitation
In this paper we propose a full upper limb exoskeleton for motor rehabilitation of reaching, grasping and releasing in post-stroke patients. The presented system takes into account the hand pre-shaping for object affordability and it is driven by patient’s intentional control through a self-paced asynchronous Motor Imagery based Brain Computer Interface (MI-BCI). The developed antropomorphic eight DoFs exoskeleton (two DoFs for the hand, two for the wrist and four for the arm) allows full support of the manipulation activity at the level of single upper limb joint. In this study, we show the feasibility of the proposed system through experimental rehabilitation sessions conducted with three chronic post-stroke patients. Results show the potential of the proposed system for being introduced in a rehabilitation protocol.
Source: IEEE Xplore Abstract – A full upper limb robotic exoskeleton for reaching and grasping rehabilitation triggered by MI-BCI
Robot-assisted therapy has become an important technology used to restore and reinforce the motor functions of the patients with neuromuscular disorders.
In this paper, we proposed an upper-limb exoskeleton intended to assist the rehabilitation training of shoulder, elbow and wrist. The proposed therapeutic exoskeleton has an anthropomorphic structure able to match the upper-limb anatomy and enable natural human-robot interaction.
A modified sliding mode control (SMC) strategy consisting of a proportional-integral-derivative (PID) sliding surface and a fuzzy hitting control law is developed to guarantee robust tracking performance and reduce the chattering effect. The Lyapunov theorem is utilized to demonstrate the system stability. In order to evaluate the effectiveness of proposed algorithm, several trajectory tracking experiments were conducted based on a real-time control system.
Experimental results are presented to prove that, when compared to the conventional PID controller, the fuzzy SMC strategy can effectively reduce the tracking errors and achieve favorable control performance.
via IEEE Xplore Abstract (Abstract) – Fuzzy sliding mode control of an upper limb exoskeleton for robot-assisted rehabilitation