Posts Tagged Shoulder
Stroke survival rates have improved a lot over the last few years. Stroke was once the third leading cause of death in the United States, but it fell to fourth place in 2008 and fifth place in 2013. Today, strokes claim an average of 129,000 American lives every year. Reducing stroke deaths in America is a great improvement, but we still have a long way to go in improving the lives of stroke survivors.
Stagnant recovery rates and low quality of life for stroke survivors are unfortunately very common. Just 10% of stroke survivors make a full recovery. Only 25% of all survivors recover with minor impairments. Nearly half of all stroke survivors continue to live with serious impairments requiring special care, and 10% of survivors live in nursing homes, skilled nursing facilities, and other long-term healthcare facilities. It’s easy to see why stroke is the leading cause of long-term disability in the United States. By 2030, it’s estimated that there could be up to 11 million stroke survivors in the country.
Traditionally, stroke rehabilitation in America leaves much to be desired in terms of recovery and quality of life. There is a serious gap between stroke patients being discharged and transitioning to physical recovery programs. In an effort to improve recovery and quality of life, the American Heart Association has urged the healthcare community to prioritize exercise as an essential part of post-stroke care.
Unfortunately, too few healthcare professionals prescribe exercise as a form of therapy for stroke, despite its many benefits for patients. Many stroke survivors are not given the skills, confidence, knowledge, or tools necessary to follow an exercise program. However, that can change.
With the right recovery programs that prioritize exercise for rehabilitation, stroke survivors can “relearn” crucial motors skills to regain a high quality of life. Thanks to a phenomenon known as neuroplasticity, even permanent brain damage doesn’t make disability inevitable.
A stroke causes loss of physical function because it temporarily or permanently damages the parts of the brain responsible for those functions. The same damage is also responsible for behavioral and cognitive changes, which range from memory and vision problems to severe depression and anger. Each of these changes correspond to a specific region of the brain that was damaged due to stroke.
For example, damage in the left hemisphere of your brain will cause weakness and paralysis on the right side of your body. If a stroke damages or kills brain cells in the right hemisphere, you may struggle to understand facial cues or control your behavior. However, brain damage due to stroke is not necessarily permanent.
For more Visit Site —> Stroke Recovery Exercises for Your Whole Body
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Arm, Balance, Core, gait, Hand, leg, saebo, Shoulder, Stroke Exercises, UE, UL, Upper Extremity, upper limb
Abstract:
The growing importance of Kinect as a tool for clinical assessment and rehabilitation is due to its portability, low cost and markerless system for human motion capture. However, the accuracy of Kinect in measuring three-dimensional body joint center locations often fails to meet clinical standards of accuracy when compared to marker-based motion capture systems such as Vicon. The length of the body segment connecting any two joints, measured as the distance between three-dimensional Kinect skeleton joint coordinates, has been observed to vary with time. The orientation of the line connecting adjoining Kinect skeletal coordinates has also been seen to differ from the actual orientation of the physical body segment. Hence we have proposed an optimization method that utilizes Kinect Depth and RGB information to search for the joint center location that satisfies constraints on body segment length and as well as orientation. An experimental study have been carried out on ten healthy participants performing upper body range of motion exercises. The results report 72% reduction in body segment length variance and 2° improvement in Range of Motion (ROM) angle hence enabling to more accurate measurements for upper limb exercises.
I. Introduction
Body joint movement analysis is extremely essential for health monitoring and treatment of patients with neurological disorders and stroke. Chronic hemiparesis of the upper extremity following a stroke causes major hand movement limitations. There is possibility of permanent reduction in muscle coactivation and corresponding joint torque patterns due to stroke [1]. Several studies suggest that abnormal coupling of shoulder adductors with elbow extensors and shoulder abductors with elbow flexors often leads to some stereotypical movement characteristics exhibited by severe stroke patients [2]. Therefore continuous and effective rehabilitation therapy is absolutely essential to monitor and control such abnormalities. There is a substantial need for home-based rehabilitation post-clinical therapy.
Source: Accurate upper body rehabilitation system using kinect – IEEE Xplore Document
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biomedical measurement, body segment orientation, Cameras, elbow, Gait Analysis, Kinect, Kinect Depth, Length measurement, Motion measurement, Motion segmentation, optimization method, patient rehabilitation, physical body segment, RGB information, Shoulder, Skeleton, upper body, upper limb exercises, VICON
Abstract:
Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation with Robotic devices have been proposed in the literature to improve rehabilitation outcomes. In this work, we present the combined use of a hybrid robotic system with an EEG-based Brain-Machine Interface to detect the user’s movement intentions to trigger the assistance. The platform has been tested in a single session with a stroke patient. The results show how the patient could successfully interact with the BMI and command the assistance of the hybrid system with low latencies. Also, the Feedback Error Learning controller implemented in this system could adjust the required FES intensity to perform the task.
I. Introduction
Stroke is a leading cause of adult disability around the world. A large number of stroke survivors are left with a unilateral arm or leg paralysis. After completing conventional rehabilitation therapy, a significant number of stroke survivors are left with limited reaching and grasping capabilities [1].
Source: Combining a hybrid robotic system with a bain-machine interface for the rehabilitation of reaching movements: A case study with a stroke patient – IEEE Xplore Document
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biomechanics, Brain computer interfaces, electroencephalography, Electromyography, exoskeletons, hybrid, Iron, medical disorders, medical robotics, Muscles, patient rehabilitation, robots, Shoulder, visualization
Abstract:
We developed a tele-rehabilitation system to improve community rehabilitation for patients who are discharged early from hospital. The developed tele-rehabilitation system consists of devices designed to reduce the physical and economic burden on users while promoting optimum user movement. A Backend-as-a-Service cloud computing service was used for the communication between terminals. A non-contact sensor, Kinect, was used to measure movement. In addition, we used a three-dimensional (3D) display to present 3D images using binocular parallax, to encourage smooth movement of patients. We used this system for stroke patients and found improvements in task-performance time, smoothness of movements, and range of motion in all patients. No major issues occurred during the tele-rehabilitation. These results demonstrated the high operability and efficacy of our cloud service-based 3D virtual reality tele-rehabilitation system.
Source: IEEE Xplore Document – Trial operation of a cloud service-based three-dimensional virtual reality tele-rehabilitation system for stroke patients
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3D display, BaaS, cloud computing, Economics, elbow, Hospitals, Shoulder, Tele-rehabilitation, Three-dimensional displays, Virtual Reality Rehabilitation
Abstract
Introduction Patients with acquired brain impairments require intensive, task-specific training to maximise upper limb recovery. Current evidence suggests, however, that they rarely achieve this. The purpose of this study was to describe the amount of practice that can be achieved by patients with acquired brain impairment during intensive upper limb treatment within a public hospital, and to examine the strategies used by therapists to maximise practice.
Method A secondary analysis was conducted using data from a previously published randomised trial. The training received by 20 people with acquired brain impairment over the 6-week trial period was recorded. The strategies used by therapists to maximise practice were also noted.
Results Over the 6-week period, 45 hours of upper limb training was provided. The median (interquartile range) amount of actual practice achieved by patients was 59 (54–63) minutes per day, with a median (interquartile range) of 186 (50–330) repetitions of active movement. Patients’ practice was maximised through the use of task-specific feedback, practice books, counters, environmental cues and stopwatches. In addition, therapists provided coaching as well as ensuring tasks were goal-oriented, measurable and patient-driven.
Conclusion Described strategies enabled patients with acquired brain impairment to practise upper limb tasks at intensities greater than currently reported in the literature.
Source: Strategies for increasing the intensity of upper limb task-specific practice after acquired brain impairment: A secondary analysis from a randomised controlled trial
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ABI, Arm, exercise training, Hand, Shoulder, Stroke, UE, UL, Upper Extremity, upper limb
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
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elbow, exoskeletons, fuzzy hitting control law, Joints, PID sliding surface, rehabilitation, robots, Shoulder, Sliding mode control, sliding mode control upper-limb exoskeleton, Trajectory, Wrist
TBI Rehabilitation 