scholarly journals Kinematic Analysis During Straight Line Free Swimming in Horses: Part 1 - Forelimbs

2021 ◽  
Vol 8 ◽  
Author(s):  
Emma Santosuosso ◽  
Renaud Leguillette ◽  
Tatiana Vinardell ◽  
Silvio Filho ◽  
Shannon Massie ◽  
...  
Keyword(s):  
Sports Medicine ◽  
Elbow Flexion ◽  
Carpal Bone ◽  
Joint Angles ◽  
Straight Line ◽  
Flexion Extension ◽  
Angular Velocities ◽  
Equine Sports ◽  
Swimming Kinematics ◽  
Rehabilitation Exercise

Background: Swimming is used for rehabilitation and conditioning purposes in equine sports medicine despite the lack of understanding of equine swimming kinematics. The aim of this study was to assess forelimb joints kinematics (elbow, carpus, and fetlock) in swimming horses. The specific objectives were 1- to calculate and compare joint angles in swimming vs. passive mobilizations (PM), 2- to determine joint angular velocities during a swimming stride cycle.Methods: Eleven elite endurance horses swam in a 100-m straight pool. Underwater (swimming) and overground (PM) videos were recorded from the horses' left side. Joint markers were applied on the lateral hoof wall, lateral metacarpal epicondyle, ulnar carpal bone, lateral humeral epicondyle, and the greater tubercle of humerus, from which elbow, carpus and fetlock angles, and angular velocities were obtained. As a reference, maximal fetlock, carpus, and elbow flexion/extension angles were determined during PM overground. Differences between angle extrema, angular velocities and range of motion (ROM) were compared.Results: Carpus and fetlock ROM were significantly smaller (p < 0.001) during swimming when compared with PM, while there was no difference in elbow ROM between both situations. The carpus had the greatest ROM of all joints during swimming. Absolute angular velocities values of all joints during swimming were greater during retraction than protraction (p < 0.001). When compared to other joints during protraction, the carpus joint reached the highest angular velocity.Conclusion: Swimming, as a rehabilitation exercise, has the potential to benefit horses where great elbow ROM with a moderate carpus and fetlock extension are wanted.

scholarly journals Recording of length-tension relationship of elbow flexors and extensors by varying elbow angle in human

2021 ◽  
Vol 64 ◽  
pp. S46-S50
Author(s):  
Hanjabam Barun Sharma ◽  
Arani Das ◽  
Prashant Tayade ◽  
Kishore K. Deepak
Keyword(s):  
Skeletal Muscle ◽  
Muscle Length ◽  
Elbow Flexion ◽  
Isometric Strength ◽  
Undergraduate Teaching ◽  
Joint Angles ◽  
Custom Made ◽  
Flexion Extension ◽  
Relationship Of ◽  
Living Person

Objectives: The concept of length-tension relationship in skeletal muscle can be studied in a living person by demonstrating the relationship between isometric strength and joint angles. There is lack of an effective practical module to demonstrate this concept in living person, hence the study was planned. Materials and Methods: A simple, feasible and novel practical is designed using a custom-made isometric elbow flexion-extension exercising instrument, in which isometric elbow strength is measured using a dynamometer against various elbow joint angles measured using a goniometer. Result: Elbow isometric strength varied across its joint angles and was maximum at the optimum angle, which was 90°. Conclusion: We propose a simple and novel practical to understand the skeletal muscle length-tension relationship in a living person partly, by using the angle-strength relationship for undergraduate teaching in physiology.

scholarly journals Synergies reciprocally relate end-effector and joint-angles in rhythmic pointing movements

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Tim A. Valk ◽  
Leonora J. Mouton ◽  
Egbert Otten ◽  
Raoul M. Bongers
Keyword(s):  
Dynamical System ◽  
Degrees Of Freedom ◽  
Index Finger ◽  
Elbow Flexion ◽  
Human Action ◽  
Joint Angles ◽  
End Effector ◽  
Action System ◽  
Flexion Extension ◽  
Pointing Movements

AbstractDuring rhythmic pointing movements, degrees of freedom (DOF) in the human action system—such as joint-angles in the arm—are assumed to covary to stabilise end-effector movement, e.g. index finger. In this paper, it is suggested that the end-effector movement and the coordination of DOF are reciprocally related in synergies that link DOF so as to produce the end-effector movement. The coordination of DOF in synergies and the relation between end-effector movement and DOF coordination received little attention, though essential to understand the principles of synergy formation. Therefore, the current study assessed how the end-effector movement related to the coordination of joint-angles during rhythmic pointing across target widths and distances. Results demonstrated that joint-angles were linked in different synergies when end-effector movements differed across conditions. Furthermore, in every condition, three joint-angles (shoulder plane of elevation, shoulder inward-outward rotation, elbow flexion-extension) largely drove the end-effector, and all joint-angles contributed to covariation that stabilised the end-effector. Together, results demonstrated synergies that produced the end-effector movement, constrained joint-angles so that they covaried to stabilise the end-effector, and differed when end-effector movement differed. Hence, end-effector and joint-angles were reciprocally related in synergies—indicating that the action system was organised as a complex dynamical system.

Contributions of Rotations of the Trunk and Upper Extremity to Hand Velocity during Front Crawl Swimming

2002 ◽  
Vol 18 (3) ◽  
pp. 243-256 ◽  
Author(s):  
Carl Payton ◽  
Vasilios Baltzopoulos ◽  
Roger Bartlett
Keyword(s):  
Upper Extremity ◽  
External Rotation ◽  
Elbow Flexion ◽  
The Other ◽  
Position Vector ◽  
Positive Contribution ◽  
Front Crawl ◽  
Relative Contribution ◽  
Flexion Extension ◽  
Angular Velocities

The purpose of this study was to present a method of determining the contributions made by rotations of the trunk and upper extremity to hand velocity during the front crawl pull, and to illustrate this with an example. Six male swimmers performed front crawl trials at their middle distance pace (1.52 ± 0.12 m.s−1). Their underwater arm stroke was recorded from the front and side using video cameras suspended over periscope systems. Recordings were digitized at 50 Hz and the 3-D coordinates of the upper extremity were obtained using a DLT algorithm. Shoulder kinematics (flexion/extension, transverse abduction/adduction, internal/external rotation) and elbow kinematics (flexion/extension) were then calculated. Trunk roll kinematics were obtained by digitizing above-water video recordings of a fin attached to each swimmer’s back. The contribution of each body segment rotation to hand velocity was computed using |ɷ × r| cos ϕ, where ɷ was the segment’s angular velocity, r was the position vector of the hand from the segment’s axis of rotation, and ϕ was the angle between hand velocity vhand/pool and v (where v = ɷ × r). Analysis revealed that shoulder extension was the joint motion primarily responsible for producing hand velocity during the insweep (relative contribution: min 66% to max 118%). This was due to the angular velocities and hand-to-joint axis distances for shoulder extension being greater than those of the other joint motions analyzed. The other rotations at the shoulder also contributed to hand velocity during the insweep, but to a lesser extent (transverse adduction: 13% to 49%; internal rotation: −1% to +40%). On average, elbow flexion accounted for 25% of the hand velocity in the middle of the insweep. Trunk roll did not make a positive contribution to hand velocity during the insweep phase (–3% to –48%), contradicting the findings of previous studies.

scholarly journals Deep Learning-Based Upper Limb Functional Assessment Using a Single Kinect v2 Sensor

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1903 ◽  
Author(s):  
Ye Ma ◽  
Dongwei Liu ◽  
Laisi Cai
Keyword(s):  
Deep Learning ◽  
Upper Limb ◽  
Short Term Memory ◽  
External Rotation ◽  
Kinematic Model ◽  
Elbow Flexion ◽  
Supervised Machine Learning ◽  
Joint Angles ◽  
Kinect V2 ◽  
Flexion Extension

We develop a deep learning refined kinematic model for accurately assessing upper limb joint angles using a single Kinect v2 sensor. We train a long short-term memory recurrent neural network using a supervised machine learning architecture to compensate for the systematic error of the Kinect kinematic model, taking a marker-based three-dimensional motion capture system (3DMC) as the golden standard. A series of upper limb functional task experiments were conducted, namely hand to the contralateral shoulder, hand to mouth or drinking, combing hair, and hand to back pocket. Our deep learning-based model significantly improves the performance of a single Kinect v2 sensor for all investigated upper limb joint angles across all functional tasks. Using a single Kinect v2 sensor, our deep learning-based model could measure shoulder and elbow flexion/extension waveforms with mean CMCs >0.93 for all tasks, shoulder adduction/abduction, and internal/external rotation waveforms with mean CMCs >0.8 for most of the tasks. The mean deviations of angles at the point of target achieved and range of motion are under 5° for all investigated joint angles during all functional tasks. Compared with the 3DMC, our presented system is easier to operate and needs less laboratory space.

scholarly journals Measurements of Tendon Movement Within the Bicipital Groove After Suprapectoral Intra-articular Biceps Tenodesis in a Cadaveric Model

2021 ◽  
Vol 9 (1) ◽  
pp. 232596712097753
Author(s):  
Brian J. Kelly ◽  
Alan W. Reynolds ◽  
Patrick J. Schimoler ◽  
Alexander Kharlamov ◽  
Mark Carl Miller ◽  
...  
Keyword(s):  
Biceps Tendon ◽  
Full Range ◽  
Elbow Flexion ◽  
Biceps Tenodesis ◽  
Bicipital Groove ◽  
Biceps Tenotomy ◽  
Flexion Extension ◽  
Before And After ◽  
Long Head ◽  
Scapular Motion

Background: Lesions of the long head of the biceps can be successfully treated with biceps tenotomy or tenodesis when surgical management is elected. The advantage of a tenodesis is that it prevents the potential development of a cosmetic deformity or cramping muscle pain. Proponents of a subpectoral tenodesis believe that “groove pain” may remain a problem after suprapectoral tenodesis as a result of persistent motion of the tendon within the bicipital groove. Purpose/Hypothesis: To evaluate the motion of the biceps tendon within the bicipital groove before and after a suprapectoral intra-articular tenodesis. The hypothesis was that there would be minimal to no motion of the biceps tendon within the bicipital groove after tenodesis. Study Design: Controlled laboratory study. Methods: Six fresh-frozen cadaveric arms were dissected to expose the long head of the biceps tendon as well as the bicipital groove. Inclinometers and fiducials (optical markers) were used to measure the motions of the scapula, forearm, and biceps tendon through a full range of shoulder and elbow motions. A suprapectoral biceps tenodesis was then performed, and the motions were repeated. The motion of the biceps tendon was quantified as a function of scapular or forearm motion in each plane, both before and after the tenodesis. Results: There was minimal motion of the native biceps tendon during elbow flexion and extension but significant motion during all planes of scapular motion before tenodesis, with the most motion occurring during shoulder flexion-extension (20.73 ± 8.21 mm). The motion of the biceps tendon after tenodesis was significantly reduced during every plane of scapular motion compared with the native state ( P < .01 in all planes of motion), with a maximum motion of only 1.57 mm. Conclusion: There was a statistically significant reduction in motion of the biceps tendon in all planes of scapular motion after the intra-articular biceps tenodesis. The motion of the biceps tendon within the bicipital groove was essentially eliminated after the suprapectoral biceps tenodesis. Clinical Relevance: This arthroscopic suprapectoral tenodesis technique can significantly reduce motion of the biceps tendon within the groove in this cadaveric study, possibly reducing the likelihood of groove pain in the clinical setting.

Clinical findings in C5-C6 and C5-C7 root palsies with brachial plexus traction lesions

2012 ◽  
Vol 38 (3) ◽  
pp. 237-241 ◽  
Author(s):  
J. A. Bertelli ◽  
M. F. Ghizoni
Keyword(s):  
Brachial Plexus ◽  
External Rotation ◽  
Elbow Flexion ◽  
Clinical Findings ◽  
Hand Strength ◽  
Shoulder Abduction ◽  
Finger Extension ◽  
Root Injury ◽  
Flexion Extension

Stretch injuries of the C5-C7 roots of the brachial plexus traditionally have been associated with palsies of shoulder abduction/external rotation, elbow flexion/extension, and wrist, thumb, and finger extension. Based on current myotome maps we hypothesized that, as far as motion is concerned, palsies involving C5-C6 and C5-C7 root injuries should be similar. In 38 patients with upper-type palsies of the brachial plexus, we examined for correlations between clinical findings and root injury level, as documented by CT tomomyeloscan. Contrary to commonly held beliefs, C5-C7 root injuries were not associated with loss of extension of the elbow, wrist, thumb, or fingers, but residual hand strength was much lower with C5-C7 vs C5-C6 lesions.

Lower-Limb Rehabilitation at Home

2021 ◽  
Vol 13 (2) ◽  
pp. 12-23
Author(s):  
Seanglidet Yean ◽  
Bu-Sung Lee ◽  
Chai Kiat Yeo
Keyword(s):  
Lower Limbs ◽  
Ageing Population ◽  
Joint Angles ◽  
Functional Activities ◽  
State Identification ◽  
Motion State ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation ◽  
Rehabilitation Exercise ◽  
At Home

Ageing causes loss of muscle strength, especially on the lower limbs, resulting in higher risk to injuries during functional activities. The path to recovery is through physiotherapy and adopt customized rehabilitation exercise to assist the patients. Hence, lowering the risk of incorrect exercise at home involves the use of biofeedback for physical rehabilitation patients and quantitative reports for clinical physiotherapy. This research topic has garnered much attention in recent years owing to the fast ageing population and the limited number of clinical experts. In this paper, the authors survey the existing works in exercise assessment and state identification. The evaluation results in the accuracy of 95.83% average classifying exercise motion state using the proposed raw signal. It confirmed that raw signals have more impact than using sensor-fused Euler and joint angles in the state identification prediction model.

scholarly journals Analysis of human-exoskeleton interactions: an elbow flexion/extension case study

2017 ◽  
Vol 20 (sup1) ◽  
pp. S9-S10 ◽  
Author(s):  
S. Bastide ◽  
N. Vignais ◽  
F. Geffard ◽  
B. Berret
Keyword(s):  
Elbow Flexion ◽  
Flexion Extension
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