scholarly journals Joint Angle, Range of Motion, Force, and Moment Assessment: Responses of the Lower Limb to Ankle Plantarflexion and Dorsiflexion

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Ukadike Chris Ugbolue ◽  
Chloe Robson ◽  
Emma Donald ◽  
Kerry L. Speirs ◽  
Frédéric Dutheil ◽  
...  

There is limited research on the biomechanical assessment of the lower limb joints in relation to dynamic movements that occur at the hip, knee, and ankle joints when performing dorsiflexion (DF) and plantarflexion (PF) among males and females. This study investigated the differences in joint angles (including range of motion (ROM)) and forces (including moments) between the left and right limbs at the ankle, knee, and hip joints during dynamic DF and PF movements in both males and females. Using a general linear model employing multivariate analysis in relation to the joint angle, ROM, force, and moment datasets, the results revealed significant main effects for gender, sidedness, phases, and foot position with respect to joint angles. Weak correlations were observed between measured biomechanical variables. These results provide insightful information for clinicians and biomechanists that relate to lower limb exercise interventions and modelling efficacy standpoints.

2019 ◽  
Vol 5 (1) ◽  
pp. e000568
Author(s):  
Frances E Feeley ◽  
Graham P Arnold ◽  
Sadiq Nasir ◽  
Weijie W Wang ◽  
Rami Abboud

ObjectivesThe lower limb is widely reported as the most commonly injured body part in the field of hockey, more specifically lateral ankle sprains and internal knee injury. Despite this, there remains limited understanding of how the biomechanics of the sport could be adapted to minimise injury. The aim of this study was to propose a foot position during the hockey hit that results in the smallest joint angles and moments, from a total of four different foot positions: 0°, 30°, 60° and 90°, which may correlate to injury risk.MethodEighteen players from the local University Ladies Hockey Club participated in this study. Each player was required to perform a hit with their lead foot in four different positions: 0°, 30°, 60° and 90°, where 0° was a lead foot position perpendicular to the direction of motion of the ball. Angles and moments were calculated with the Vicon system using force plates and motion analysis.ResultsSignificant differences (p<0.05) were found between the angles and moments of the four foot positions tested, indicating that foot angle can influence the degree of angulation, and moments, produced in the lower limb joints during the hockey hit.ConclusionThere is a relationship between lead foot position and the angles and moments produced in the lower limb joints during the hockey hit, and this may correlate with injury risk.


Robotica ◽  
2017 ◽  
Vol 36 (3) ◽  
pp. 395-407 ◽  
Author(s):  
Nicholas B. Melo ◽  
Carlos E. T. Dórea ◽  
Pablo J. Alsina ◽  
Márcio V. Araújo

SUMMARYIn this work, we propose a method able to find user-oriented gait trajectories that can be used in powered lower limb orthosis applications. Most research related to active orthotic devices focuses on solving hardware issues. However, the problem of generating a set of joint trajectories that are user-oriented still persists. The proposed method uses principal component analysis to extract shared features from a gait dataset, taking into consideration gait-related variables such as joint angle information and the user's anthropometric features, used directly in an orthosis application. The trajectories of joint angles used by the model are represented by a given number of harmonics according to their respective Fourier series analyses. This representation allows better performance of the model, whose capability to generate gait information is validated through experiments using a real active orthotic device, analysing both joint motor energy consumption and user metabolic effort.


2017 ◽  
Vol 11 (4) ◽  
pp. 322-329 ◽  
Author(s):  
Mohammad Taghi Karimi

Background: A variety of shoe modifications have been used to reduce the forces applied on the plantar surface of the foot in those with diabetes. Toe and heel rockers are 2 of the most common types used. The aim of this study is to evaluate the effect of these shoe modifications on the kinematics of both normal and diabetic individuals. Method: Two groups of healthy and diabetic individuals were recruited for this study. The Qualysis motion analysis system was used to record the motions of participants while walking with shoes with toe and a combination of toe and heel rockers (combined). The effects of the type of rockers used and the effect of groups were determined using MANOVA. Results: Results of the study demonstrated no discernible difference between the spatiotemporal and range of motion of the ankle, knee, and hip joints while walking with a toe and combined rockers. There was also no difference between healthy and diabetic individuals in relation to these parameters (P value >.05). Conclusion: Results of this study demonstrated no difference between the spatiotemporal and range of motion of lower-limb joints in healthy and diabetic individuals when walking with toe and combined rockers. Because the use of these rockers did not influence the kinematics of the joints while walking, it is recommended that they be used for this group of individuals if they influence the forces applied on the foot. Levels of Evidence: Level IV


2000 ◽  
Vol 83 (5) ◽  
pp. 2931-2945 ◽  
Author(s):  
G. Bosco ◽  
R. E. Poppele ◽  
J. Eian

Many sensorimotor neurons in the CNS encode global parameters of limb movement and posture rather than specific muscle or joint parameters. Our investigations of spinocerebellar activity have demonstrated that these second-order spinal neurons also may encode proprioceptive information in a limb-based rather than joint-based reference frame. However, our finding that each foot position was determined by a unique combination of joint angles in the passive limb made it difficult to distinguish unequivocally between a limb-based and a joint-based representation. In this study, we decoupled foot position from limb geometry by applying mechanical constraints to individual hindlimb joints in anesthetized cats. We quantified the effect of the joint constraints on limb geometry by analyzing joint-angle covariance in the free and constrained conditions. One type of constraint, a rigid constraint of the knee angle, both changed the covariance pattern and significantly reduced the strength of joint-angle covariance. The other type, an elastic constraint of the ankle angle, changed only the covariance pattern and not its overall strength. We studied the effect of these constraints on the activity in 70 dorsal spinocerebellar tract (DSCT) neurons using a multivariate regression model, with limb axis length and orientation as predictors of neuronal activity. This model also included an experimental condition indicator variable that allowed significant intercept or slope changes in the relationships between foot position parameters and neuronal activity to be determined across conditions. The result of this analysis was that the spatial tuning of 37/70 neurons (53%) was unaffected by the constraints, suggesting that they were somehow able to signal foot position independently from the specific joint angles. We also investigated the extent to which cell activity represented individual joint angles by means of a regression model based on a linear combination of joint angles. A backward elimination of the insignificant predictors determined the set of independent joint angles that best described the neuronal activity for each experimental condition. Finally, by comparing the results of these two approaches, we could determine whether a DSCT neuron represented foot position, specific joint angles, or none of these variables consistently. We found that 10/70 neurons (14%) represented one or more specific joint-angles. The activity of another 27 neurons (39%) was significantly affected by limb geometry changes, but 33 neurons (47%) consistently elaborated a foot position representation in the coordinates of the limb axis.


2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Congo Tak-Shing Ching ◽  
Su-Yu Liao ◽  
Teng-Yun Cheng ◽  
Chih-Hsiu Cheng ◽  
Tai-Ping Sun ◽  
...  

Background. The measurement of the functional range of motion (FROM) of lower limb joints is an essential parameter for gait analysis especially in evaluating rehabilitation programs.Aim. To develop a simple, reliable, and affordable mechanical goniometer (MGR) for gait analysis, with six-degree freedom to dynamically assess lower limb joint angles.Design. Randomized control trials, in which a new MGR was developed for the measurements of FROM of lower limb joints.Setting. Reliability of the designed MGR was evaluated and validated by a motion analysis system (MAS).Population. Thirty healthy subjects participated in this study.Methods. Reliability and validity of the new MGR were tested by intraclass correlation coefficient (ICC), Bland-Altman plots, and linear correlation analysis.Results. The MGR has good inter- and intrarater reliability and validity withICC≥0.93(for both). Moreover, measurements made by MGR and MAS were comparable and repeatable with each other, as confirmed by Bland-Altman plots. Furthermore, a very high degree of linear correlation (R≥0.92for all joint angle measurements) was found between the lower limb joint angles measured by MGR and MAS.Conclusion. A simple, reliable, and affordable MGR has been designed and developed to aid clinical assessment and treatment evaluation of gait disorders.


2018 ◽  
Author(s):  
Ian N. Bezodis ◽  
James Cowburn ◽  
Adam Brazil ◽  
Rhian Richardson ◽  
Cassie Wilson ◽  
...  

Cerebral palsy is known to generally limit range of motion and force producing capability during movement. It also limits sprint performance, but the exact mechanisms underpinning this are not well known. One elite male T36 multiple-Paralympic sprint medallist (T36) and 16 well-trained able-bodied (AB) sprinters each performed 5-6 maximal sprints from starting blocks. Whole body kinematics (250 Hz) in the block phase and first two steps, and synchronised external forces (1000 Hz) in the first stance phase after block exit were combined to quantify lower-limb joint kinetics. Sprint performance (normalised average horizontal external power in the first stance after block exit) was lower in T36 compared to AB. T36 had lower extensor range of motion and peak extensor angular velocity at all lower limb joints in the first stance after block exit. Positive work produced at the knee and hip joints in the first stance was lower in T36 than AB, and the ratio of positive:negative ankle work produced was lower in T36 than AB. These novel results directly demonstrate the manner in which cerebral palsy limits performance in a competition-specific sprint acceleration movement, thereby improving understanding of the factors that may limit performance in elite sprinters with cerebral palsy.


Author(s):  
Javier Conte Alcaraz ◽  
Sanam Moghaddamnia ◽  
Jürgen Peissig

AbstractReliability and user compliance of the applied sensor system are two key issues of digital healthcare and biomedical informatics. For gait assessment applications, accurate joint angle measurements are important. Inertial measurement units (IMUs) have been used in a variety of applications and can also provide significant information on gait kinematics. However, the nonlinear mechanism of human locomotion results in moderate estimation accuracy of the gait kinematics and thus joint angles. To develop “digital twins” as a digital counterpart of body lower limb joint angles, three-dimensional gait kinematic data were collected. This work investigates the estimation accuracy of different neural networks in modeling lower body joint angles in the sagittal plane using the kinematic records of a single IMU attached to the foot. The evaluation results based on the root mean square error (RMSE) show that long short-term memory (LSTM) networks deliver superior performance in nonlinear modeling of the lower limb joint angles compared to other machine learning (ML) approaches. Accordingly, deep learning based on the LSTM architecture is a promising approach in modeling of gait kinematics using a single IMU, and thus can reduce the required physical IMUs attached on the subject and improve the practical application of the sensor system.


Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1104
Author(s):  
Hualong Xie ◽  
Guanchao Li ◽  
Xiaofei Zhao ◽  
Fei Li

To enable exoskeleton wearers to walk on level ground, estimation of lower limb movement is particularly indispensable. In fact, it allows the exoskeleton to follow the human movement in real time. In this paper, the general regression neural network optimized by golden section algorithm (GS-GRNN) is used to realize prediction of the human lower limb joint angle. The human body hip joint angle and the surface electromyographic (sEMG) signals of the thigh muscles are taken as the inputs of a neural network to predict joint angles of lower limbs. To improve the prediction accuracy in different gait phases, the plantar pressure signals are also added into the input. After that, the error between the prediction result and the actual data decreases significantly. Finally, compared with the prediction result of the BP neural network, GRNN shows splendid prediction performance for its less processing time and higher prediction accuracy.


Author(s):  
Carmen Stătescu ◽  
Doru Stoica ◽  
Bogdan Ion Gavrilă ◽  
Magdalena Rodica Trăistaru ◽  
Tudor Adrian Bălșeanu

In time, osteoarthritis (OA) generates the misalignment of the affected joint structures. However, due to the nature of bipedal gait, OA in the lower limb can also cause pathological gait patterns, which can generate instability and falls, with great consequence, especially in the aged population. With goniometry used to evaluate the range of motion of joints (ROM), we wanted to evaluate how gender impacts gait dynamics in OA patients. For this study we have compared 106 OA patients (male=32, female=74) to age matched controls. All participants had their right leg as dominant. Video recording of normal gait was analysed with a digital goniometry tool phone application, and the knee&rsquo;s ROM was measured in midstance and midswing of the gait. During midstance, significant extension and flexion of the knee excursion have been observed in both males and females. During midswing, knee OA presents more differences, whereas subjects with hip and knee OA present changes on the dominant knee. Midstance changes suggest that the knee&rsquo;s joint degenerative changes can be linked to hip OA secondary changes. Midswing changes in lower limb OA suggest a connection to the activities of daily life. Gender differences generated by OA must furthermore be studied in both lower limbs so that the best therapeutic approach can be chosen.


Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7199
Author(s):  
Jianyu Yang ◽  
Guanchao Li ◽  
Xiaofei Zhao ◽  
Hualong Xie

In the current study, our research group proposed an asymmetric lower extremity exoskeleton to enable above-knee amputees to walk with a load. Due to the absence of shank and foot, the knee and ankle joint at the amputation side of the exoskeleton lack tracking targets, so it is difficult to realize the function of assisted walking when going up and downstairs. Currently, the use of lower-limb electromyography to predict the angles of lower limb joints has achieved remarkable results. However, the prediction effect was poor when only using electromyography from the thigh. Therefore, this paper introduces hip-angle and plantar pressure signals for improving prediction effect and puts forward a joint prediction method of knee- and ankle-joint angles by electromyography of the thigh, hip-joint angle, and plantar pressure signals. The generalized regression neural network optimized by the golden section method is used to predict the joint angles. Finally, the parameters (the maximum error, the Root-Mean-Square error (RMSE), and correlation coefficient (γ)) were calculated to verify the feasibility of the prediction method.


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