Joint Movement Patterns Research Articles

Dynamic evaluation of community health services and health quality based on biomechanical time series

Background: Evaluating community health services and fitness exceptional is important for identifying areas of development and making sure powerful healthcare shipping. Biomechanical assessment, especially reading joint movements, provides valuable insights into people’s fitness popularity and useful capabilities. Although biomechanical time-collecting information has terrific promise, there is not much thorough research that comprises those parameters in population health checks. Aim: This study evaluates the dynamic relationship between biomechanical time series data of joint movements and community health quality metrics. It also finds important factors for good health and gives practical advice for improving community health services. Methods: The study utilizes a biomechanical time series dataset from Kaggle. The collected time series data was preprocessed using Z-score standardization to ensure comparability. Gated Refined Long Short-Term Memory (GRLSTM) networks were employed for tasks due to their ability to capture long-term dependencies and temporal relationships inherent in time series data. Results: Statistical analyses such as regression and ANOVA were conducted to explore relationships between joint movement patterns and health quality predictors. The GRLSTM indicates significant associations between specific joint movement patterns and health quality indicators. Regression analyses confirmed key predictors of health quality, while ANOVA demonstrated significant differences in joint movement patterns among different health quality groups. The GRLSTM model demonstrates exceptional performance, with 94% precision and 95% recall rates, an accuracy of 98% and a robust F1-score of 96%, indicating a strong equilibrium between recall and accuracy. The ANOVA shows joint angles as the strongest predictor (p < 0.001). The regression analysis identifies stride length (β = 2.30, p < 0.001) as the strongest positive predictor. Conclusion: This observation emphasizes the importance of incorporating biomechanical assessments into community health reviews, highlighting the capability of GRLSTM networks and predictive analytics in improving fitness satisfaction and healthcare strategies.

A reproducible representation of healthy tibiofemoral kinematics during stair descent using REFRAME – Part II: Exploring optimisation criteria and inter-subject differences

Kinematic analysis is a central component of movement biomechanics, describing the relative motion of joint segments during different activities, in different subject cohorts, and at different timepoints. Establishing whether two sets of kinematic signals represent fundamentally similar or different underlying motion patterns is especially challenging, given 1) the lack of consensus around reference frame and joint axis definition, and 2) the substantial effect that minimal variations in frame position and orientation are known to have on signal magnitude and characteristics. As such, enormous variability in the reporting of tibiofemoral kinematics has resulted in joint movement patterns that remain controversially discussed. Previously, we demonstrated the ability of the REference FRame Alignment MEthod (REFRAME) to reorientate and reposition differently aligned local segment frames to achieve convergence in signals representing the same underlying motion, thereby offering a novel approach to consistently report joint motion. In this study, for the first time, we apply REFRAME to assess the rotational and translational in vivo tibiofemoral motion of ten healthy subjects during stair descent based on kinematic signals collected using a moving videofluoroscope. Kinematics were analysed before and after different REFRAME implementations, revealing generally neutral ab/adduction behaviour, accompanied by varying degrees of a sinusoidal int/external tibial rotation pattern over the activity cycle. Our data demonstrate that different selected implementations of REFRAME are able to highlight different characteristics of the motion patterns: Minimisation of the translational root-mean-square revealed proximodistal translation patterns with overall neutral progression, while anteroposterior translation showed seemingly different levels of correlation with flexion/extension in different subjects. On the other hand, REFRAME minimisation of translational variances exposed differences in the relative mean displacement between the femoral and tibial origins between subjects, highlighting differences in mean centre of rotation positions. This early application of REFRAME for providing an understanding of tibiofemoral kinematics demonstrates the potential of this novel approach to bring clarity to an otherwise complex representation of highly variable time-series signals, while highlighting the philosophical challenges of clinically interpretating kinematic signals in the first place.

Feasibility of predicting changes in gait biomechanics following muscle strength perturbations using optimal control in patients with transfemoral amputation

Bone-anchored limbs (BALs) are socket prosthesis alternatives, directly fixing to residual bone via osseointegrated implant. There is a need to quantify multi-level effects of rehabilitation for transfemoral BAL users (i.e. changes in joint loading and movement patterns). Our primary objective was determining feasibility of using optimal control to predict gait biomechanics compared to ground-truth experimental data from transfemoral BAL users. A secondary objective was examining biomechanical effects from estimated changes in hip abductor muscle strength. We developed and validated a workflow for predicting gait biomechanics in four transfemoral BAL users and investigated the biomechanical effects of altered hip abductor strengths.

Biomechanical and Neuromuscular Insights into Deadlift Variations: Implications for Sports Science, Strength Training, and Rehabilitation

The deadlift is a fundamental exercise in resistance training, essential for the development of overall strength and power. This review synthesizes current research on kinematics and electromyographic (EMG) activity during deadlifts, highlighting the effects of different variations and techniques on performance and muscle activation. Kinematic studies have revealed significant differences in joint angles and movement patterns between conventional and sumo deadlifts, emphasizing the importance of technique and experience in optimizing performance and reducing injury risk. EMG analysis has also revealed distinct muscle activation profiles for key muscles, such as the vastus lateralis, gluteus maximus, and hamstrings, across different deadlift variations. These findings are critical for designing effective, individualized training programs in strength and conditioning, as well as developing targeted rehabilitation and injury prevention strategies in sports medicine. By understanding the biomechanical and neuromuscular dynamics of the deadlift, practitioners can improve performance, minimize injury risk, and tailor interventions to the specific needs of athletes. Thus, this review provides a comprehensive overview of the current understanding of deadlift kinematics and EMG activity, offering valuable insights for optimizing training and rehabilitation protocols.

Real-time sports injury monitoring system based on the deep learning algorithm

In response to the low real-time performance and accuracy of traditional sports injury monitoring, this article conducts research on a real-time injury monitoring system using the SVM model as an example. Video detection is performed to capture human movements, followed by human joint detection. Polynomial fitting analysis is used to extract joint motion patterns, and the average of training data is calculated as a reference point. The raw data is then normalized to adjust position and direction, and dimensionality reduction is achieved through singular value decomposition to enhance processing efficiency and model training speed. A support vector machine classifier is used to classify and identify the processed data. The experimental section monitors sports injuries and investigates the accuracy of the system’s monitoring. Compared to mainstream models such as Random Forest and Naive Bayes, the SVM utilized demonstrates good performance in accuracy, sensitivity, and specificity, reaching 94.2%, 92.5%, and 96.0% respectively.

Comparison of Joint Mobilization and Movement Pattern Training for Hip-Related Groin Pain: Ancillary Analysis to Assess 12-Month Outcomes of a Pilot Randomized Clinical Trial

Comparison of Joint Mobilization and Movement Pattern Training for Hip-Related Groin Pain: Ancillary Analysis to Assess 12-Month Outcomes of a Pilot Randomized Clinical Trial

Dynamic Stability of Human Walking in Response to Sudden Speed Changes

Abrupt changes in gait speed can interfere with the symmetry of the overall gait apparatus and result in unstable joint movement patterns. Because unstable joint movements may cause slips, trips, and falls, it is necessary to quantitatively characterize the changes in joint movement patterns in response to sudden speed changes. The purpose of this study is to examine how abrupt changes in gait speed affect gait dynamics. Twenty-two healthy young subjects walked for four minutes, including a warm-up period, under three different speed conditions. Utilizing nonlinear dynamics tools, including the maximum Lyapunov exponent, Sample Entropy, and Detrended Fluctuation Analysis, we quantitatively assessed gait dynamics for the different speed conditions. Our findings highlight how different speed change patterns impact joint instability, notably within the knee joint during gait (p < 0.05). Furthermore, introducing a resting phase during random speed changes exhibited the potential to restore gait symmetry and control movement patterns. This research offers valuable insights into human gait stability dynamics, especially concerning sudden speed changes. Understanding how controlled speed variations affect gait and joint instability informs fall prevention and rehabilitation strategies, emphasizing speed management to improve gait symmetry and reduce joint instability.

Knee kinematics are primarily determined by implant alignment but knee kinetics are mainly influenced by muscle coordination strategy

Implant malalignment has been reported to be a primary reason for revision total knee arthroplasty (TKA). In addition, altered muscle coordination patterns are commonly observed in TKA patients, which is thought to alter knee contact loads. A comprehensive understanding of the influence of surgical implantation and muscle recruitment strategies on joint contact mechanics is crucial to improve surgical techniques, increase implant longevity, and inform rehabilitation protocols. In this study, a detailed musculoskeletal model with a 12 degrees of freedom knee was developed to represent a TKA subject from the CAMS-Knee datasets. Using motion capture and ground reaction force data, a level walking cycle was simulated and the joint movement and loading patterns were estimated using a novel technique for concurrent optimization of muscle activations and joint kinematics. In addition, over 12′000 Monte Carlo simulations were performed to predict knee contact mechanics during walking, considering numerous combinations of implant alignment and muscle activation scenarios. Validation of our baseline simulation showed good agreement between the model kinematics and loading patterns against the in vivo data. Our analyses reveal a considerable impact of implant alignment on the joint kinematics, while variation in muscle activation strategies mainly affects knee contact loading. Moreover, our results indicate that high knee compressive forces do not necessarily originate from extreme kinematics and vice versa. This study provides an improved understanding of the complex inter-relationships between loading and movement patterns resulting from different surgical implantation and muscle coordination strategies and presents a validated framework towards population-based modelling in TKA.

Real-time tactile biofeedback device use for improving balance control of an adolescent with medulloblastoma

PurposeBiofeedback is used for regulating vestibular adaptation and balance by providing real-time stimulus to the individual during physical activities. This study aimed at (1) developing a wearable device, which tracks balance, counts the number and the direction of balance losses and provides haptic biofeedback through real-time vibration stimulus (2) investigating device efficacy on an adolescent medulloblastoma patient during static and dynamic tasks.Design/methodology/approachA 16-year-old medulloblastoma patient used the device during 10-m walking and single-leg stance tests. The knee joint kinematics and the number and direction of balance losses were recorded for “with” and “without” biofeedback conditions.FindingsThe device helped regulate the knee joint kinematics and reduce the number of balance losses of the medulloblastoma patient. The knee joint movement pattern similarity of the control subject was highly correlated (R2 = 0.997, RMSE = 1.232). Conversely, medulloblastoma patient knee joint movement pattern similarity was relatively weak (R2 = 0.359, RMSE = 18.6) when “with” and “without” biofeedback conditions were compared. The number of balance losses decreased when the medulloblastoma patient was guided with biofeedback.Research limitations/implicationsThe major limitation of this pilot study is the lack of a large and homogeneous number of participants. The medulloblastoma patient used the device while walking after she was given enough time to get used to the tactile biological feedback, so the long-term effect of the device and biofeedback guidance were not investigated. Additionally, the potential desensitization with prolonged use of the device was not evaluated.Practical implicationsBiofeedback reduced the number of balance losses; additionally, the knee joint movement pattern was regulated during static and dynamic tasks. This device can be integrated into the physical therapy of patients with balance, vestibular and postural control impairments.Social implicationsThis is compact and has an easy-to-wear design, patients, who have balance and postural control impairments, can practically use the device during their activities of daily living.Originality/valueThe device promotes physical activity adaptation and regulates gait through continuous and real-time balance control. Its design makes it simple for the user to wear it beneath clothing while using the sensor.

Temporomandibular joint biomechanics and equine incisor occlusal plane maintenance.

In equine dentistry, the physiological incisor occlusal surface is visually perceived as a plane with a distinct inclination to the head's coronal plane, extending rostro-ventrally to caudo-dorsally. To better understand the formation of this inclined plane and its connection to dental wear, we investigated the hypothesis that it arises from masticatory movements and the considerable distance between mandibular articular heads and the incisor occlusal surfaces, acting as the three points of support for the mandibles. Leveraging data from a large-scale clinical study involving static and dynamic orthodontic measurements in horses, we approximated the mandibular movement range where incisor occlusion and dental wear occur. By introducing and testing a segment coordinate system, we explored possible angular deviations from the occlusal plane caused by mandibular roll and pitch rotations during two lateral mandibular movement patterns, protrusion and retrusion. Theoretical biomechanical calculations and simulations confirmed the visual perception of the incisor occlusal surface as a plane. To further examine our assumptions, we employed a simple mechanical simulator to assess incisor normal occlusion and provoked malocclusions (diagonal, smile, and frown bite) by modifying temporomandibular joint (TMJ) movement patterns. The results from clinical investigations were corroborated by both the theoretical analysis and mechanical simulations, strengthening our understanding of the biomechanical basis behind the physiological incisor occlusal plane maintenance in horses. These findings have significant implications for equine dental health and contribute to a thorough understanding of TMJ dynamics.

Interspecies comparison of temporomandibular joint condylar cartilage extracellular matrix from macro to microscopy

Interspecies comparisons of the extracellular matrix of temporomandibular joint (TMJ) condylar cartilage are necessary to elucidate the mechanisms underlying its superior mechanical properties, to guide the construction of animal models of TMJ-related diseases, and to establish standards for the engineering of TMJ condylar cartilage. Here we characterize and compare TMJ condylar cartilage from six different species from a materials science perspective, including structure, composition and mechanical properties from the macroscopic to the microscopic level. The gross morphology showed obvious interspecies differences in size and shape, which may be related to the different joint motion patterns. Although the condylar cartilage of all species can be divided histologically into a superficial fibrous layer and a deep hyaline layer, there are significant interspecies differences in the microstructure of the fibrils in the two layers, mainly in the diameter of the fibrils. Compositionally, there were no significant differences in collagen composition between species, but the content of glycosaminoglycans (GAGs) decreased progressively with increasing body size, with the same results obtained by Safranin O staining and biochemical analysis. Mechanically, the elastic modulus of mouse condylar cartilage was significantly higher than that of the other species and tended to decrease with increasing body size. This study shows that the TMJ condylar cartilage of different species has its own specific structure-composition-mechanics matching characteristics for their unique masticatory stress dissipation, and differences in fibril diameter and GAGs content may be the two ultimate factors influencing the differences in cartilage mechanical properties between species, while the condylar cartilage of pigs is most similar to that of humans, suggesting that pigs may be a suitable animal model for TMJ studies.

The use of enhanced intrinsic feedback for motor learning in stroke survivors: Clinical trial protocol

BackgroundStroke can lead to lasting sensorimotor deficits of the upper limb (UL) persisting into the chronic phase despite intensive rehabilitation. A major impairment of reaching after stroke is a decreased range of active elbow extension, which in turn leads to the use of compensatory movements. Retraining movement patterns relies on cognition and motor learning principles. Implicit learning may lead to better outcomes than explicit learning. Error augmentation (EA) is a feedback modality based on implicit learning resulting in improved precision and speed of UL reaching movements in people with stroke. However, accompanying changes in UL joint movement patterns have not been investigated. The objective of this study is to determine the capacity for implicit motor learning in people with chronic stroke and how this capacity is affected by post-stroke cognitive impairments. MethodsFifty-two subjects who have chronic stroke will practice reaching movements 3×/wk. for 9 wk. in a virtual reality environment. Participants will be randomly allocated to 1 of 2 groups to train with or without EA feedback. Outcome measures (pre-, post- and follow-up) will be: endpoint precision, speed, smoothness, and straightness and joint (UL and trunk) kinematics during a functional reaching task. The degree of cognitive impairment, lesion profile, and integrity of descending white matter tracts will be related to training outcomes. ConclusionsThe results will inform us which patients can best benefit from training programs that rely on motor learning and utilize enhanced feedback.Trial status: Ethical approval for this study was finalized in May 2022. Recruitment and data collection is actively in progress and is planned to finish in 2026. Data analysis and evaluation will occur subsequently, and the final results will be published.

Effect of non-specific neck pain on the path of the instantaneous axis of rotation of the neck during its flexion-extension movement

Non-specific neck pain is a common musculoskeletal disorder with a high prevalence and involves impaired joint movement pattern. Therefore, this study aimed to compare the trajectory of the instantaneous axis of rotation(IAR) in flexion-extension movements of the neck between people with and without nonspecific neck pain, using functional data analysis techniques. Furthermore, possible relationships between neck kinematics and perceived pain and disability were explored.Seventy-three volunteers participated in this cross-sectional study. They were allocated in a non-specific pain group (PG, n = 28) and a control group (CG, n = 45). A cyclic flexion-extension movement was assessed by a video photogrammetry system and numerical and functional variables were computed to analyze IAR trajectory during movement. Moreover, to explore possible relationships of these variables with pain and neck disability, a visual analogue scale (VAS) and the neck disability index (NDI) were used.The instantaneous axis of rotation trajectory during the flexion-extension cyclic movement described a path like Greek letter rho both in the CG and the PG, but this trajectory was shorter and displaced upward in the PG, compared to the CG. A reduction of the displacement range and a rise in the vertical position of the IAR were related to VAS and NDI scores.Non-specific neck pain is associated with a higher location of the instantaneous axis of rotation and a decrease in length of the path traveled during the flexion-extension movement. This study contributes to a better description of neck movement in people with non-specific neck pain, which would help to plan an individualized treatment.

Dual‐Mode Pressure Sensor Integrated with Deep Learning Algorithm for Joint State Monitoring in Tennis Motion

The precise capture and identification of movement features are important for numerous scientific endeavors. In this work, we present a novel multimodal sensor, called the resistance/capacitance dual‐mode (RCDM) sensor, which effectively differentiates between compression and stretchable strains during tennis motion; meanwhile, it can also accurately identify various joint movements. The proposed wearable device features a seamless design, comprising two separate components: a resistive part and a capacitive part. The resistive and capacitive components operate independently and utilize a resistance–capacitance mechanism to measure pressure and strain signals, respectively. The RCDM sensor demonstrates remarkable sensitivity to strains (GF = 7.84, 0%–140%) and exceptional linear sensitivity (S = 4.08 kPa−1) through capacitance. Utilizing machine learning algorithms, the sensor achieves a recognition rate of 97.21% in identifying various joint movement patterns. This advanced production method makes it feasible to manufacture the sensors on a large scale, offering tremendous potential for various applications, including tennis sports systems.

Facile Approach to Fabricate Oriented Porous PDMS Composites for Movements Monitoring and Identifying Motion Patterns.

The facile and rapid fabrication of oriented porous polymers is crucial for flexible pressure sensors. Herein, a pressure sensor is developed based on oriented porous polydimethylsiloxane (PDMS) composites for detecting human motion and identifying joint motion patterns. The oriented porous PDMS composite is first constructed through thiol-ene click chemistry and directional freezing within only 30min, then fabricated by interfacial in situ polymerization of dopamine and pyrrole to generate robust interfaces. As a result, the as-prepared oriented porous PDMS composite is assembled into a pressure sensor that shows potential applications in pressure and human motion detection. Interestingly, a sensor assembled by orthogonally stacking the PDMS composites can be used for joint motion pattern recognition with potential monitoring of football motion due to their directional structures. This facile strategy coupled with the oriented porous structure is expected to help design advanced wearable electronic devices.

Application of wearable technologies for player motion analysis in racket sports: A systematic review

The use of wearable devices for player motion analysis is becoming a popular method to measure kinematic parameters associated with player techniques in racket sports. This systematic review focused on identifying the current applications of wearable technology for player motion analysis in racket sports (tennis, table tennis, badminton and squash) through two research questions: (1) What are the existing applications of wearable technology for player motion analysis in racket sports? (2) What data analysis methods are used to quantify and evaluate player motion? A comprehensive search of MEDLINE, EMBASE, SPORTDiscus, Scopus, Web of Science, and IEEE databases was undertaken following PRISMA reporting guidelines. Included studies must have only used external wearable technology mounted to either the player or the racket for the potential application of player motion analysis in a racket sport, tested the wearable technology under normal playing conditions and not only focused on detecting/classifying the player's stroke or activity movement. Of the 6616 articles found, a total of 15 studies met the inclusion and exclusion criteria. Tennis and table tennis were the most popular sports researched and inertial measurement units and electromyography sensors were the most common types of sensors used. This review found that wearable devices were mainly used to analyze (1) movement similarities and differences of players at different playing levels, (2) variability in racket, upper limb and joint movement patterns and (3) movement differences associated with different ball spin levels. These technologies can create a new level of accessible personalized training in these sports.

Implementation of Long Short-Term Memory and Gated Recurrent Units on grouped time-series data to predict stock prices accurately

Stocks are an attractive investment option because they can generate large profits compared to other businesses. The movement of stock price patterns in the capital market is very dynamic. Therefore, accurate data modeling is needed to forecast stock prices with a low error rate. Forecasting models using Deep Learning are believed to be able to predict stock price movements accurately with time-series data input, especially the Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms. Unfortunately, several previous studies and investigations of LSTM/GRU implementation have not yielded convincing performance results. This paper proposes eight new architectural models for stock price forecasting by identifying joint movement patterns in the stock market. The technique is to combine the LSTM and GRU models with four neural network block architectures. Then, the proposed architectural model is evaluated using three accuracy measures obtained from the loss function Mean Absolute Percentage Error (MAPE), Root Mean Squared Percentage Error (RMSPE), and Rooted Mean Dimensional Percentage Error (RMDPE). The three accuracies, MAPE, RMSPE, and RMDPE, represent lower accuracy, true accuracy, and higher accuracy in using the model.

The power of instruction on retropulsion: A pilot randomized controlled trial of therapeutic exercise focused on ankle joint movement in Parkinson’s disease

IntroductionAlthough retropulsion is a serious complication of Parkinson’s disease (PD), it is unknown whether ankle joint movement patterns can be targeted to treat retropulsion. The primary aim of this study was to investigate the effectiveness of therapeutic exercise focused on instructions regarding ankle joint movement on retropulsion in PD. MethodsTwenty patients with moderate PD were randomly allocated to the experimental intervention (INSTR) or control groups. The INSTR group received a 2-week therapeutic exercise program (40 min/day, five times/week) that involved repeated backward pulls on the shoulders with instructions to land on the toes as a response, and the control group received the same intervention without the instructions. The primary outcome was the difference in changes from baseline in the Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS part III) score between the study groups at weeks 1 and 2. ResultsThe improvement in the MDS-UPDRS part III scores was significantly greater for the INSTR group in the week 1 (p = 0.033, pη2 = 0.241) and week 2 (p = 0.004, pη2 = 0.401) assessments. However, the provision of instructions to land on the toes as a backward response induced improvement in the only scores related to the backward response, and no significant between-group differences were observed in the other outcomes. ConclusionThe 2-week therapeutic exercise program with instructions to treat retropulsion improved the backward response. Trial registrationUMIN-CTR, UMIN000042722.

Increased Trailing Limb Angle is Associated with Regular and Stable Trunk Movements in Patients with Hemiplegia

ObjectivesIn post-stroke patients, shifts in the center of gravity may affect joint movement patterns of the paraplegic lower limb during walking. The impact of changes in ankle dorsiflexion angle and trailing limb angle due to slight weight-shifting is unknown. This study aimed to investigate the effect of the abovementioned parameters on gait characteristics measured by trunk acceleration. Materials and methodsDuring walking, the ankle dorsiflexion angle and trailing limb angle were assessed using two-dimensional motion analysis. Shifts in the center of gravity were assessed to evaluate symmetry, regularity, and sway of trunk movements by calculating the harmonic ratio, autocorrelation coefficient, and root mean square using a wearable trunk accelerometer. ResultsAnkle dorsiflexion angle showed a significant negative correlation with the root mean square of the anteroposterior axis (r = -0.460, p = 0.005). Trailing limb angle was significantly correlated with the autocorrelation coefficient of the vertical axis (r = 0.585, p < 0.001) and root mean square of the vertical (r = -0.579, p < 0.001), mediolateral (r = -0.474, p = 0.004), and anteroposterior axes (r = -0.548, p = 0.001). Trailing limb angle was a significant predictor (autocorrelation coefficient vertical axis, p = 0.001; root mean square vertical axis, p = 0.001; mediolateral axis, p = 0.007; anteroposterior axis, p = 0.001). ConclusionsTrailing limb angle can indicate the acquisition of forward propulsion during walking; an increase in it may contribute to improvements of the regular vertical movement ability and stability of the center of gravity sway.

Proximal and distal movement patterns during a graphomotor task in typically developing children and children with handwriting problems

BackgroundTherapists specializing in handwriting difficulties in children often address motor problems including both proximal and distal movements in the upper extremity. Kinematic measures can be used to investigate various aspects of handwriting. This study examined differences in movement patterns in proximal and distal joints of the upper extremity during graphomotor tasks between typically developing children with and without handwriting problems. Additionally, it explored relationships between movement patterns, speed, and legibility of writing.MethodsForty-one children, aged 7–11 years, were assessed with the Aleph Aleph Ktav Yad Hebrew Handwriting assessment and the Beery Test of Visual Motor Integration and, based on their scores, were divided into a research group (with handwriting difficulties) and a control group (without handwriting difficulties). Upper extremity joint movement patterns were analyzed with a motion capture system. Differences in the quality of shapes traced and copied on a graphics tablet positioned horizontally and vertically were compared. Between-group differences and relationships with speed and legibility were analyzed.ResultsIn both groups, there was greater movement in the distal compared to the proximal joints, greater movement when performing the task in a horizontal compared to a vertical plane, and greater movement when tracing than copying. Joint movements in the arm executed scaled-down versions of the shapes being drawn. While the amount of joint displacement was similar between groups, children in the research group showed greater dissimilarity between the drawn shape and the shape produced by the proximal joints. Finally, the drawing measure on the tablet was a significant predictor of legibility, speed of writing, visual motor integration and motor coordination, whereas the dissimilarity measure of joint movement was a significant predictor of speed of writing and motor coordination.ConclusionsThis study provides support for the role of the distal upper extremity joints in the writing process and some guidance to assist clinicians in devising treatment strategies for movement-related handwriting problems. While we observed differences in proximal joint movements between the children with and without handwriting difficulties, the extent to which they are responsible for the differences in drawing quality remains to be determined. Further studies should use a similar methodology to examine additional tasks such as drawing shapes of varying sizes.