Age-related changes in cheek skin movement: A case study of Japanese women.

BACKGROUND: The majority of conventional studies on skin aging have focused on static conditions. However, in daily life, the facial skin we encounter is constantly in motion due to conversational expressions and changes in facial expressions, causing the skin to alter its position and shape, resulting in a dynamic state. Consequently, it is hypothesized that characteristics of aging not apparent in static conditions may be present in the dynamic state of the skin. Therefore, this study investigates age-related changes in dynamic skin characteristics associated with facial expression alterations. METHODS: A motion capture system measured the dynamic characteristics (delay and stretchiness of skin movement associated with expression) of the cheek skin in response to facial expressions among 86 Japanese women aged between 20 and 69 years. RESULTS: The findings revealed an increase in the delay of cheek skin response to facial expressions (r = 0.24, p < 0.05) and a decrease in the stretchiness of the lower cheek area with age (r = 0.60, p < 0.01). An increasing variance in delay and stretchiness within the same age group was also observed with aging. CONCLUSION: The findings of this study revealed that skin aging encompasses both static characteristics, such as spots, wrinkles, and sagging, traditionally studied in aging research, and dynamic aging characteristics of the skin that emerge in response to facial expression changes. These dynamic aging characteristics could pave the way for the development of new methodologies in skin aging analysis and potentially improve our understanding and treatment of aging impressions that are visually perceptible in daily life but remain unexplored.

A Review of Motor Brain-Computer Interfaces Using Intracranial Electroencephalography Based on Surface Electrodes and Depth Electrodes.

Brain-computer interfaces (BCIs) provide a communication interface between the brain and external devices and have the potential to restore communication and control in patients with neurological injury or disease. For the invasive BCIs, most studies recruited participants from hospitals requiring invasive device implantation. Three widely used clinical invasive devices that have the potential for BCIs applications include surface electrodes used in electrocorticography (ECoG) and depth electrodes used in Stereo-electroencephalography (SEEG) and deep brain stimulation (DBS). This review focused on BCIs research using surface (ECoG) and depth electrodes (including SEEG, and DBS electrodes) for movement decoding on human subjects. Unlike previous reviews, the findings presented here are from the perspective of the decoding target or task. In detail, five tasks will be considered, consisting of the kinematic decoding, kinetic decoding,identification of body parts, dexterous hand decoding, and motion intention decoding. The typical studies are surveyed and analyzed. The reviewed literature demonstrated a distributed motor-related network that spanned multiple brain regions. Comparison between surface and depth studies demonstrated that richer information can be obtained using surface electrodes. With regard to the decoding algorithms, deep learning exhibited superior performance using raw signals than traditional machine learning algorithms. Despite the promising achievement made by the open-loop BCIs, closed-loop BCIs with sensory feedback are still in their early stage, and the chronic implantation of both ECoG surface and depth electrodes has not been thoroughly evaluated.

IMU Data-Driven and PCA-Based Approach to Establish Quantifiable and Practically Applicable Measures for V2 Technique Elements in Cross-Country Skiing.

Quantifying movement coordination in cross-country (XC) skiing, specifically the technique with its elemental forms, is challenging. Particularly, this applies when trying to establish a bidirectional transfer between scientific theory and practical experts' knowledge as expressed, for example, in ski instruction curricula. The objective of this study was to translate 14 curricula-informed distinct elements of the V2 ski-skating technique (horizontal and vertical posture, lateral tilt, head position, upper body rotation, arm swing, shoulder abduction, elbow flexion, hand and leg distance, plantar flexion, ski set-down, leg push-off, and gliding phase) into plausible, valid and applicable measures to make the technique training process more quantifiable and scientifically grounded. Inertial measurement unit (IMU) data of 10 highly experienced XC skiers who demonstrated the technique elements by two extreme forms each (e.g., anterior versus posterior positioning for the horizontal posture) were recorded. Element-specific principal component analyses (PCAs)-driven by the variance produced by the technique extremes-resulted in movement components that express quantifiable measures of the underlying technique elements. Ten measures were found to be sensitive in distinguishing between the inputted extreme variations using statistical parametric mapping (SPM), whereas for four elements the SPM did not detect differences (lateral tilt, plantar flexion, ski set-down, and leg push-off). Applicability of the established technique measures was determined based on quantifying individual techniques through them. The study introduces a novel approach to quantitatively assess V2 ski-skating technique, which might help to enhance technique feedback and bridge the communication gap that often exists between practitioners and scientists.

Concerto of movement: how expertise shapes the synergistic control of upper limb muscles in complex motor tasks with varying tempo and dynamics.

Objective. This research aims to reveal how the synergistic control of upper limb muscles adapts to varying requirements in complex motor tasks and how expertise shapes the motor modules.Approach. We study the muscle synergies of a complex, highly skilled and flexible task-piano playing-and characterize expertise-related muscle-synergy control that permits the experts to effortlessly execute the same task at different tempo and force levels. Surface EMGs (28 muscles) were recorded from adult novice (N= 10) and expert (N= 10) pianists as they played scales and arpeggios at different tempo-force combinations. Muscle synergies were factorized from EMGs.Main results. We found that experts were able to cover both tempo and dynamic ranges using similar synergy selections and achieved better performance, while novices altered synergy selections more to adapt to the changing tempi and keystroke intensities compared with experts. Both groups relied on fine-tuning the muscle weights within specific synergies to accomplish the different task styles, while the experts could tune the muscles in a greater number of synergies, especially when changing the tempo, and switch tempo over a wider range.Significance. Our study sheds light on the control mechanism underpinning expertise-related motor flexibility in highly skilled motor tasks that require decade-long training. Our results have implications on musical and sports training, as well as motor prosthetic design.

Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment (i.e., tethering an infant's foot to a colorful mobile). Vicon motion capture data from multiple infant joints were used here to create Histograms of Joint Displacements (HJDs) to generate pose-based descriptors for 3D infant spatial trajectories. Using HJDs as inputs, machine and deep learning systems were tasked with classifying the experimental state from which snippets of movement data were sampled. The architectures tested included k-Nearest Neighbour (kNN), Linear Discriminant Analysis (LDA), Fully connected network (FCNet), 1D-Convolutional Neural Network (1D-Conv), 1D-Capsule Network (1D-CapsNet), 2D-Conv and 2D-CapsNet. Sliding window scenarios were used for temporal analysis to search for topological changes in infant movement related to functional context. kNN and LDA achieved higher classification accuracy with single joint features, while deep learning approaches, particularly 2D-CapsNet, achieved higher accuracy on full-body features. For each AI architecture tested, measures of foot activity displayed the most distinct and coherent pattern alterations across different experimental stages (reflected in the highest classification accuracy rate), indicating that interaction with the world impacts the infant behaviour most at the site of organism~world connection.

Physical Factors Associated with Non-Specific Neck Pain: Correlations Among Pain, Disability, Posture, Endurance, and Compensatory Movement.

BACKGROUND This study was conducted to investigate physical risk factors in patients with non-specific neck pain. The correlations among pain intensity, pressure pain threshold, range of motion (ROM), and disability index were analyzed in 50 patients with non-specific neck pain at a hospital in Korea. MATERIAL AND METHODS We enrolled 50 patients diagnosed with non-specific neck pain by a doctor. All subjects were evaluated for pain intensity, pressure threshold, degree of disability, active range of motion (ROM) of the neck, upper cervical rotation ROM, muscular endurance of deep cervical flexor, compensatory movements for neck flexion, forward head posture, shoulder height difference, and rounded shoulder posture. The correlation between each variable was analyzed. RESULTS Pain intensity had a significant correlation between cervical rotation ROM, cervical flexion-rotation ROM, rounded shoulder posture, shoulder height difference, and forward head posture (P<.05). There was a significant correlation between the pressure pain threshold and the cervical extension ROM, cervical flexion-rotation ROM, and rounded shoulder height (P<.05). The disability index had a significant correlation between the cervical rotation ROM, cervical flexion-rotation ROM, rounded shoulder posture, and the compensatory movement of neck flexion (P<.05). CONCLUSIONS Physical risk factors for non-specific neck pain included cervical rotation ROM, upper cervical rotation ROM, rounded shoulder posture, shoulder height difference, and cervical flexion compensatory movements, which can affect pain intensity and pressure pain threshold.

Spontaneous rates exhibit high intra-individual stability across movements involving different biomechanical systems and cognitive demands.

Spontaneous rhythmic movements are part of everyday life, e.g., in walking, clapping or music making. Humans perform such spontaneous motor actions at different rates that reflect specific biomechanical constraints of the effector system in use. However, there is some evidence for intra-individual consistency of specific spontaneous rates arguably resulting from common underlying processes. Additionally, individual and contextual factors such as musicianship and circadian rhythms have been suggested to influence spontaneous rates. This study investigated the relative contributions of these factors and provides a comprehensive picture of rates among different spontaneous motor behaviors, i.e., melody production, walking, clapping, tapping with and without sound production, the latter measured online before and in the lab. Participants (n = 60) exhibited high intra-individual stability across tasks. Task-related influences included faster tempi for spontaneous production rates of music and wider ranges of spontaneous motor tempi (SMT) and clapping rates compared to walking and music making rates. Moreover, musicians exhibited slower spontaneous rates across tasks, yet we found no influence of time of day on SMT as measured online in pre-lab sessions. Tapping behavior was similar in pre-lab and in-lab sessions, validating the use of online SMT assessments. Together, the prominent role of individual factors and high stability across domains support the idea that different spontaneous motor behaviors are influenced by common underlying processes.

Control strategies for trunk exoskeletons based on motion intent recognition: A review.

BACKGROUND: Wearable trunk exoskeletons hold immense potential in fields such as healthcare and industry. Previous research has indicated that intention recognition control plays a crucial role in users' daily use of exoskeletons. OBJECTIVE: This review aims to discuss the characteristics of intention recognition control schemes for intelligent trunk exoskeletons under different control objectives over the past decade. METHODS: Considering the relatively late development of active trunk exoskeletons, we selected papers published in the last decade (2013 to 2023) from the Web of Science, PubMed, and IEEE Xplore databases. In total, 50 articles were selected and examined based on four control objectives. RESULTS: In general, we found that researchers focus on trunk exoskeleton devices designed for assistance and motor augmentation, which rely more on body movement signals as a source for intention recognition. CONCLUSION: Based on these results, we identify and discuss several promising research directions that may help to attain a widely accepted control methods, thereby advancing further development of trunk exoskeleton technology.

A prefrontal motor circuit initiates persistent movement.

Persistence reinforces continuous action, which benefits animals in many aspects. Diverse external or internal signals may trigger animals to start a persistent movement. However, it is unclear how the brain decides to persist with current actions by selecting specific information. Using single-unit extracellular recordings and opto-tagging in awake mice, we demonstrated that a group of dorsal mPFC (dmPFC) motor cortex projecting (MP) neurons initiate a persistent movement by selectively encoding contextual information rather than natural valence. Inactivation of dmPFC MP neurons impairs the initiation and reduces neuronal activity in the insular and motor cortex. After the persistent movement is initiated, the dmPFC MP neurons are not required to maintain it. Finally, a computational model suggests that a successive sensory stimulus acts as an input signal for the dmPFC MP neurons to initiate a persistent movement. These results reveal a neural initiation mechanism on the persistent movement.

Predicting the bodily self in space and time.

To understand how the human brain distinguishes itself from external stimulation, it was examined if motor predictions enable healthy adult volunteers to infer self-location and to distinguish their body from the environment (and other agents). By uniquely combining a VR-setup with full-body motion capture, a full-body illusion paradigm (FBI) was developed with different levels of motion control: (A) a standard, passive FBI in which they had no motion control; (B) an active FBI in which they made simple, voluntary movements; and (C) an immersive game in which they real-time controlled a human-sized avatar in third person. Systematic comparisons between measures revealed a causal relationship between (i) motion control (prospective agency), (ii) self-other identification, and (iii) the ability to locate oneself. Healthy adults could recognise their movements in a third-person avatar and psychologically align with it (action observation); but did not lose a sense of place (self-location), time (temporal binding), nor who they are (self/other). Instead, motor predictions enabled them to localise their body and to distinguish self from other. In the future, embodied games could target and strengthen the brain's control networks in psychosis and neurodegeneration; real-time motion simulations could help advance neurorehabilitation techniques by fine-tuning and personalising therapeutic settings.

Movement and Pressure Injury Prevention Care for Nursing Home Residents: Addressing the Nescience.

OBJECTIVE: To compare movement associated with position changes among nursing home residents who remain in lying versus upright positions for more than 2 hours and among residents living with obesity, dementia, or neither condition. METHODS: The authors conducted a descriptive exploratory study using secondary data (N = 934) from the Turn Everyone And Move for Ulcer Prevention (TEAM-UP) clinical trial to examine transient movements (<60 seconds) within prolonged periods of 2 to 5 hours without repositioning. RESULTS: Nursing home residents exhibit significantly more episodic transient movements when upright than lying. Residents with obesity or dementia exhibited similar frequencies of episodic transient movements compared with residents with neither obesity nor dementia. Upright or lying movements were more frequent among residents with obesity than among those with neither obesity nor dementia selectively when prolonged events ranged from 2 to 4 hours. Pairwise comparisons of movement rates among resident subgroups (living with obesity, living with dementia, or neither group) across repositioning intervals showed episodic transient movements were significantly higher across all subgroups for repositioning intervals up to 3 hours when compared with repositioning intervals of greater than 3 hours. CONCLUSIONS: Findings challenge assumptions that nursing home residents are inactive and at risk for prolonged sitting. These preliminary findings, along with TEAM-UP findings where no pressure injuries occurred in up to 5 hours in prolonged positions, support establishing a standard 3-hour repositioning interval with use of high-density mattresses without a negative impact on pressure injury occurrence. There should be caution when considering repositioning intervals greater than 3 hours. Further research is indicated to explore protective effect of episodic transient movements of other subgroups.

Low and high beta rhythms have different motor cortical sources and distinct roles in movement control and spatiotemporal attention.

Low and high beta frequency rhythms were observed in the motor cortex, but their respective sources and behavioral correlates remain unknown. We studied local field potentials (LFPs) during pre-cued reaching behavior in macaques. They contained a low beta band (<20 Hz) dominant in primary motor cortex and a high beta band (>20 Hz) dominant in dorsal premotor cortex (PMd). Low beta correlated positively with reaction time (RT) from visual cue onset and negatively with uninstructed hand postural micro-movements throughout the trial. High beta reflected temporal task prediction, with selective modulations before and during cues, which were enhanced in moments of increased focal attention when the gaze was on the work area. This double-dissociation in sources and behavioral correlates of motor cortical low and high beta, with respect to both task-instructed and spontaneous behavior, reconciles the largely disparate roles proposed for the beta rhythm, by suggesting band-specific roles in both movement control and spatiotemporal attention.

A cross-dataset adaptive domain selection transfer learning framework for motor imagery-based brain-computer interfaces.

Objective. In brain-computer interfaces (BCIs) that utilize motor imagery (MI), minimizing calibration time has become increasingly critical for real-world applications. Recently, transfer learning (TL) has been shown to effectively reduce the calibration time in MI-BCIs. However, variations in data distribution among subjects can significantly influence the performance of TL in MI-BCIs.Approach.We propose a cross-dataset adaptive domain selection transfer learning framework that integrates domain selection, data alignment, and an enhanced common spatial pattern (CSP) algorithm. Our approach uses a huge dataset of 109 subjects as the source domain. We begin by identifying non-BCI illiterate subjects from this huge dataset, then determine the source domain subjects most closely aligned with the target subjects using maximum mean discrepancy. After undergoing Euclidean alignment processing, features are extracted by multiple composite CSP. The final classification is carried out using the support vector machine.Main results.Our findings indicate that the proposed technique outperforms existing methods, achieving classification accuracies of 75.05% and 76.82% in two cross-dataset experiments, respectively.Significance.By reducing the need for extensive training data, yet maintaining high accuracy, our method optimizes the practical implementation of MI-BCIs.

Multi-Condition Latent Diffusion Network for Scene-Aware Neural Human Motion Prediction.

Inferring 3D human motion is fundamental in many applications, including understanding human activity and analyzing one's intention. While many fruitful efforts have been made to human motion prediction, most approaches focus on pose-driven prediction and inferring human motion in isolation from the contextual environment, thus leaving the body location movement in the scene behind. However, real-world human movements are goal-directed and highly influenced by the spatial layout of their surrounding scenes. In this paper, instead of planning future human motion in a "dark" room, we propose a Multi-Condition Latent Diffusion network (MCLD) that reformulates the human motion prediction task as a multi-condition joint inference problem based on the given historical 3D body motion and the current 3D scene contexts. Specifically, instead of directly modeling joint distribution over the raw motion sequences, MCLD performs a conditional diffusion process within the latent embedding space, characterizing the cross-modal mapping from the past body movement and current scene context condition embeddings to the future human motion embedding. Extensive experiments on large-scale human motion prediction datasets demonstrate that our MCLD achieves significant improvements over the state-of-the-art methods on both realistic and diverse predictions.

Characterizing Disease Progression in Parkinson's Disease from Videos of the Finger Tapping Test.

INTRODUCTION: Parkinson's disease (PD) is characterized by motor symptoms whose progression is typically assessed using clinical scales, namely the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Despite its reliability, the scale is bounded by a 5-point scale that limits its ability to track subtle changes in disease progression and is prone to subjective interpretations. We aimed to develop an automated system to objectively quantify motor symptoms in PD using Machine Learning (ML) algorithms to analyze videos and capture nuanced features of disease progression. METHODS: We analyzed videos of the Finger Tapping test, a component of the MDS-UPDRS, from 24 healthy controls and 66 PD patients using ML algorithms for hand pose estimation. We computed multiple movement features related to bradykinesia from videos and employed a novel tiered classification approach to predict disease severity that employed different features according to severity. We compared our video-based disease severity prediction approach against other approaches recently introduced in the literature. RESULTS: Traditional kinematics features such as amplitude and velocity changed linearly with disease severity, while other non-traditional features displayed non-linear trends. The proposed disease severity prediction approach demonstrated superior accuracy in detecting PD and distinguishing between different levels of disease severity when compared to existing approaches.

Inter- and intra-athlete technique variability of conventional new ball swing bowling in elite and pre-elite Australian male fast bowlers.

This study aimed to investigate inter- and intra-athlete technique variability in pre-elite and elite Australian fast bowlers delivering new ball conventional swing bowling. Ball grip angle and pelvis, torso, shoulder, elbow, wrist, upper arm, forearm, and hand kinematics were investigated at the point of ball release for inswing and outswing deliveries. Descriptive evaluations of group and individual data and k-means cluster analyses were used to assess inter- and intra-bowler technique variability. Inter-athlete technique and ball grip variability were identified, demonstrating that skilled bowlers use individualised strategies to generate swing. Functional movement variability was demonstrated by intra-athlete variability in successful swing bowling trials. Bowlers demonstrated stable technique parameters in large proximal body segments of the pelvis and torso, providing a level of repeatability to their bowling action. Greater variation was observed in bowling arm kinematics, allowing athletes to manipulate the finger and ball position to achieve the desired seam orientation at the point of ball release. This study demonstrates that skilled bowlers use individualised techniques and grips to generate swing and employ technique variations in successive deliveries. Coaches should employ individualised training strategies and use constraints-led approaches in training environments to encourage bowlers to seek adaptive movement solutions to generate swing.

The effects of jaw clenching and mouthpiece use on bat swing velocity in Division II athletes.

Research assessing the effects of mouthpieces on an individual's aerobic, anaerobic, or muscular performance have attributed cited improvements to the participant's ability to jaw clench. Jaw clenching research finds positive outcomes with the task of jaw clenching with targeted muscle groups in a controlled laboratory setting. Thus, the study's goal was to determine if the addition of a mouthpiece would positively affect performance outcomes in a field-based whole-body muscle movement. Fourteen participants (8=F and 6=M) NCAA softball and baseball athletes completed 5 maximal bat swings with and without a mouthpiece in 4 conditions: no jaw clenching (NC), mouthpiece and jaw clenching (MP+C), mouthpiece only (MP), and jaw clenching only (C). Significant differences occurred in conditions, with the highest velocity noted in the combined condition of MP+C (71.9 mph) as compared to NC (67.9 mph), MP (68.6 mph), and C (70.9 mph). A repeated measures ANOVA demonstrated significant differences with bat swing velocity (F = 13.19, df 3, p < 0.0001). Pairwise comparisons revealed significant differences in MP+C with MP (p = 0.007); MP+C with NC (p = 0.001), and C with NC (p = 0.009). The results of this study provide evidence of jaw clenching's positive effects on the dynamic, whole-body explosive activity of a bat swing.

Restoration of coherent reach-grasp-pull movement via sequential intraneural peripheral nerve stimulation in rats.

Objective.Peripheral nerve stimulation (PNS) has been demonstrated as an effective way to selectively activate muscles and to produce fine hand movements. However, sequential multi-joint upper limb movements, which are critical for paralysis rehabilitation, has not been tested with PNS. Here, we aimed to restore multiple upper limb joint movements through an intraneural interface with a single electrode, achieving coherent reach-grasp-pull movement tasks through sequential stimulation.Approach.A transverse intrafascicular multichannel electrode was implanted under the axilla of the rat's upper limb, traversing the musculocutaneous, radial, median, and ulnar nerves. Intramuscular electrodes were implanted into the biceps brachii (BB), triceps brachii (TB), flexor carpi radialis (FCR), and extensor carpi radialis (ECR) muscles to record electromyographic (EMG) activity and video recordings were used to capture the kinematics of elbow, wrist, and digit joints. Charge-balanced biphasic pulses were applied to different channels to recruit distinct upper limb muscles, with concurrent recording of EMG signals and joint kinematics to assess the efficacy of the stimulation. Finally, a sequential stimulation protocol was employed by generating coordinated pulses in different channels.Main results.BB, TB, FCR and ECR muscles were selectively activated and various upper limb movements, including elbow flexion, elbow extension, wrist flexion, wrist extension, digit flexion, and digit extension, were reliably generated. The modulation effects of stimulation parameters, including pulse width, amplitude, and frequency, on induced joint movements were investigated and reach-grasp-pull movement was elicited by sequential stimulation.Significance.Our results demonstrated the feasibility of sequential intraneural stimulation for functional multi-joint movement restoration, providing a new approach for clinical rehabilitation in paralyzed patients.

Experimental Validation of an Upper Limb Benchmarking Framework in Healthy and Post-Stroke Individuals: A Pilot Study.

In the context of neurorehabilitation, there have been rapid and continuous improvements in sensors-based clinical tools to quantify limb performance. As a result of the increasing integration of technologies in the assessment procedure, the need to integrate evidence-based medicine with benchmarking has emerged in the scientific community. In this work, we present the experimental validation of our previously proposed benchmarking scheme for upper limb capabilities in terms of repeatability, reproducibility, and clinical meaningfulness. We performed a prospective multicenter study on neurologically intact young and elderly subjects and post-stroke patients while recording kinematics and electromyography. 60 subjects (30 young healthy, 15 elderly healthy, and 15 post-stroke) completed the benchmarking protocol. The framework was repeatable among different assessors and instrumentation. Age did not significantly impact the performance indicators of the scheme for healthy subjects. In post-stroke subjects, the movements presented decreased smoothness and speed, the movement amplitude was reduced, and the muscular activation showed lower power and lower intra-limb coordination. We revised the original framework reducing it to three motor skills, and we extracted 14 significant performance indicators with a good correlation with the ARAT clinical scale. The applicability of the scheme is wide, and it may be considered a valuable tool for upper limb functional evaluation in the clinical routine.

Validation of OpenCap: A low-cost markerless motion capture system for lower-extremity kinematics during return-to-sport tasks.

Low-cost markerless motion capture systems offer the potential for 3D measurement of joint angles during human movement. This study aimed to validate a smartphone-based markerless motion capture system's (OpenCap) derived lower extremity kinematics during common return-to-sport tasks, comparing it to an established optoelectronic motion capture system. Athletes with prior anterior cruciate ligament reconstruction (12-18 months post-surgery) performed three movements: a jump-landing-rebound, single-leg hop, and lateral-vertical hop. Kinematics were recorded concurrently with two smartphones running OpenCap's software and with a 10-camera, marker-based motion capture system. Validity of lower extremity joint kinematics was assessed across 437 recorded trials using measures of agreement (coefficient of multiple correlation: CMC) and error (mean absolute error: MAE, root mean squared error: RMSE) across the time series of movement. Agreement was best in the sagittal plane for the knee and hip in all movements (CMC > 0.94), followed by the ankle (CMC = 0.84-0.93). Lower agreement was observed for frontal (CMC = 0.47-0.78) and transverse (CMC = 0.51-0.6) plane motion. OpenCap presented a grand mean error of 3.85° (MAE) and 4.34° (RMSE) across all joint angles and movements. These results were comparable to other available markerless systems. Most notably, OpenCap's user-friendly interface, free software, and small physical footprint have the potential to extend motion analysis applications beyond conventional biomechanics labs, thus enhancing the accessibility for a diverse range of users.