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Measures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies or clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing both the kinematics (i.e., motion) and dynamics (i.e., forces) of human movement using videos captured from two or more smartphones. OpenCap leverages pose estimation algorithms to identify body landmarks from videos; deep learning and biomechanical models to estimate three-dimensional kinematics; and physics-based simulations to estimate muscle activations and musculoskeletal dynamics. OpenCap’s web application enables users to collect synchronous videos and visualize movement data that is automatically processed in the cloud, thereby eliminating the need for specialized hardware, software, and expertise. We show that OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions. Additionally, we demonstrate OpenCap’s practical utility through a 100-subject field study, where a clinician using OpenCap estimated musculoskeletal dynamics 25 times faster than a laboratory-based approach at less than 1% of the cost. By democratizing access to human movement analysis, OpenCap can accelerate the incorporation of biomechanical metrics into large-scale research studies, clinical trials, and clinical practice.

[This corrects the article DOI: 10.1371/journal.pone.0187886.].

The field of tissue engineering continues to expand and mature, and several products are now in clinical use, with numerous other preclinical and clinical studies underway. However, specific challenges still remain in the repair or regeneration of tissues that serve a predominantly biomechanical function. Furthermore, it is now clear that mechanobiological interactions between cells and scaffolds can critically influence cell behavior, even in tissues and organs that do not serve an overt biomechanical role. Over the past decade, the field of “functional tissue engineering” has grown as a subfield of tissue engineering to address the challenges and questions on the role of biomechanics and mechanobiology in tissue engineering. Originally posed as a set of principles and guidelines for engineering of load-bearing tissues, functional tissue engineering has grown to encompass several related areas that have proven to have important implications for tissue repair and regeneration. These topics include measurement and modeling of the in vivo biomechanical environment; quantitative analysis of the mechanical properties of native tissues, scaffolds, and repair tissues; development of rationale criteria for the design and assessment of engineered tissues; investigation of the effects biomechanical factors on native and repair tissues, in vivo and in vitro; and development and application of computational models of tissue growth and remodeling. Here we further expand this paradigm and provide examples of the numerous advances in the field over the past decade. Consideration of these principles in the design process will hopefully improve the safety, efficacy, and overall success of engineered tissue replacements.

Testing a prediction is fundamental to scientific experiments. Where biomechanical experiments involve analysis of 1-Dimensional (waveform) data, sample size estimation should consider both 1D variance and hypothesised 1D effects. This study exemplifies 1D sample size estimation using typical biomechanical signals and contrasts this with 0D (discrete) power analysis. For context, biomechanics papers from 2018 and 2019 were reviewed to characterise current practice. Sample size estimation occurred in approximately 4% of 653 papers and reporting practice was mixed. To estimate sample sizes, common biomechanical signals were sourced from the literature and 1D effects were generated artificially using the open-source power1d software. Smooth Gaussian noise was added to the modelled 1D effect to numerically estimate the sample size required. Sample sizes estimated using 1D power procedures varied according to the characteristics of the dataset, requiring only small-to-moderate sample sizes of approximately 5–40 to achieve target powers of 0.8 for reported 1D effects, but were always larger than 0D sample sizes (from N + 1 to >N + 20). The importance of a priori sample size estimation is highlighted and recommendations are provided to improve the consistency of reporting. This study should enable researchers to construct 1D biomechanical effects to address adequately powered, hypothesis-driven, predictive research questions.

Corneal biomechanics are critical to both normal physiology and pathological conditions such as keratoconus (KC), yet existing measurement techniques fail to assess regional variations in material stiffness, limiting early diagnosis and therapeutic evaluation. This study focuses on evaluating the symmetry characteristics of bilateral corneal biomechanical properties based on a corneal inflation testing, while systematically analyzing the spatial distribution differences of biomechanical parameters in KC lesion regions and following corneal cross-linking (CXL) treatment. Thirty-six New Zealand white rabbits were divided into normal, KC-induced (via type I collagenase), and CXL-treated (riboflavin/ultraviolet light) groups. Four weeks post-intervention, corneal inflation tests were conducted, and the shear modulus (μ), the strain hardening index (α), and the tangent modulus (Et) in 25 different cornea regions were calculated. In the normal group, corneal material stiffness was similar in all 25 regions considered, with mirror symmetry and the highest Et in the upper temporal central region while the lowest in the lower temporal and peripheral nasal regions. Et of the central region reduced significantly in the KC group, while no statistical difference was found between the bilateral eyes in other 24 regions (all P > 0.05). Et enhanced after CXL, with the greatest increase in the central region and varying effects in other areas, correlating with preoperative properties. The analysis method provided a robust tool for capturing the regional biomechanical variations and derives morphology-independent biomechanical parameters, revealing localized stiffness losses in keratoconus and heterogeneous post-corneal cross linking stiffness enhancement.

[Display omitted] Decellularized extracellular matrix (d-ECM) serves as an ideal scaffold for constructing artificial ovaries, a promising approach to fertility preservation for patients experiencing premature ovarian failure. The biomechanical properties of d-ECM are crucial for the development and maturation of follicles. However, there is no standardized or comprehensive framework for evaluating the various decellularization methods proposed in the literature. In this study, we developed a novel decellularization protocol for porcine ovaries using liquid nitrogen and hypertonic saline methods, comparing its effectiveness against conventional chemical and enzymatic techniques through histological analysis, quantitative assessments and biomechanical testing. Histological analyses demonstrated that our d-ECM protocols effectively removed cellular and nuclear materials (at least 95% reduction) while preserving the structural integrity of elastin and collagen fibers (maximum 15% reduction). Furthermore, tensile testing results indicated that the novel decellularization methods using liquid nitrogen and hypertonic saline retained mechanical properties most similar to those of the fresh group. Our findings expand the evaluation of decellularization techniques by incorporating the biomechanical properties of d-ECM. Additionally, we provide valuable insights for enhancing decellularization methods and identifying optimal scaffolds for artificial ovaries.

Spine biomechanics is at a transformation with the advent and integration of machine learning and computer vision technologies. These novel techniques facilitate the estimation of 3D body shapes, anthropometrics, and kinematics from as simple as a single-camera image, making them more accessible and practical for a diverse range of applications. This study introduces a framework that merges these methodologies with traditional musculoskeletal modeling, enabling comprehensive analysis of spinal biomechanics during complex activities from a single camera. Additionally, we aim to evaluate their performance and limitations in spine biomechanics applications. The real-world applications explored in this study include assessment in workplace lifting, evaluation of whiplash injuries in car accidents, and biomechanical analysis in professional sports. Our results demonstrate potential and limitations of various algorithms in estimating body shape, kinematics, and conducting in-field biomechanical analyses. In industrial settings, the potential to utilize these new technologies for biomechanical risk assessments offers a pathway for preventive measures against back injuries. In sports activities, the proposed framework provides new opportunities for performance optimization, injury prevention, and rehabilitation. The application in forensic domain further underscores the wide-reaching implications of this technology. While certain limitations were identified, particularly in accuracy of predictions, complex interactions, and external load estimation, this study demonstrates their potential for advancement in spine biomechanics, heralding an optimistic future in both research and practical applications.

Marker-based motion capture is a fundamental tool in biomechanical analysis, yet comes with major constraints such as time, cost and accessibility. This study aimed to validate the use of OpenCap, a free, markerless motion capture system compared to a marker-based motion capture system to measure lower extremity kinematics during functional tasks. 20 individuals from an athletic population (18 females, 2 males) performed two gait trials (walking, running) and three functional tasks (double leg squat, countermovement jump, jump-landing). Lower extremity peak joint kinematics were collected simultaneously using Vicon and OpenCap to assess the validity of markerless motion capture. Strong agreements were observed in the frontal hip plane joint kinematics across all tasks with root mean squared errors below 6°. Moderate agreements were observed in the sagittal knee plane joint kinematics (4–10°) and there was a weak agreement in the gait trials of the sagittal hip measures (>10°). The results from the study indicate the need for further research on the use of OpenCap in clinical settings. The findings align with previous studies with similar agreements observed in the frontal hip and sagittal knee measures. Validating the use of an open-source motion capture software could provide clinicians and researchers an accessible tool for in depth biomechanical assessments.

Multiple camera systems are widely used for 3D-motion analysis. Due to increasing accuracies these camera systems gained interest in biomechanical research areas, where high precision measurements are desirable. In the current study different measurement systems were compared regarding their measurement accuracy. Translational and rotational accuracy measurements as well as the zero offset measurements of seven different measurement systems were performed using two reference devices and two different evaluation algorithms. All measurements were performed in the same room with constant temperature at the same laboratory. Equal positions were measured with the systems according to a standardized protocol. Measurement errors were determined and compared. The highest measurement errors were seen for a measurement system using active ultrasonic markers, followed by another active marker measurement system (infrared) having measurement errors up to several hundred micrometers. The highest accuracies were achieved by three stereo camera systems, using passive 2D marker points having errors typically below 20 [mu]m. This study can help to better assess the results obtained with different measurement systems. With the focus on the measurement accuracy, only one aspect in the selection of a system was considered. Depending on the requirements of the user, other factors like measurement frequency, the maximum analyzable volume, the marker type or the costs are important factors as well.

Disease progression is usually accompanied by changes in the biochemical composition of cells and tissues and their biophysical properties. For instance, hallmarks of cancer include the stiffening of tissues caused by extracellular matrix remodelling and the softening of individual cancer cells. In this context, accumulating evidence has shown that immune cells sense and respond to mechanical signals from the environment. However, the mechanisms regulating these mechanical aspects of immune surveillance remain partially understood. The growing appreciation for the ‘mechano-immunology’ field has urged researchers to investigate how immune cells sense and respond to mechanical cues in various disease settings, paving the way for the development of novel engineering strategies that aim at mechanically modulating and potentiating immune cells for enhanced immunotherapies. Recent pioneer developments in this direction have laid the foundations for leveraging ‘mechanical immunoengineering’ strategies to treat various diseases. This Review first outlines the mechanical changes occurring during pathological progression in several diseases, including cancer, fibrosis and infection. We next highlight the mechanosensitive nature of immune cells and how mechanical forces govern the immune responses in different diseases. Finally, we discuss how targeting the biomechanical features of the disease milieu and immune cells is a promising strategy for manipulating therapeutic outcomes. This Review highlights the current understanding of mechanisms underlying the mechanical changes occurring in diseased and immune cells and discusses new approaches to leverage and target biomechanical cues for immune engineering at various length scales for therapeutic interventions.