Modern biomechanics motion analysis is no longer limited to a fixed lab and cameras in a calibrated volume. With wearable inertial motion capture technology, you can capture kinematics data in 3D in the lab, clinic, or real-world environments, while keeping your methods consistent across participants and sessions.
In most motion research workflows, the goal is to quantify how the body moves during a task and translate those signals into metrics that can be compared across trials, conditions, and populations. Common outputs include:
Kinematics: joint angles, segment orientation, range of motion, velocity, acceleration
Spatiotemporal metrics: step length, cadence, step width, timing
Symmetry and coordination: left right differences, inter joint coordination
Task specific outcomes: reach strategy, trunk contribution, movement variability
This is where 3D motion analysis becomes essential. You need reliable 3D movement data to compute consistent metrics and support meaningful comparisons in biomechanical research.
A typical motion capture system workflow has three stages:
Motion capture records segment motion over time and reconstructs a 3D representation of the movement. Many biomechanics teams use IMUs (inertial measurement units) to record linear acceleration and angular velocity. Inertial systems are especially useful when you need portability, fast setup, and capture outside a lab environment.
Raw sensor data becomes meaningful when it is combined with a biomechanical model. This is the role of human movement simulation software. It estimates segment orientations, joint angles, and other kinematic outputs using anatomical modeling and sensor fusion algorithms.
Finally, researchers use movement analysis software and tools to:
visualize movement in 3D
compute metrics and summary statistics
compare trials, conditions, or cohorts
export outputs for further analysis in MATLAB, Python, or other biomechanics toolchains
Biomechanical engineering research and applied biomechanics have expanded beyond controlled lab tasks. Inertial motion capture adds value because it supports:
Repeatability: standardized protocols across sessions and operators
Real-world measurement: capture in clinics, training spaces, work environments, or outside
Time efficiency: faster turnaround from capture to results
Richer interpretation: full body context instead of single point measurements
If your work spans multiple environments, wearable motion capture for biomechanics helps maintain a consistent methodology while expanding where research can be conducted.
When comparing motion capture systems, focus on criteria that protect both data quality and research efficiency.
Look for performance evidence in metrics that matter to your studies, such as joint angle repeatability, segment length estimation, and gait measures, including step width.
Your biomechanical analysis software should support:
clear visualization and review
detailed outputs for kinematics and spatiotemporal metrics
export options that fit your analysis stack
models that align with your population and tasks
Consider setup time, calibration requirements, portability, and how easily the system fits your protocol. Wearable systems are often chosen for their ability to capture outside the lab and get users running quickly.
Documentation and validation resources matter when you scale studies or run multi-site projects. Prioritize systems with independent validation studies and a track record of use in peer-reviewed research.
Once you understand how motion capture is used in biomechanics, the next step is selecting a system that matches your research goals. Many teams use Xsens because it maps well to common requirements for measuring devices in biomechanical research across lab, clinic, and field work.
Capture outside camera volumes: Xsens wearable motion capture supports data collection in environments where optical setups are not feasible.
Full-body kinematics for biomechanical motion analysis: Xsens Analyze is designed for human motion analysis and supports exporting and integrating data with third-party tools, including MATLAB, in common biomechanics formats.
A biomechanical model and algorithm that keep evolving: Xsens constantly develops the system, including work on gender-specific models.
Research and validation resources: Xsens maintains a research and validation hub that helps teams find publications and reference validation work in their methods and discussion sections.
Learn more about Xsens motion capture options.
Biomechanical analysis relies on accurate 3D human motion measurements. With modern motion capture for biomechanics and strong movement analysis software, teams can run repeatable biomechanics 3D motion analysis in more places, with clearer insights and faster iteration.
Motion capture is used to capture full-body 3D movement, convert that data into kinematic and spatiotemporal variables using a biomechanical model, and report metrics that support research questions in performance, rehabilitation, ergonomics, and human movement science.
Common outputs include joint angles, segment orientations, range of motion, gait timing, step length, step width, symmetry metrics, and task-specific movement strategies.
Movement analysis software processes raw sensor data, applies sensor fusion engine algorithm and a biomechanical model, and outputs interpretable variables that you can visualize, compare, and export for statistical analysis and reporting.