How can you use motion capture technology to evaluate automotive seating?

3 What equipment and software do you need?

When selecting a mocap system for seating evaluation, you should consider your budget, space, and accuracy requirements. Optical mocap systems use cameras and markers attached to the body or the seat to track motion and offer high accuracy and resolution, but they can be expensive, bulky, and sensitive to interference. Inertial mocap systems use sensors embedded in suits or straps that measure acceleration, rotation, and magnetic field of the body or the seat. They are cheaper, smaller, and more portable than optical systems but can suffer from drift, noise, or calibration issues. Pressure mocap systems use mats or pads that measure pressure distribution on the seat surface but can be affected by temperature, humidity, or wear and tear. To process and analyze data collected by the mocap system, you will need software that can import, edit, visualize, and export motion data. Popular software options include MotionBuilder for 3D animation handling large data sets; Vicon Blade for mocap with optical systems from Vicon or other brands; and Qualisys Track Manager for mocap with optical systems from Qualisys or other brands.

4 What are the benefits of using mocap for seating evaluation?

Mocap for seating evaluation can be a great asset, providing benefits such as improved comfort and ergonomics, enhanced safety and performance, increased customer satisfaction and loyalty, and a decrease in cost and time for the design process. It can identify and solve issues that cause discomfort, pain, or fatigue for users, optimize the position, orientation, and adjustment of seat components, create seats that fit the needs of different segments of the market, and validate prototypes, test hypotheses, or refine design decisions.

5 What are the challenges of using mocap for seating evaluation?

Using mocap for seating evaluation can also pose some challenges. Finding the right balance between realism and repeatability in mocap experiments can be difficult, as you want to simulate real-world conditions while controlling variables. Additionally, the complexity and variability of the human body and behavior must be taken into account, as individual differences and dynamic changes affect how people sit, move, and react to seats. Lastly, managing the large amount of data and multiple dimensions of analysis generated by mocap can be a challenge, requiring you to select relevant data and metrics that answer research questions and support design goals.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?