Cipher Skin Validates Accuracy of its BioSleeve for Motion Analysis

With a 98.1% accuracy rate, Cipher Skin BioSleeve is a highly reliable measurement tool to perform complex motion analysis and range of motion assessment.

Three-dimensional motion analysis and range of motion assessment are essential tests for injury prevention, rehabilitation, and return-to-play.

Although they are widely used by physical therapists and trainers, these tests are often limited by outdated or complicated measurement tools that currently exist.

How do we measure?

Complex motion analysis typically requires expensive equipment used in a controlled laboratory environment, operated only by an expert due to its complexity. Additionally, video-based motion capture requires specific cameras and equipment costing several thousands of dollars or more.

Joint range of motion can be measured with the universal goniometer, but its level of accuracy is highly questionable. While a fairly simple process, measurements can vary due to dependence on the experience level of the technician and can be subjective from one patient to another, leaving much room for error.

How do we offer athletes and physical therapists a measurement tool that is easy to wear, can be used in any performance environment, and at the same time, output reliable, accurate and objective data for range of motion assessment and motion analysis?

Cipher Skin BioSleeve offers a highly accurate and suitable tool to conduct these tests, producing only 1.9% angle measurement error. It gives users reliable, objective data while enabling them to perform testing anywhere.

The angle measurement accuracy of the BioSleeve has been validated in our Cipher Skin Lab, through a proven and reliable method.


Cipher Skin’s in-house angle measurement validation method

We assessed the accuracy of the angle outputs from the BioSleeve, displayed on the Digital Mirror application, by comparing them with a true reference using high-speed video capture as a trusted source.

The camera was first calibrated by capturing images with a goniometer oriented at known angles between 30 and 180 degrees. The images were processed using a program written in Matlab in which 3 points are tracked and the angle between them is calculated.

We then captured images once the Digital Mirror App displayed the desired angle, which would be analyzed for accuracy using the Matlab script.

The mean percentage difference in Digital Mirror angle output compared to the actual angle averaged 1.9% only.

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