Smart Wearable Test Lab

This Lab validates smart wearable devices with the Fusion Sensor Validation Library (Motion Library). With scenario simulations and AI-driven automation, this lab will help us validate the stability of the sensors, as well as the fusion algorithm of the devices in different scenarios.

Benefits of Smart Wearable Test Lab

From smart bracelets, watches to VR glasses, wearable devices are widely used in many applications. But unlike traditional consumer electronics, wearable devices are typically stripped to user’s arm or head for a long time, and can be used in activities like outdoor sports, indoor fitness, swimming, and more. With such diverse applications and long-time usage, wearables are exposed to countless environmental and scenario factors that could lead to potential risks.

Potential Risks of Wearable

Stability and accuracy of the sensors

Wearable devices are driven by different sensors. Accelerators are used to detect movements such as swinging, walking. Gyroscopes are used to navigate and measure angular velocity. These sensors are sensitive to surrounding environments and once damaged, could lead to unsatisfying issues such as inaccuracies in sports performance.

Inconsistent performance in different user-scenarios

Since wearables can be worn by almost anyone (children, athletes, adults) and can be used in versatile applications (sports, health management, gaming), it is very likely to have inconsistent performance in different scenarios. It is challenging to make sure that wearable devices can have consistent performance in any real-life scenarios.

Interoperability Issues

According to our test results, around 70% of issues found in Bluetooth wearable devices are related to connectivity, and among them 45% of the issues are pairing problems

Fusion Sensor Validation: A Smart Test for Smart Wearable

The Fusion Sensor Validation is consists of Motion Library and AI-driven test tools to offer customized scenario tests.

The Motion Library is a database that stores rich motion patterns, which are simulations of user-behaviors under different scenarios. Wearable manufactueres can test their devices in terms of:

  • Wearable sensor stability (How consistent and stable the sensors are)
  • Fusion algorithm (Is the device delivering exceptional user-experience?)

Comprehensive Solutions for Smart Wearable
Allion provides consultancy starting at the developmental stage, and with the Motion Library, IoP Test, and Reliability Test, we can help manufacturers all the way to the performance tests of their end products:

Interoperability Test (Global IoT Center)- Making sure your devices can always be connected

Our Global IoT Center is consists of comprehensive smart devices, including mobile phones, tablets, TV, smart speakers, and laptops. Here at Allion Labs, we provide manufacturers the necessary devices and facilities to engage in interoperability tests.For more details, please visit Allion Interoperability Test Center

Reliability Test- The stability of sensors

Our test chambers are designed to perform reliability tests, which are essential for wearable devices as many are designed for outdoor sports and interactive gaming. It is essential to get them tested in different environmental simulations.
Extreme environment test, humidity and thermal test, and shock and vibration tests, accelerated life cycle test are available here at Allion

***AI-enabled Motion Library -Testing the fusion algorithm of the devices

Motion Patterns are recorded and stored so we can run simulation tests of various user behaviors. So far, we have 5 major simulations categories: Basic Pattern, Walking Pattern, Running Pattern, Head Movement Pattern, and Hand Movement Pattern. These simulations, along with AI-driven tools, we can build consistent and repetitive test which will help us obtain rich data.Check out how we verify the performance of pedometers (smart bracelets) here: Tech Blog


Data-centric analysis to enhance your product performance
With the above tests, we can recreate how a user really use their devices in real-life scenarios. These simulations of scenarios, alongside AI-driven automation tests, will help manufacturers to get a better understanding of how their devices perform and what issues to fix