Wearables and Holdables

Use Reality AI to detect how customers are behaving while using, holding or wearing your device.

Build the next generation of connected consumer, health, and medical devices

Use accelerometers, sound, and medical/biometric sensors to identify specific human activities, surrounding context and health indicators. Our technology easily detects the most subtle movements, in high-variation activities and noisy data.


Watch our Demonstration Video

Subtle differences in activity or motion can be detected with Reality AI using accelerometers sampled at 50-100Hz.

For another accelerometer demo using the NXP i.MXRT

Typical sample rates when working with accelerometers and vibration sensors

You'll get your best results with Reality AI when you use time waveforms as your input data and you select an appropriate sample rate. If time waveform isn't practical, we can also work with FFT as input - though we prefer as much frequency and time resolution as possible. In some cases our tools can get good results with Peak-to-Peak, RMS and similar values, but the more information the tools can get in the frequency and time domains, the better.


>> Learn more about our ready-to-use Edge AI Solutions <<

Learn more with our Technical Whitepaper

Explore the technical details behind the Reality AI approach to machine learning with signals

  • Why signals require a different approach than other machine learning problems

  • The importance of "features" to effective machine learning

  • Why the FFT probably isn't good enough, and what other options are better

  • The difference between Reality AI and Deep Learning