New energy-efficient technology enables AI within wearable devices

According to the developers, the device uses significantly less energy than current technologies, as the nanoelectronic technology can crunch large amounts of data and perform AI tasks in real time without sending data to the cloud for analysis.

With its footprint, low power consumption and a proven lack of lag time to receive analyses, the device can be incorporated into wearable electronics, like smart watches and fitness trackers, for real-time data processing and near-instant diagnostics.

To test the technology, researchers trained the device to interpret data from ECGs, a task that typically requires significant time from health care workers. The AI was then asked to classify six types of heart beats, such as normal to atrial premature beat and premature ventricular contraction.

 It was found that the device could correctly identify an irregular heartbeat and determine the arrhythmia subtype from among six different categories with near 95 per cent accuracy.

The study’s senior author, Mark C. Hersam, said: “Today, most sensors collect data and then send it to the cloud, where the analysis occurs on energy-hungry servers before the results are finally sent back to the user. This approach is incredibly expensive, consumes significant energy and adds a time delay.