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Neural network-based Bluetooth synchronization of multiple wearable devices

Engineering and Technology

Neural network-based Bluetooth synchronization of multiple wearable devices

K. K. Balasubramanian, A. Merello, et al.

This exciting research by Karthikeyan Kalyanasundaram Balasubramanian and colleagues introduces a groundbreaking application-level solution for synchronizing Bluetooth-enabled wearable devices. Utilizing a neural network, the team compensates for timing variations in high-frequency motion capture, paving the way for advancements in wireless communications beyond Bluetooth.

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Playback language: English
Abstract
This paper presents an application-level solution for synchronizing multiple Bluetooth-enabled wearable devices. A neural network analyzes timing variations at each node, compensating for time shifts and fine-tuning a virtual clock to achieve synchronization. The solution is demonstrated using Kinematics Detectors for high-frequency (200 Hz) synchronized motion capture, and is independent of the physical layer, potentially applicable to other wireless protocols.
Publisher
Nature Communications
Published On
Jul 25, 2023
Authors
Karthikeyan Kalyanasundaram Balasubramanian, Andrea Merello, Giorgio Zini, Nathan Charles Foster, Andrea Cavallo, Cristina Becchio, Marco Crepaldi
Tags
Bluetooth
wearable devices
synchronization
neural network
motion capture

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