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A smart neckband for tracking dietary intake

A smart neckband for tracking dietary intake
The sensor module, positioned on the thyrohyoid muscle, features a 45-degree pre-curved design and soft, waterproof encapsulation. Credit: Park et al

A smart neckband allows wearers to monitor their dietary intake. Automatically monitoring food and fluid intake can be useful when managing conditions including diabetes and obesity, or when maximizing fitness. But wearable technologies must be able to distinguish eating and drinking from similar movements, such as speaking and walking.

Chi Hwan Lee and colleagues propose a machine-learning enabled neckband that can differentiate body movements, speech, and fluid and food intake. The work is published in the journal PNAS Nexus.

The neckband's sensor module includes a surface electromyography sensor, a three-axis accelerometer, and a microphone. Together, these sensors can capture muscle activation patterns in the thyrohyoid muscle of the neck, along with body movements and acoustic signals.

  • A smart neckband for tracking dietary intake
    Subject wearing the smart neckband in a stationary state: stationary pose, speaking, fluid intake, and food intake. Credit: Park et al
  • A smart neckband for tracking dietary intake
    Time series data of surface electromyography sensor, three-axis acceleration, and microphone recordings captured over a 105 second interval, with the subject engaging in activities such as sitting at rest, speaking, and consuming fluid and food. Credit: Park et al

In a study of six volunteers, the algorithm correctly determined which movements were eating or drinking with an accuracy rate of about 96% for individual activities and 89% for concurrent activities.

The neckband is made of a stretchable, twistable, breathable, mesh-structured textile loaded with 47 active and passive components that can run on battery power for more than 18 hours between charges.

According to the authors, the neckband could be used in a closed-loop system combined with continuous glucose meter and to calculate insulin dosages for by identifying meal timings—or to aid athletes and other individuals interested in increasing their overall health and wellness.

More information: Taewoong Park et al, A machine-learning-enabled smart neckband for monitoring dietary intake, PNAS Nexus (2024). DOI: 10.1093/pnasnexus/pgae156

Journal information: PNAS Nexus
Provided by PNAS Nexus
Citation: A smart neckband for tracking dietary intake (2024, May 8) retrieved 15 June 2024 from
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