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NoiseFit Twist: A Budget-Friendly Smartwatch with Impressive Battery Life and Features

The NoiseFit Twist offers a remarkable package for its price

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Aditya Saikrishna
Aditya Saikrishna
I am 21 years old and an avid Motorsports enthusiast.

INDIA: Homegrown smartwatch brand Noise has been making waves in the wearable technology market with its latest addition to the lineup, the NoiseFit Twist. Priced at an astonishingly affordable Rs 1,999, this fully-functional smartwatch is capturing attention for its impressive features and outstanding battery life.

The NoiseFit Twist doesn’t compromise on functionality despite its wallet-friendly price tag. It boasts a 3.50-inch round TFT display, complete with IP68 dust and splash protection, making it suitable for both indoor and outdoor activities. 

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The watch supports Bluetooth calling and offers an array of health and fitness tracking features, making it a worthy competitor in the smartwatch arena.

While the NoiseFit Twist’s large dial design is eye-catching, the plastic frame and strap contribute to keeping costs low. The watch offers a comfortable fit with replaceable, soft silicone straps that blend seamlessly with various outfits. Its expansive 1.38-inch display provides ample space for information, even in bright sunlight.

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Performance-wise, the NoiseFit Twist doesn’t disappoint. It accurately tracks SPO2, heart rate, and sleep patterns. Surprisingly, its sensor accuracy rivals even medical-grade equipment, as verified during a COVID-19 illness.

Despite its strengths, the NoiseFit Twist is not without minor flaws. Touch response on the screen tends to be slower, and occasional syncing issues, especially with Bluetooth calling, have been reported. Nonetheless, considering its price point, these issues become more forgivable.

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Undoubtedly, the star feature of the NoiseFit Twist is its impressive battery life. Lasting up to 7 days with Bluetooth calling disabled, it outperforms many competitors. With Bluetooth calling enabled, it still delivers a commendable 3–4 days.

Also Read: Silent Spies: Deep Learning Model Stealthily Steals Data by Eavesdropping on Keyboard Sounds

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