Energy-Efficient Frequency Selection Method for Bio-Signal Acquisition in AI/ML Wearables
Author:
Affiliation:
1. Embedded Systems Laboratory (ESL), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
2. EcoCloud, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Funder
Nespresso SA
ETH Board ? Joint Initiative
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3665314.3670815
Reference21 articles.
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3. Analog Devices. 2023. AD4130-8. https://www.analog.com/en/products/ad4130-8.html. Accessed: 7 March 2024.
4. D. Bellasi et al. 2017. A wide tuning-range ADFLL for mW-SoCs with dithering-enhanced accuracy in 65 nm CMOS. In ISCAS.
5. S. Benatti et al. 2019. Online learning and classification of EMG-based gestures on a parallel ultra-low power platform using hyperdimensional computing. TBioCAS (2019).
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