image: Conceptual Diagram of a Low-Power, High-Accuracy Sensing System Utilizing Signal Similarity (Example based on a wireless EEG device)
Credit: Daisuke Kanemoto and Tomoya Kumauchi
Osaka, Japan - Researchers at The University of Osaka have developed a groundbreaking energy-efficient and high-precision measurement system leveraging the inherent similarity between waveforms generated by the same type of signal source. Unlike black-box approaches such as generative AI, the system is built on the explicit theoretical framework of compressed sensing. This innovative approach drastically reduces the amount of data required for accurate signal reproduction, leading to significant energy savings. Demonstrated with an electroencephalogram (EEG) measuring system, the technology achieved world-leading energy efficiency using only commercially available electronic components, consuming a mere 72μW. This breakthrough paves the way for long-term, battery-powered wearable devices and self-powered, battery-free IoT devices that can operate on minimal energy harvested from the environment, with broad applications in healthcare, disaster prevention, and environmental monitoring.
The proliferation of wearable devices and IoT sensors has highlighted the critical challenges of battery life and charging requirements. Achieving high-precision measurements while minimizing energy consumption has proven particularly difficult, demanding new technological breakthroughs. Conventional methods of reducing energy consumption in sensors often compromise waveform reproduction accuracy. Addressing this trade-off, The University of Osaka research group built upon their 2023 waveform similarity-based measurement theory to develop a system that achieves both energy efficiency and high precision.
The core of this innovation lies in exploiting the inherent similarity between waveforms emanating from a common source. This allows for significant data reduction while maintaining high-fidelity signal reconstruction. Unlike black-box approaches such as generative AI, the system is built on the explicit theoretical framework of compressed sensing. The researchers implemented an EEG measurement system using readily available components, including a general-purpose microcontroller (nRF52840). This system minimized power consumption to an impressive 72μW for all measurement operations, from analog-to-digital conversion to wireless transmission. By leveraging waveform similarities between previously recorded EEG data from other subjects and the current subject's data, the system achieved high-accuracy waveform reproduction, demonstrating a Normalized Mean Squared Error (NMSE) of 0.116 averaged over 500 measurements.
The successful demonstration of this energy-efficient, high-precision measurement system using off-the-shelf components for EEG measurement has far-reaching implications. It opens exciting new possibilities for wearable devices capable of continuous, long-term bio-signal monitoring powered by compact, lightweight batteries. Furthermore, it enables the development of self-powered, battery-free IoT devices and infrastructure monitoring sensors using energy harvesting technologies. These advancements promise significant contributions to sustainable development across diverse fields, including healthcare, elderly care, disaster preparedness, and environmental monitoring.
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About The University of Osaka
The University of Osaka was founded in 1931 as one of the seven imperial universities of Japan and is now one of Japan's leading comprehensive universities with a broad disciplinary spectrum. This strength is coupled with a singular drive for innovation that extends throughout the scientific process, from fundamental research to the creation of applied technology with positive economic impacts. Its commitment to innovation has been recognized in Japan and around the world, being named Japan's most innovative university in 2015 (Reuters 2015 Top 100) and one of the most innovative institutions in the world in 2017 (Innovative Universities and the Nature Index Innovation 2017). Now, Osaka University is leveraging its role as a Designated National University Corporation selected by the Ministry of Education, Culture, Sports, Science and Technology to contribute to innovation for human welfare, sustainable development of society, and social transformation.
Website: https://resou.osaka-u.ac.jp/en
Method of Research
Experimental study
Subject of Research
Not applicable