ReviewMicromachines2023
Acoustic Wake-Up Technology for Microsystems: A Review.
Review in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Acoustic Metamaterial Nanogenerator for Multi-Band Sound Insulation and Acoustic-Electric Conversion.Sensors (Basel, Switzerland) · 2025Article
- Advanced Noise Indicator Mapping Relying on a City Microphone Network.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microsystems with capabilities of acoustic signal perception and recognition are widely used in unattended monitoring applications. In order to realize long-term and large-scale monitoring, microsystems with ultra-low power consumption are always required. Acoustic wake-up is one of the solutions to effectively reduce the power consumption of microsystems, especially for monitoring sparse events. This paper presents a review of acoustic wake-up technologies for microsystems. Acoustic sensing, acoustic recognition, and system working mode switching are the basis for constructing acoustic wake-up microsystems. First, state-of-the-art MEMS acoustic transducers suitable for acoustic wake-up microsystems are investigated, including MEMS microphones, MEMS hydrophones, and MEMS acoustic switches. Acoustic transducers with low power consumption, high sensitivity, low noise, and small size are attributes needed by the acoustic wake-up microsystem. Next, acoustic features and acoustic classification algorithms for target and event recognition are studied and summarized. More acoustic features and more computation are generally required to achieve better recognition performance while consuming more power. After that, four different system wake-up architectures are summarized. Acoustic wake-up microsystems with absolutely zero power consumption in sleep mode can be realized in the architecture of zero-power recognition and zero-power sleep. Applications of acoustic wake-up microsystems are then elaborated, which are closely related to scientific research and our daily life. Finally, challenges and future research directions of acoustic wake-up microsystems are elaborated. With breakthroughs in software and hardware technologies, acoustic wake-up microsystems can be deployed for ultra-long-term and ultra-large-scale use in various fields, and play important roles in the Internet of Things.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.