ArticleNature electronics2024
An asynchronous wireless network for capturing event-driven data from large populations of autonomous sensors.
Article in Nature electronics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- High-channel-count neural recording and stimulation platform with 5376 simultaneous recording channels.npj biomedical innovations · 2026Article
- Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Time-Aware Graph Neural Network for Asynchronous Multi-Station Integrated Sensing and Communications Fusion in Open RAN.Sensors (Basel, Switzerland) · 2026Article
- High-channel-count neural recording and stimulation platform with 5,376 simultaneous recording channels.bioRxiv : the preprint server for biology · 2026Article
- Intracortical Microstimulation in Brain-Computer Interfaces: Evoking Perception and Plasticity.Cyborg and bionic systems (Washington, D.C.) · 2026Review
- Distributed implantable microchips as wireless networks for neural sensing and stimulation.Frontiers in neuroscience · 2026Review
- In-sensor analog optoelectronic processing of concurrent event and memory signals for dynamic vision sensing.Nature communications · 2025Article
- Multitarget neurostimulation of the deep brain: clinical opportunities, challenges, and emerging technologies.Journal of neural engineering · 2025Review
- Patterned electrical brain stimulation by a wireless network of implantable microdevices.Nature communications · 2024Article
- Advances in Machine Learning for Wearable Sensors.ACS nano · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Networks of spatially distributed radiofrequency identification sensors could be used to collect data in wearable or implantable biomedical applications. However, the development of scalable networks remains challenging. Here we report a wireless radiofrequency network approach that can capture sparse event-driven data from large populations of spatially distributed autonomous microsensors. We use a spectrally efficient, low-error-rate asynchronous networking concept based on a code-division multiple-access method. We experimentally demonstrate the network performance of several dozen submillimetre-sized silicon microchips and complement this with large-scale in silico simulations. To test the notion that spike-based wireless communication can be matched with downstream sensor population analysis by neuromorphic computing techniques, we use a spiking neural network machine learning model to decode prerecorded open source data from eight thousand spiking neurons in the primate cortex for accurate prediction of hand movement in a cursor control task.
Indexed as
Identifiers
What OpenQuestion holds
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.