ArticleIEEE transactions on biomedical circuits and systems2024
A Low-Noise Low-Power 0.001Hz-1kHz Neural Recording System-on-Chip With Sample-Level Duty-Cycling.
Article in IEEE transactions on biomedical circuits and systems, 2024. 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.
- Chip-based high-precision fluorescent fiber-optic temperature sensor.Scientific reports · 2026Article
- Advances in (Bio)Sensors for Physiological Monitoring: A Special Issue Review.Sensors (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Advances in brain-machine interfaces and wearable biomedical sensors for healthcare and human-computer interactions call for precision electrophysiology to resolve a variety of biopotential signals across the body that cover a wide range of frequencies, from the mHz-range electrogastrogram (EGG) to the kHz-range electroneurogram (ENG). Existing integrated wearable solutions for minimally invasive biopotential recordings are limited in detection range and accuracy due to trade-offs in bandwidth, noise, input impedance, and power consumption. This article presents a 16-channel wide-band ultra-low-noise neural recording system-on-chip (SoC) fabricated in 65nm CMOS for chronic use in mobile healthcare settings that spans a bandwidth of 0.001 Hz to 1 kHz through a featured sample-level duty-cycling (SLDC) mode. Each recording channel is implemented by a delta-sigma analog-to-digital converter (ADC) achieving 1.0 μ V
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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.