Evidence map›Paper›PMID 39399673›Full record

ArticleResearch square2024

Scalable networks of wireless bioelectronics using magnetoelectrics.

Joshua E Woods, Fatima Alrashdan, Ellie C Chen, Wendy Tan, Mathews John, Lukas Jaworski, Drew Bernard, Allison Post, Angel Moctezuma-Ramirez, Abdelmotagaly Elgalad and 7 more

Abstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Joshua E WoodsDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA.ORCID 0000-0001-5069-4678
Fatima AlrashdanDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Ellie C ChenDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Wendy TanDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Mathews JohnTexas Heart Institute, Houston, TX, USA.
Lukas JaworskiTexas Heart Institute, Houston, TX, USA.
Drew BernardTexas Heart Institute, Houston, TX, USA.
Allison PostTexas Heart Institute, Houston, TX, USA.
Angel Moctezuma-RamirezTexas Heart Institute, Houston, TX, USA.
Abdelmotagaly ElgaladTexas Heart Institute, Houston, TX, USA.
Alexander G SteeleDepartment of Neurosurgery, Houston Methodist, Houston, TX, USA.ORCID 0000-0001-5007-0638
Sean M BarberDepartment of Neurosurgery, Houston Methodist, Houston, TX, USA.
Philip J HornerHouston Methodist Research Institute, Houston, TX, USA.
Amir H FarajiDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Dimitry G SayenkoDepartment of Neurosurgery, Houston Methodist, Houston, TX, USA.
Mehdi RazaviTexas Heart Institute, Houston, TX, USA.ORCID 0000-0001-7176-5586
Jacob T RobinsonDepartment of Electrical and Computer Engineering, Rice University, Houston, TX, USA.

Funding

Harnessing Neuroplasticity of Postural Sensorimotor Networks Using Non-Invasive Spinal Neuromodulation to Maximize Functional Recovery After Spinal Cord InjuryR01NS119587 · NINDS · METHODIST HOSPITAL RESEARCH INSTITUTE · PI Dimitry Sayenko · 2022 to 2026
$3.2M
Leadless wirelessly powered pacemaker for multi chamber pacing using miniaturized pacing and sensing nodeR01HL144683 · NHLBI · TEXAS HEART INSTITUTE · PI BABAKHANI, AYDIN, RAZAVI, MEHDI · 2019 to 2022
$2.4M
NHLBI NIH HHS R01 HL144683NINDS NIH HHS R01 NS119587
6 · The paper itself

Abstract

Networks of miniature bioelectronic implants would enable precise measurement and manipulation of the complex and distributed physiological systems in the body. For example, sensing and stimulation nodes throughout the heart, brain, or peripheral nervous system would more accurately track and treat disease or support prosthetic technologies with many degrees of freedom. A main challenge to creating this type of in-body bioelectronic network is the fact that wireless power and data transfer are often inefficient when communicating through biological tissues. This challenge is typically compounded as one increases the number of implants within the network. Here, we show that magnetoelectric wireless data and power transfer enable a network of millimeter-sized bioelectronic implants where the power transfer efficiency of the system improves as the number of implanted devices increases. Using this property, we demonstrate networks of wireless battery-free bioelectronics ranging from 1 to 6 implants where the wireless power transfer efficiency for the system increases from 0.2% to 1.3%, with each node in the network receiving 2.2 mW at a distance of 1 cm. We use this system for efficient and robust wireless data and power transfer to demonstrate proof-of-concept networks of miniature spinal cord stimulators and cardiac pacing devices in large animals. The scalability of this network architecture enabled by magnetoelectric wireless power transfer provides a platform for building wireless closed-loop networks of bioelectronic implants for next-generation electronic medicine.

Identifiers

PMID39399673
PMCPMC11469518

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Registered trials

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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.