Miniaturized wireless gastric pacing via inductive power transfer with non-invasive monitoring using cutaneous Electrogastrography

Author:

Perley Andrew,Roustaei Mehrdad,Aguilar-Rivera Marcelo,Kunkel David C.,Hsiai Tzung K.,Coleman Todd P.,Abiri ParinazORCID

Abstract

Abstract Background Gastroparesis is a debilitating disease that is often refractory to pharmacotherapy. While gastric electrical stimulation has been studied as a potential treatment, current devices are limited by surgical complications and an incomplete understanding of the mechanism by which electrical stimulation affects physiology. Methods A leadless inductively-powered pacemaker was implanted on the gastric serosa in an anesthetized pig. Wireless pacing was performed at transmitter-to-receiver distances up to 20 mm, frequency of 0.05 Hz, and pulse width of 400 ms. Electrogastrogram (EGG) recordings using cutaneous and serosal electrode arrays were analyzed to compute spectral and spatial statistical parameters associated with the slow wave. Results Our data demonstrated evident change in EGG signal patterns upon initiation of pacing. A buffer period was noted before a pattern of entrainment appeared with consistent and low variability in slow wave direction. A spectral power increase in the EGG frequency band during entrainment also suggested that pacing increased strength of the slow wave. Conclusion Our preliminary in vivo study using wireless pacing and concurrent EGG recording established the foundations for a minimally invasive approach to understand and optimize the effect of pacing on gastric motor activity as a means to treat conditions of gastric dysmotility.

Funder

National Institute of General Medical Sciences

National Heart, Lung, and Blood Institute

National Institute of Biomedical Imaging and Bioengineering

Publisher

Springer Science and Business Media LLC

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Electrogastrography measurement systems and analysis methods used in clinical practice and research: comprehensive review;Frontiers in Medicine;2024-07-01

2. A Review Based On Classifying Regular And Improper Gastrointestinal Waves Using CNN;2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2023-05-12

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