Ultra-soft and highly stretchable tissue-adhesive hydrogel based multifunctional implantable sensor for monitoring of overactive bladder

Oh, Byungkook; Lim, Young-Soo; Ko, Kun Woo; Seo, Hyeonyeob; Kim, Dong Jun; Kong, Dukyoo; You, Jae Min; Kim, Hansoul; Kim, Taek‐Soo; Park, Seongjun; Kwon, Dong‐Soo; Na, Joon Chae; Han, Woong Kyu; Park, Sung Min; Park, Steve

doi:10.1016/j.bios.2023.115060

Cited by 18 publications

(1 citation statement)

References 37 publications

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“…In addition to SCI, the device can be further utilized to investigate other nervous system disorders in animal models through its versatile functionality. Especially, it can offer significant benefits for many indications requiring long-term evaluation including gastrointestinal disorders [40], bladder dysfunction [41], obesity management [42], and epileptic seizures [43].…”

Section: Discussionmentioning

confidence: 99%

Fully Implantable Neurostimulation System for Long-Term Behavioral Animal Study

Kang,

Lee,

Choi

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Spinal cord stimulation (SCS) is an emerging therapeutic option for patients with neuropathic pain due to spinal cord injury (SCI). Numerous studies on pain relief effects with SCS have been conducted and demonstrated promising resultswhile the mechanisms of analgesic effect during SCS remain unclear. However, an experimental system that enables large-scale long-term animal studies is still an unmet need for those mechanistic studies. This study proposed a fully wireless neurostimulation system that can efficiently support a long-term animal study for neuropathic pain relief. The developed system consists of an implantable stimulator, an animal cage with an external charging coil, and a wireless communication interface. The proposed device has the feature of remotely controlling stimulation parameters via radio-frequency (RF) communication and wirelessly charging via magnetic induction in freely moving rats. Users can program stimulation parameters such as pulse width, intensity, and duration through an interface on a computer. The stimulator was packaged with biocompatible epoxy to ensure long-term durability under in vivo conditions. Animal experiments using SCI rats were conducted to demonstrate the functionality of the device, including long-term usability and therapeutic effects. The developed system can be tailored to individual user needs with commercially available components, thus providing a costeffective solution for large-scale long-term animal studies on neuropathic pain relief.

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Section: Discussionmentioning

confidence: 99%

Fully Implantable Neurostimulation System for Long-Term Behavioral Animal Study

Kang,

Lee,

Choi

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Recent Advances in Hydrogel‐Based Soft Bioelectronics and its Convergence with Machine Learning

Lee,

Kim

et al. 2024

Adv Eng Mater

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Recent advancements in artificial intelligence (AI) technologies, particularly machine learning (ML) techniques, have opened up a promising frontier in the development of intelligent soft bioelectronics, demonstrating unparalleled performance in interfacing with the human body. Hydrogels, owing to their unique combination of biocompatibility, tunable mechanical properties, and high water content, have emerged as a versatile platform for constructing soft bioelectronic devices. Functionalized hydrogels, such as conductive hydrogels, can efficiently capture biosignals from various target tissues while seamlessly forming conformal and reliable interfaces. They can also function as an intermediary layer between biological tissues and soft bioelectronics for diagnosis and therapy purposes. Meanwhile, ML has demonstrated its efficacy in processing extensive datasets collected from the bioelectronics. The convergence of hydrogel‐based soft bioelectronics and ML has unlocked a myriad of possibilities in unprecedented diagnostics, therapeutics, and beyond. In this review, the latest advances in hydrogel‐based soft bioelectronics are introduced. After briefly describing the materials and device strategies for high‐performance hydrogel bioelectronics, how ML can be integrated to augment the functionalities is discussed. Recent examples of ML‐integrated hydrogel bioelectronics are then discussed. Finally, the review is concluded by introducing future potential applications of AI in hydrogel‐based bioelectronics, alongside inherent challenges in this interdisciplinary domain.

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Bioelectronic Implantable Devices for Physiological Signal Recording and Closed‐Loop Neuromodulation

Oh,

Jekal,

Liu

et al. 2024

Adv Funct Materials

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Bioelectronic implantable devices are adept at facilitating continuous monitoring of health and enabling the early detection of diseases, offering insights into the physiological conditions of various bodily organs. Furthermore, these advanced systems have therapeutic capabilities in neuromodulation, demonstrating their efficacy in addressing diverse medical conditions through the precise delivery of stimuli directly to specific targets. This comprehensive review explores developments and applications of bioelectronic devices within the biomedical field. Special emphasis is placed on the evolution of closed‐loop systems, which stand out for their dynamic treatment adjustments based on real‐time physiological feedback. The integration of Artificial Intelligence (AI) and edge computing technologies is discussed, which significantly bolster the diagnostic and therapeutic functions of these devices. By addressing elemental analyses, current challenges, and future directions in implantable devices, the review aims to guide the pathway for advances in bioelectronic devices.

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Ultra-soft and highly stretchable tissue-adhesive hydrogel based multifunctional implantable sensor for monitoring of overactive bladder

Cited by 18 publications

References 37 publications

Fully Implantable Neurostimulation System for Long-Term Behavioral Animal Study

Fully Implantable Neurostimulation System for Long-Term Behavioral Animal Study

Recent Advances in Hydrogel‐Based Soft Bioelectronics and its Convergence with Machine Learning

Bioelectronic Implantable Devices for Physiological Signal Recording and Closed‐Loop Neuromodulation

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