Machine Learning for Bioelectronics on Wearable and Implantable Devices: Challenges and Potential

Goh, Guo Dong; Lee, Jia Min; Goh, Guo Liang; Huang, Xi; Lee, Samuel; Yeong, Wai Yee

doi:10.1089/ten.tea.2022.0119

Cited by 18 publications

(9 citation statements)

References 166 publications

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“…Potentially, machine learning techniques such as artificial neural network can be adopted and applied to discern the sensor outputs and predict the type of objects that is being manipulated by the gripper. [ 61 ]…”

Section: Resultsmentioning

confidence: 99%

A 3D Printing‐Enabled Artificially Innervated Smart Soft Gripper with Variable Joint Stiffness

Goh,

Nguyen

et al. 2023

Adv Materials Technologies

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The manufacturing industry has witnessed advancements in soft robotics, specifically in robotic grippers for handling fragile or irregular objects. However, challenges remain in balancing shape compliance, structural rigidity, weight, and sensor integration. To address these limitations, a 3D‐printed multimaterial gripper design is proposed. This approach utilizes a single, nearly fully automated 3D printing process to create a universal gripper with almost no assembly work. By processing functional polymer, polymer nanocomposite, and metal wire simultaneously, this technique enables multifunctionality. The gripper achieves different gripping configurations by adjusting joint stiffness through Joule heating of conductive polylactic acid material, ensuring shape conformance. Embedded metal wires, created using an in‐house wire embedding technique, form reliable high‐current‐loading interconnections for the conductive joints acting as the heater. Additionally, an integrated soft sensor printed in thermoplastic polyurethane (TPU) and conductive TPU detects compression levels and discerns handled samples. This study showcases the potential of 3D multimaterial printing for on‐demand fabrication of a smart universal gripper with variable stiffness and integrated sensors, benefiting the automation industry. Overall, this work presents an effective strategy for designing and fabricating integrated multifunctional structures using soft, rigid, and conductive materials, such as polymer, polymer nanocomposite, and metal through multimaterial 3D printing.

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Section: Resultsmentioning

confidence: 99%

A 3D Printing‐Enabled Artificially Innervated Smart Soft Gripper with Variable Joint Stiffness

Goh,

Nguyen

et al. 2023

Adv Materials Technologies

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“…The use of data analysis and real-time computation techniques, specifically machine learning and artificial intelligence (AI), also plays an important role in the progress of battery-free implantable systems. 32 The ability to incorporate AI in the device or facilitate communication strategies that enable cloud-based computation is a key advantage of remotely powered systems over electrochemically powered devices. The ability to produce large amounts of high-quality continuous data will become critical for increasingly capable implants that support diagnosis and treatment of complex diseases.…”

Section: Technological Advances In Implantable Systemsmentioning

confidence: 99%

Wireless Battery-free and Fully Implantable Organ Interfaces

Bhatia,

Hanna,

Stuart

et al. 2024

Chem. Rev.

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Advances in soft materials, miniaturized electronics, sensors, stimulators, radios, and battery-free power supplies are resulting in a new generation of fully implantable organ interfaces that leverage volumetric reduction and soft mechanics by eliminating electrochemical power storage. This device class offers the ability to provide high-fidelity readouts of physiological processes, enables stimulation, and allows control over organs to realize new therapeutic and diagnostic paradigms. Driven by seamless integration with connected infrastructure, these devices enable personalized digital medicine. Key to advances are carefully designed material, electrophysical, electrochemical, and electromagnetic systems that form implantables with mechanical properties closely matched to the target organ to deliver functionality that supports high-fidelity sensors and stimulators. The elimination of electrochemical power supplies enables control over device operation, anywhere from acute, to lifetimes matching the target subject with physical dimensions that supports imperceptible operation. This review provides a comprehensive overview of the basic building blocks of battery-free organ interfaces and related topics such as implantation, delivery, sterilization, and user acceptance. State of the art examples categorized by organ system and an outlook of interconnection and advanced strategies for computation leveraging the consistent power influx to elevate functionality of this device class over current battery-powered strategies is highlighted.

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“…283,284 Recent developments in machine learning and artificial intelligence can significantly improve the performance and reliability of these devices. 285 One potential application of machine learning is optimizing the design, process parameters, and material properties required for specific needs and fabrication of microelectrodes. Machine learning algorithms can analyze large data sets of microelectrode fabrication parameters and performance metrics to identify the optimal set of parameters for achieving high sensitivity and selectivity.…”

Section: Miniaturization and Integration Of Microelectrode Systemsmentioning

confidence: 99%

“…Recent developments in machine learning and artificial intelligence can significantly improve the performance and reliability of these devices . One potential application of machine learning is optimizing the design, process parameters, and material properties required for specific needs and fabrication of microelectrodes.…”

Section: Prospects Of 3d-printed Microelectrodes In Diagnosismentioning

confidence: 99%

Use of 3D Printing Techniques to Fabricate Implantable Microelectrodes for Electrochemical Detection of Biomarkers in the Early Diagnosis of Cardiovascular and Neurodegenerative Diseases

Zilinskaite,

Shukla,

Baradoke

2023

ACS Meas. Sci. Au

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This Review provides a comprehensive overview of 3D printing techniques to fabricate implantable microelectrodes for the electrochemical detection of biomarkers in the early diagnosis of cardiovascular and neurodegenerative diseases. Early diagnosis of these diseases is crucial to improving patient outcomes and reducing healthcare systems' burden. Biomarkers serve as measurable indicators of these diseases, and implantable microelectrodes offer a promising tool for their electrochemical detection. Here, we discuss various 3D printing techniques, including stereolithography (SLA), digital light processing (DLP), fused deposition modeling (FDM), selective laser sintering (SLS), and two-photon polymerization (2PP), highlighting their advantages and limitations in microelectrode fabrication. We also explore the materials used in constructing implantable microelectrodes, emphasizing their biocompatibility and biodegradation properties. The principles of electrochemical detection and the types of sensors utilized are examined, with a focus on their applications in detecting biomarkers for cardiovascular and neurodegenerative diseases. Finally, we address the current challenges and future perspectives in the field of 3D-printed implantable microelectrodes, emphasizing their potential for improving early diagnosis and personalized treatment strategies.

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Machine Learning for Bioelectronics on Wearable and Implantable Devices: Challenges and Potential

Cited by 18 publications

References 166 publications

A 3D Printing‐Enabled Artificially Innervated Smart Soft Gripper with Variable Joint Stiffness

A 3D Printing‐Enabled Artificially Innervated Smart Soft Gripper with Variable Joint Stiffness

Wireless Battery-free and Fully Implantable Organ Interfaces

Use of 3D Printing Techniques to Fabricate Implantable Microelectrodes for Electrochemical Detection of Biomarkers in the Early Diagnosis of Cardiovascular and Neurodegenerative Diseases

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