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![Timeline/history for the development of biomedical devices fabricated using traditional manufacturing and 3D printing. i) First implantable cardiac pacemaker invented in 1958,[¹] ii) A digital glucometer based on test strip,[²] iii) schematic of microarray pattern fabrication via photolithography.[²⁵] iv) A microfluidic device using soft‐lithography replica molding,[²⁵] v) a set of electrochemical sensors on the same substrate for in vivo biomolecule detection.[²⁶] vi) First SLA‐printed 3D part created by Chuck Hull.[²⁷] vii) A 3D gear made by SLS method using metal powders and powder blends.[²⁸] viii) First use of a lab‐grown urinary bladder made from molded polymer for transplant surgery.[²⁹] ix) 3D printed (omnidirectional) microvascular networks within a hydrogel reservoir using direct ink writing method.[³⁰] x) 3D printed biosensors for online analysis of subcutaneous human microdialysate, a) a microvial, b) probe holder, c) sensor sealing holder, and d) glucose and lactate sensor probes. Reproduced with permission.[³¹] Copyright 2015, American Chemical Society. xi) A 3D printed lab‐on‐a‐chip device platform for biosensing applications.[¹⁷] Reproduced with permission.[¹⁷] Copyright 2015, Wiley‐VCH. xii) The 3D electrochemiluminescent detection platform for the measurement of cigarette and e‐cigarette smoke extracts and polluted water samples.[¹⁹] Reproduced with permission.[¹⁹] Copyright 2017, American Chemical Society. xiii) A textile‐mounted 3D capacitive fiber created for the detection of elongational strains.[²⁰] Reproduced with permission.[²⁰] Copyright 2020, Wiley‐VCH. xiv) 3D printed acoustic biosensor for infectious disease monitoring.[³²] Reproduced with permission.[³²] Copyright 2019, American Chemical Society. xv) A 10 s COVID‐19 test chip by enabling aerosol jet 3D nanoparticle printing.[³³] Reproduced with permission.[³³] Copyright 2020, Wiley‐VCH.](publication/356559762/figure/fig1/AS:11431281173040185@1688750905192/Timeline-history-for-the-development-of-biomedical-devices-fabricated-using-traditional.png)
Timeline/history for the development of biomedical devices fabricated using traditional manufacturing and 3D printing. i) First implantable cardiac pacemaker invented in 1958,[¹] ii) A digital glucometer based on test strip,[²] iii) schematic of microarray pattern fabrication via photolithography.[²⁵] iv) A microfluidic device using soft‐lithography replica molding,[²⁵] v) a set of electrochemical sensors on the same substrate for in vivo biomolecule detection.[²⁶] vi) First SLA‐printed 3D part created by Chuck Hull.[²⁷] vii) A 3D gear made by SLS method using metal powders and powder blends.[²⁸] viii) First use of a lab‐grown urinary bladder made from molded polymer for transplant surgery.[²⁹] ix) 3D printed (omnidirectional) microvascular networks within a hydrogel reservoir using direct ink writing method.[³⁰] x) 3D printed biosensors for online analysis of subcutaneous human microdialysate, a) a microvial, b) probe holder, c) sensor sealing holder, and d) glucose and lactate sensor probes. Reproduced with permission.[³¹] Copyright 2015, American Chemical Society. xi) A 3D printed lab‐on‐a‐chip device platform for biosensing applications.[¹⁷] Reproduced with permission.[¹⁷] Copyright 2015, Wiley‐VCH. xii) The 3D electrochemiluminescent detection platform for the measurement of cigarette and e‐cigarette smoke extracts and polluted water samples.[¹⁹] Reproduced with permission.[¹⁹] Copyright 2017, American Chemical Society. xiii) A textile‐mounted 3D capacitive fiber created for the detection of elongational strains.[²⁰] Reproduced with permission.[²⁰] Copyright 2020, Wiley‐VCH. xiv) 3D printed acoustic biosensor for infectious disease monitoring.[³²] Reproduced with permission.[³²] Copyright 2019, American Chemical Society. xv) A 10 s COVID‐19 test chip by enabling aerosol jet 3D nanoparticle printing.[³³] Reproduced with permission.[³³] Copyright 2020, Wiley‐VCH.
Source publication
Additive manufacturing, also called 3D printing, is a rapidly evolving technique that allows for the fabrication of functional materials with complex architectures, controlled microstructures, and material combinations. This capability has influenced the field of biomedical sensing devices by enabling the trends of device miniaturization, customiza...
Citations
... This process significantly decreases the cost and skill barrier of creating customized devices, as well as shortens the device iteration process. To date, 3D-printed microdevices have been reported for many applications, including droplet separation, generation, and sorting, microfluidics, cell manipulation, and multiple forms of detection/diagnostics [1][2][3][4][5][6][7][8][9][10]. Some applications have combined multiple components, such as 3D-printed microfluidic devices for electrochemical detection through the fabrication of devices that incorporate electrodes [11][12][13][14][15]. ...
3D-printed microdevices have become increasingly important to the advancement of point-of-care (POC) immunoassays. Despite its great potential, using 3D-printed surfaces on the solid support for immunorecognition has been limited due to the non-ideal adsorption properties for many photocurable resins. In this work, we report a simple surface modification protocol that works for diverse commercial photocurable resins, improving ELISAs performed directly on 3D-printed devices. This surface modification strategy involves surface activation via air plasma followed by the one-step incubation of GLYMO-labeled streptavidin. We successfully immobilized biotinylated anti-activin A antibodies on the 3D-printed surfaces and performed the complete ELISA protocol on the 3D-printed surfaces. We demonstrated that this protocol achieved an improved performance over passive adsorption for ELISAs. The present method is also compatible with diverse commercial resins and works with both microwells and microchannels. Finally, this method demonstrated a comparable limit of detection to the ELISA performed using commercial microwells. We believe the simplicity and broad compatibility of the present surface modification strategy will facilitate the development of 3D-printed POC ELISA devices.
... Selective laser melting (SLM) and SLS technologies are identical, with the exception that it requires a greater temperature during processing than SLS technique in order to fully melt the metal grains and produce homogeneous components [46]. The required temperature is provided by a higher power laser beam. ...
Novel sensors with applications in every aspect of human life have been developed
rapidly thanks to recent advancements in 3D printing technology and materials. The development of three-dimensional (3D) printing technology has completely changed the way electrochemical sensors are made, providing previously
unheard-of levels of customization and flexibility in both design and production.
This chapter explores the difficulties and potential benefits of 3D-printed electrochemical sensors in various applications. In order to improve sensor performance and durability, we address important issues such material selection, printing resolution, and surface modification approaches. Furthermore, to enable innovative sensor capabilities and applications, we investigate how 3D printing might be integrated with sophisticated sensing techniques such as nanomaterials, microfluidics, and biosensing. We also discuss new developments in 3D-printed sensors, including environmental monitoring, point-of-care diagnostics, and wearable and implantable sensors. Lastly, we outline prospects for further study and advancement of 3D-printed electrochemical sensors.
... Recently biomedical sensing devices are gaining rapid attention because of the ever growing needs of the healthcare sector. Mostly widely used biomedical sensors such as biomarkers, implantable sensors, haptic sensors, and microfluidic based biosensors [151]. Among them haptic sensor can be featured in high sophisticated brain-machine interfacing and futuristic gaming application [152]. ...
In light of the industry’s environmental constraints, sustainable manufacturing technology has emerged as a critical goal for emerging applications. Due to the increased need for electronic production around the world, the requirement for environmentally safe technology is the necessity of this decade as the world government shifts towards sustainability in all manufacturing technology. Henceforth, printed electronics will be one such solution to regulate the electronic device and components production requirement of this decade. The article has discussed about the recent advances in inkjet-printed electronics across a wide range of electronics applications. We have discussed several inkjet printing inks and their formulation methods, which are required for minimizing environmental waste. In addition, we have discussed the future scope of printed electronics production and its impact on the economy as well as the environment.
... Additive manufacturing, particularly 3D printing, has revolutionised device fabrication by allowing for rapid prototyping and customisable designs with minimal manufacturing processes. 3D-printed devices have demonstrated widespread applications ranging from wearable electronics to artificial prosthetics [22][23][24]. Among various 3D printing technologies, fused deposition modelling (FDM) is known for its fast and simple fabrication technologies with minimum operational requirements [25][26][27]. ...
With the growing demand for integrated smart home systems driven by advancements in the Internet of Things (IoT) and smart city initiatives, the need for efficient, simple, and self-sustaining sensors has become essential. Triboelectric nanogenerators (TENGs) have recently emerged as a promising device for both energy harvesting and sensing. However, the fabrication of different TENG layers using conventional techniques is often complex, time-intensive, and involves multiple processing steps. Here, a single-step multi-material 3D printing (MMP) approach is used to fabricate the fully functional TENG device, consisting of positive and negative triboelectric layers, current collectors and supporting substrate. Nylon 6 and carbon/polyvinylidene fluoride (C/PVDF) filaments are selected for positive and negative triboelectric layers, respectively and conductive carbon/polylactic acid (C/PLA) filament was selected for both current collectors and wood/PLA is selected for both top and bottom supporting layers. The MMP-TENG is integrated with electronics to showcase its capability for remote monitoring in smart home settings to detect real-time fall detection and security monitoring. This research will pave the way for fabricating a smart floor for security monitoring and energy generation in a smart building.
... The innovations in materials and design have transformed wearable biosensors for realtime wound monitoring into a device that is functional, comfortable, and adaptable. More precisely, the advances made in the area of flexible/stretchable materials, microneedles, and 3D-printed devices have significantly improved the performance of such systems while improving user-friendliness [86,87]. ...
Wound healing is a complicated biological process that is important for restoring tissue integrity and function after injury. Infection, usually due to bacterial colonization, significantly complicates this process by hindering the course of healing and enhancing the chances of systemic complications. Recent advances in wearable biosensors have transformed wound care by making real-time monitoring of biomarkers such as pH, temperature, moisture, and infection-related metabolites like trimethylamine and uric acid. This review focuses on recent advances in biosensor technologies designed for wound management. Novel sensor architectures, such as flexible and stretchable electronics, colorimetric patches, and electrochemical platforms, enable the non-invasive detection of changes associated with wounds with high specificity and sensitivity. These are increasingly combined with AI and analytics based on smartphones that can enable timely and personalized interventions. Examples are the PETAL patch sensor that applies multiple sensing mechanisms for wide-ranging views on wound status and closed-loop systems that connect biosensors to therapeutic devices to automate infection control. Additionally, self-powered biosensors that tap into body heat or energy from the biofluids themselves avoid any external batteries and are thus more effective in field use or with limited resources. Internet of Things connectivity allows further support for remote sharing and monitoring of data, thus supporting telemedicine applications. Although wearable biosensors have developed relatively rapidly and their prospects continue to expand, regular clinical application is stalled by significant challenges such as regulatory, cost, patient compliance, and technical problems related to sensor accuracy, biofouling, and power, among others, that need to be addressed by innovative solutions. The goal of this review is to synthesize current trends, challenges, and future directions in wound healing and infection monitoring, with emphasis on the potential for wearable biosensors to improve patient outcomes and reduce healthcare burdens. These innovations are leading the way toward next-generation wound care by bridging advanced materials science, biotechnology, and digital health.
... Another gap concerns the ethical and regulatory framework for the use of AI in healthcare, particularly with regard to data privacy, liability, and equitable access. Research on the long-term effectiveness and safety of AI-based rehabilitation solutions is limited, and there are insufficient clinical trials to allow for the validation of results [77]. The integration of AI-AM systems into existing healthcare workflows has not been adequately addressed, leaving practical implementation strategies underdeveloped. ...
Featured Application
The application supports the design and production of new, personalized solutions in the field of rehabilitation and physiotherapy by introducing AI into 3D printing.
Abstract
The integration of artificial intelligence (AI) with additive manufacturing (AM) is driving breakthroughs in personalized rehabilitation and physical therapy solutions, enabling precise customization to individual patient needs. This article presents the current state of knowledge and perspectives of using personalized solutions for rehabilitation and physiotherapy thanks to the introduction of AI to AM. Advanced AI algorithms analyze patient-specific data such as body scans, movement patterns, and medical history to design customized assistive devices, orthoses, and prosthetics. This synergy enables the rapid prototyping and production of highly optimized solutions, improving comfort, functionality, and therapeutic outcomes. Machine learning (ML) models further streamline the process by anticipating biomechanical needs and adapting designs based on feedback, providing iterative refinement. Cutting-edge techniques leverage generative design and topology optimization to create lightweight yet durable structures that are ideally suited to the patient’s anatomy and rehabilitation goals .AI-based AM also facilitates the production of multi-material devices that combine flexibility, strength, and sensory capabilities, enabling improved monitoring and support during physical therapy. New perspectives include integrating smart sensors with printed devices, enabling real-time data collection and feedback loops for adaptive therapy. Additionally, these solutions are becoming increasingly accessible as AM technology lowers costs and improves, democratizing personalized healthcare. Future advances could lead to the widespread use of digital twins for the real-time simulation and customization of rehabilitation devices before production. AI-based virtual reality (VR) and augmented reality (AR) tools are also expected to combine with AM to provide immersive, patient-specific training environments along with physical aids. Collaborative platforms based on federated learning can enable healthcare providers and researchers to securely share AI insights, accelerating innovation. However, challenges such as regulatory approval, data security, and ensuring equity in access to these technologies must be addressed to fully realize their potential. One of the major gaps is the lack of large, diverse datasets to train AI models, which limits their ability to design solutions that span different demographics and conditions. Integration of AI–AM systems into personalized rehabilitation and physical therapy should focus on improving data collection and processing techniques.
... It is intriguing to think about being able to accurately control the mechanical, electrochemical, heating, and optical aspects of intricate three-dimensional components. It has already attracted the interest of experts from a variety of fields, including printed electronics, fluidics, the field of robotics, aviation and automobile industries, quantitative sciences, and more (Ali, 2022;Gonzalez, 2022;Izdebska-Podsiadły, 2022;Rao, 2022;Tan, 2022;Zhang, 2022). To enhance repeatability in scalable manufacturing, there is a growing interest in integrating feedback systems, such as machine learning-powered inspection systems. ...
This chapter explores the evolution and recent advancements of composite materials in the field of rapid prototyping, also known as additive manufacturing or 3D printing. Rapid prototyping has brought about a revolutionary transformation in the manufacturing and product development domains. Over time, composite materials used in rapid prototyping have witnessed significant advancements. Initially, the focus was primarily on single-material systems, such as thermoplastics or photopolymers. However, the growing demand for functional prototypes with improved mechanical, thermal, or electrical properties spurred the development of composite materials specifically tailored for 3D printing. These advancements in composite materials have significantly broadened the scope of functional prototyping, tooling, and even end-use part production. The ability to fabricate lightweight, high-strength components with intricate geometries has opened new avenues across industries such as aerospace, automotive, healthcare, and consumer goods. Continued research and development efforts in this field are expected to drive further improvements in composite materials, enabling the creation of even more versatile and high-performance 3D-printed products. Furthermore, the chapter discusses the challenges associated with composite material usage in rapid prototyping, examines recent innovations aimed at overcoming these challenges, and concludes by presenting prospects and potential directions for further research in this field.
... AIE materials, with their high luminescence, large Stokes shifts, excellent photophysical stability, and superior biocompatibility, offer several advantages over traditional fluorescent sensors and have seen rapid development [112,113]. Concurrently, 3DP technology can prepare devices with complex structures, achieve customized and miniaturized production of sensors, and enhance the potential of sensor manufacturing [114]. ...
Aggregation-induced emission (AIE) materials exhibit remarkable emission properties in the aggregated or solid states, offering numerous advantages such as high quantum yield, excellent photostability, and low background signals. These characteristics have led to their widespread application in optoelectronic devices, bio-detection markers, chemical sensing, and stimuli-responsive applications among others. In contrast to traditional manufacturing processes, 3D printing (3DP) enables rapid prototyping and large-scale customization with excellent flexibility in manufacturing techniques and material selection. The combination of AIE materials with 3DP can provide new strategies for fabricating materials and devices with complex structures. Therefore, 3DP is an ideal choice for processing AIE organic luminescent materials. However, 3DP of AIE materials is still in the early stages of development and is facing many challenges including limited printable AIE materials, poor printing functionalities and limited application range. This review aims to summarize the significant achievements in the field of 3DP of AIE materials. Firstly, different types of AIE materials for 3DP are studied, and the factors that affect the printing effect and the luminescence mechanism are discussed. Then, the latest advancements made in various application domains using 3D printed AIE materials are summarized. Finally, the existing challenges of this emerging field are discussed while the future prospects are prospected.
... In recent years, the AM field has evolved from rapid prototyping to mainstream manufacturing due to the capability of building complex three-dimensional freeform features with multiple materials [5][6][7][8]. Additive manufacturing, popularly called "3D Printing" is now being implemented in fields ranging from biomedical devices [9][10][11], semiconductor electronics [12,13], and energy devices [14][15][16] to the construction industry [17,18]. Several additive manufacturing technologies have mushroomed, each with their own unique process capabilities [19][20][21]. ...
Additive manufacturing (AM) has impacted the manufacturing of complex three-dimensional objects in multiple materials for a wide array of applications. However, additive manufacturing, as an upcoming field, lacks automated and specific design rules for different AM processes. Moreover, the selection of specific AM processes for different geometries requires expert knowledge, which is difficult to replicate. An automated and data-driven system is needed that can capture the AM expert knowledge base and apply it to 3D-printed parts to avoid manufacturability issues. This research aims to develop a data-driven system for AM process selection within the design for additive manufacturing (DFAM) framework for Industry 4.0. A Genetic and Evolutionary Feature Weighting technique was optimized using 3D CAD data as an input to identify the optimal AM technique based on several requirements and constraints. A two-stage model was developed wherein the stage 1 model displayed average accuracies of 70% and the stage 2 model showed higher average accuracies of up to 97.33% based on quantitative feature labeling and augmentation of the datasets. The steady-state genetic algorithm (SSGA) was determined to be the most effective algorithm after benchmarking against estimation of distribution algorithm (EDA) and particle swarm optimization (PSO) algorithms, respectively. The output of this system leads to the identification of optimal AM processes for manufacturing 3D objects. This paper presents an automated design for an additive manufacturing system that is accurate and can be extended to other 3D-printing processes.
... The allure of fabricating microfluidic devices with 3D printing [139,140] stems from its unique properties. (1) Complex 3D geometries can be easily fabricated with 3D printing [141]. ...
Vascular diseases are widespread, and sometimes such life-threatening medical disorders cause abnormal blood flow, blood particle damage, changes to flow dynamics, restricted blood flow, and other adverse effects. The study of vascular flow is crucial in clinical practice because it can shed light on the causes of stenosis, aneurysm, blood cancer, and many other such diseases, and guide the development of novel treatments and interventions. Microfluidics and computational fluid dynamics (CFDs) are two of the most promising new tools for investigating these phenomena. When compared to conventional experimental methods, microfluidics offers many benefits, including lower costs, smaller sample quantities, and increased control over fluid flow and parameters. In this paper, we address the strengths and weaknesses of computational and experimental approaches utilizing microfluidic devices to investigate the rheological properties of blood, the forces of action causing diseases related to cardiology, provide an overview of the models and methodologies of experiments, and the fabrication of devices utilized in these types of research, and portray the results achieved and their applications. We also discuss how these results can inform clinical practice and where future research should go. Overall, it provides insights into why a combination of both CFDs, and experimental methods can give even more detailed information on disease mechanisms recreated on a microfluidic platform, replicating the original biological system and aiding in developing the device or chip itself.
