Device-on-Chip Application in Biomedical Engineering

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensor and Bioelectronic Devices".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 11712

Special Issue Editors

Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794-5280, USA
Interests: medical device; biosensor; bio-optics; device on a chip; wearable device; ultrasound
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biosensors have the potential to deliver point-of-care diagnostics and remote biological sensing that can match or even surpass the conventional technologies. With the development of nanotechnology, sensors and the measurement electronics can be miniaturized while maintaining the high level of sophistication. The challenge lies in the integration of sensors with their control and data acquisition along with achieving high-performance data analysis, which can create a device-on-chip solution for real-time application. Microcontrollers and FPGAs are frequently employed in those applications. This Special Issue is soliciting original research in this area with the following areas of focus:

  • Miniaturized sensor technology for device-on-a-chip
  • Novel integration platforms for sensor control and data acquisition using embedded electronics such as microcontroller and FPGA
  • Real-time sensor data processing using FPGA technology
  • Integration of deep learning technology with sensors as a device-on-chip solution
  • High-performance data analysis and high data throughput of image sensors

Dr. Wei Lin
Prof. Dr. Ajeet Kaushik
Guest Editors

If you want to learn more information or need any advice, you can contact the Special Issue Editor Jessica Zhou via <[email protected]> directly.

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • FPGA
  • microcontroller
  • sensor
  • biosensor
  • high-performance computing
  • high data throughput
  • sensor control
  • device-on-chip

Published Papers (4 papers)

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Research

11 pages, 2674 KiB  
Article
All-in-One Optofluidic Chip for Molecular Biosensing Assays
by Tyler Sano, Han Zhang, Ravipa Losakul and Holger Schmidt
Biosensors 2022, 12(7), 501; https://doi.org/10.3390/bios12070501 - 09 Jul 2022
Cited by 9 | Viewed by 2050
Abstract
Integrated biosensor platforms have become subjects of high interest for consolidated assay preparation and analysis to reduce sample-to-answer response times. By compactly combining as many biosensor processes and functions as possible into a single lab-on-chip device, all-in-one point-of-care devices can aid in the [...] Read more.
Integrated biosensor platforms have become subjects of high interest for consolidated assay preparation and analysis to reduce sample-to-answer response times. By compactly combining as many biosensor processes and functions as possible into a single lab-on-chip device, all-in-one point-of-care devices can aid in the accessibility and speed of deployment due to their compact size and portability. Biomarker assay preparation and sensing are functionalities that are often carried out on separate devices, thus increasing opportunity of contamination, loss of sample volume, and other forms of error. Here, we demonstrate a complete lab-on-chip system combining sample preparation, on-chip optofluidic dye laser, and optical detection. We first show the integration of an on-chip distributed feedback dye laser for alignment-free optical excitation of particles moving through a fluidic channel. This capability is demonstrated by using Rhodamine 6G as the gain medium to excite single fluorescent microspheres at 575 nm. Next, we present an optofluidic PDMS platform combining a microvalve network (automaton) for sample preparation of nanoliter volumes, on-chip distributed feedback dye laser for target excitation, and optical detection. We conduct concurrent capture and fluorescence tagging of Zika virus nucleic acid on magnetic beads in 30 min. Target-carrying beads are then optically excited using the on-chip laser as they flow through an analysis channel, followed by highly specific fluorescence detection. This demonstration of a complete all-in-one biosensor is a tangible step in the development of a rapid, point-of-care device that can assist in limiting the severity of future outbreaks. Full article
(This article belongs to the Special Issue Device-on-Chip Application in Biomedical Engineering)
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11 pages, 2510 KiB  
Article
Energy-Efficient, On-Demand Activation of Biosensor Arrays for Long-Term Continuous Health Monitoring
by Jonathan Lundquist, Benjamin Horstmann, Dmitry Pestov, Umit Ozgur, Vitaliy Avrutin and Erdem Topsakal
Biosensors 2022, 12(5), 358; https://doi.org/10.3390/bios12050358 - 21 May 2022
Cited by 3 | Viewed by 2267
Abstract
Wearable biosensors for continuous health monitoring, particularly those used for glucose detection, have a limited operational lifetime due to biodegradation and fouling. As a result, patients must change sensors frequently, increasing cost and patient discomfort. Arrays of multiple sensors, where the individual devices [...] Read more.
Wearable biosensors for continuous health monitoring, particularly those used for glucose detection, have a limited operational lifetime due to biodegradation and fouling. As a result, patients must change sensors frequently, increasing cost and patient discomfort. Arrays of multiple sensors, where the individual devices can be activated on demand, increase overall operational longevity, thereby reducing cost and improving patient outcomes. This work demonstrates the feasibility of this approach via decomposition of combustible nitrocellulose membranes that protect the individual sensors from exposure to bioanalytes using a current pulse. Metal contacts, connected by graphene-loaded PEDOT:PSS polymer on the surface of the membrane, deliver the required energy to decompose the membrane. Nitrocellulose membranes with a thickness of less than 1 µm consistently transfer on to polydimethylsiloxane (PDMS) wells. An electrical energy as low as 68 mJ has been shown to suffice for membrane decomposition. Full article
(This article belongs to the Special Issue Device-on-Chip Application in Biomedical Engineering)
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20 pages, 5110 KiB  
Article
FPGA Correlator for Applications in Embedded Smart Devices
by Christopher H. Moore and Wei Lin
Biosensors 2022, 12(4), 236; https://doi.org/10.3390/bios12040236 - 12 Apr 2022
Cited by 2 | Viewed by 2882
Abstract
Correlation has a variety of applications that require signal processing. However, it is computationally intensive, and software correlators require high-performance processors for real-time data analysis. This is a challenge for embedded devices because of the limitation of computing resources. Hardware correlators that use [...] Read more.
Correlation has a variety of applications that require signal processing. However, it is computationally intensive, and software correlators require high-performance processors for real-time data analysis. This is a challenge for embedded devices because of the limitation of computing resources. Hardware correlators that use Field Programmable Gate Array (FPGA) technology can significantly boost computational power and bridge the gap between the need for high-performance computing and the limited processing power available in embedded devices. This paper presents a detailed FPGA-based correlator design at the register level along with the open-source Very High-Speed Integrated Circuit Hardware Description Language (VHDL) code. It includes base modules for linear and multi-tau correlators of varying sizes. Every module implements a simple and unified data interface for easy integration with standard and publicly available FPGA modules. Eighty-lag linear and multi-tau correlators were built for validation of the design. Three input data sets—constant signal, pulse signal, and sine signal—were used to test the accuracy of the correlators. The results from the FPGA correlators were compared against the outputs of equivalent software correlators and validated with the corresponding theoretical values. The FPGA correlators returned results identical to those from the software references for all tested data sets and were proven to be equivalent to their software counterparts. Their computation speed is at least 85,000 times faster than the software correlators running on a Xilinx MicroBlaze processor. The FPGA correlator can be easily implemented, especially on System on a Chip (SoC) integrated circuits that have processor cores and FPGA fabric. It is the ideal component for device-on-chip solutions in biosensing. Full article
(This article belongs to the Special Issue Device-on-Chip Application in Biomedical Engineering)
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11 pages, 3171 KiB  
Article
Pressure-Free Assembling of Poly(methyl methacrylate) Microdevices via Microwave-Assisted Solvent Bonding and Its Biomedical Applications
by Kieu The Loan Trinh, Woo Ri Chae and Nae Yoon Lee
Biosensors 2021, 11(12), 526; https://doi.org/10.3390/bios11120526 - 20 Dec 2021
Cited by 6 | Viewed by 3002
Abstract
Poly(methyl methacrylate) (PMMA) has become an appealing material for manufacturing microfluidic chips, particularly for biomedical applications, because of its transparency and biocompatibility, making the development of an appropriate bonding strategy critical. In our research, we used acetic acid as a solvent to create [...] Read more.
Poly(methyl methacrylate) (PMMA) has become an appealing material for manufacturing microfluidic chips, particularly for biomedical applications, because of its transparency and biocompatibility, making the development of an appropriate bonding strategy critical. In our research, we used acetic acid as a solvent to create a pressure-free assembly of PMMA microdevices. The acetic acid applied between the PMMA slabs was activated by microwave using a household microwave oven to tightly merge the substrates without external pressure such as clamps. The bonding performance was tested and a superior bond strength of 14.95 ± 0.77 MPa was achieved when 70% acetic acid was used. Over a long period, the assembled PMMA device with microchannels did not show any leakage. PMMA microdevices were also built as a serpentine 2D passive micromixer and cell culture platform to demonstrate their applicability. The results demonstrated that the bonding scheme allows for the easy assembly of PMMAs with a low risk of clogging and is highly biocompatible. This method provides for a simple but robust assembly of PMMA microdevices in a short time without requiring expensive instruments. Full article
(This article belongs to the Special Issue Device-on-Chip Application in Biomedical Engineering)
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