The Experts below are selected from a list of 7083 Experts worldwide ranked by ideXlab platform
Chenyi Lee - One of the best experts on this subject based on the ideXlab platform.
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droplet size aware and error correcting sample preparation using micro electrode dot array digital microfluidic biochips
IEEE Transactions on Biomedical Circuits and Systems, 2017Co-Authors: Kelvin Yitse Lai, Chenyi LeeAbstract:Sample preparation in digital microfluidics refers to the generation of droplets with target concentrations for on-chip biochemical applications. In recent years, digital microfluidic biochips (DMFBs) have been adopted as a platform for sample preparation. However, there remain two major problems associated with sample preparation on a conventional DMFB. First, only a (1:1) mixing/splitting model can be used, leading to an increase in the number of fluidic operations required for sample preparation. Second, only a limited number of sensors can be integrated on a conventional DMFB; as a result, the latency for error detection during sample preparation is significant. To overcome these drawbacks, we adopt a next generation DMFB platform, referred to as micro-electrode-dot-array (Meda), for sample preparation. We propose the first sample-preparation method that exploits the Meda-specific advantages of fine-grained control of droplet sizes and real-time droplet sensing. Experimental demonstration using a fabricated Meda biochip and simulation results highlight the effectiveness of the proposed sample-preparation method.
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droplet size aware high level synthesis for micro electrode dot array digital microfluidic biochips
IEEE Transactions on Biomedical Circuits and Systems, 2017Co-Authors: Kelvin Yitse Lai, Krishnendu Chakrabarty, Chenyi LeeAbstract:A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. In recent years, DMFBs based on a microelectrode-dot-array (Meda) architecture have been demonstrated. However, due to the inherent differences between today's DMFBs and Meda, existing synthesis solutions for biochemistry mapping cannot be utilized for Meda biochips. We present the first synthesis approach that can be used for Meda biochips. We first present a general analytical model for droplet velocity and validate it experimentally using a fabricated Meda biochip. We then present the proposed synthesis method targeting reservoir placement, operation scheduling, module placement, routing of droplets of various sizes, and diagonal movement of droplets in a two-dimensional array. Simulation results using benchmarks and experimental results using a fabricated Meda biochip demonstrate the effectiveness of the proposed synthesis technique.
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high level synthesis for micro electrode dot array digital microfluidic biochips
Design Automation Conference, 2016Co-Authors: Kelvin Yitse Lai, Krishnendu Chakrabarty, Chenyi LeeAbstract:A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. However, today's DMFBs suffer from several limitations: (i) constraints on droplet size and the inability to vary droplet volume in a fine-grained manner; (ii) the lack of integrated sensors for real-time detection; (iii) the need for special fabrication processes and reliability/yield concerns. To overcome the above problems, DMFBs based on a micro-electrode-dot-array (Meda) architecture have recently been demonstrated. However, due to the inherent differences between today's DMFBs and Meda, existing synthesis solutions cannot be utilized for Meda-based biochips. We present the first biochip synthesis approach that can be used for Meda. The proposed synthesis method targets operation scheduling, module placement, routing of droplets of various sizes, and diagonal movement of droplets in a two-dimensional array. Simulation results using benchmarks and experimental results using a fabricated Meda biochip demonstrate the effectiveness of the proposed co-optimization technique.
Kelvin Yitse Lai - One of the best experts on this subject based on the ideXlab platform.
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droplet size aware and error correcting sample preparation using micro electrode dot array digital microfluidic biochips
IEEE Transactions on Biomedical Circuits and Systems, 2017Co-Authors: Kelvin Yitse Lai, Chenyi LeeAbstract:Sample preparation in digital microfluidics refers to the generation of droplets with target concentrations for on-chip biochemical applications. In recent years, digital microfluidic biochips (DMFBs) have been adopted as a platform for sample preparation. However, there remain two major problems associated with sample preparation on a conventional DMFB. First, only a (1:1) mixing/splitting model can be used, leading to an increase in the number of fluidic operations required for sample preparation. Second, only a limited number of sensors can be integrated on a conventional DMFB; as a result, the latency for error detection during sample preparation is significant. To overcome these drawbacks, we adopt a next generation DMFB platform, referred to as micro-electrode-dot-array (Meda), for sample preparation. We propose the first sample-preparation method that exploits the Meda-specific advantages of fine-grained control of droplet sizes and real-time droplet sensing. Experimental demonstration using a fabricated Meda biochip and simulation results highlight the effectiveness of the proposed sample-preparation method.
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droplet size aware high level synthesis for micro electrode dot array digital microfluidic biochips
IEEE Transactions on Biomedical Circuits and Systems, 2017Co-Authors: Kelvin Yitse Lai, Krishnendu Chakrabarty, Chenyi LeeAbstract:A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. In recent years, DMFBs based on a microelectrode-dot-array (Meda) architecture have been demonstrated. However, due to the inherent differences between today's DMFBs and Meda, existing synthesis solutions for biochemistry mapping cannot be utilized for Meda biochips. We present the first synthesis approach that can be used for Meda biochips. We first present a general analytical model for droplet velocity and validate it experimentally using a fabricated Meda biochip. We then present the proposed synthesis method targeting reservoir placement, operation scheduling, module placement, routing of droplets of various sizes, and diagonal movement of droplets in a two-dimensional array. Simulation results using benchmarks and experimental results using a fabricated Meda biochip demonstrate the effectiveness of the proposed synthesis technique.
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high level synthesis for micro electrode dot array digital microfluidic biochips
Design Automation Conference, 2016Co-Authors: Kelvin Yitse Lai, Krishnendu Chakrabarty, Chenyi LeeAbstract:A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. However, today's DMFBs suffer from several limitations: (i) constraints on droplet size and the inability to vary droplet volume in a fine-grained manner; (ii) the lack of integrated sensors for real-time detection; (iii) the need for special fabrication processes and reliability/yield concerns. To overcome the above problems, DMFBs based on a micro-electrode-dot-array (Meda) architecture have recently been demonstrated. However, due to the inherent differences between today's DMFBs and Meda, existing synthesis solutions cannot be utilized for Meda-based biochips. We present the first biochip synthesis approach that can be used for Meda. The proposed synthesis method targets operation scheduling, module placement, routing of droplets of various sizes, and diagonal movement of droplets in a two-dimensional array. Simulation results using benchmarks and experimental results using a fabricated Meda biochip demonstrate the effectiveness of the proposed co-optimization technique.
Tsung-yi Ho - One of the best experts on this subject based on the ideXlab platform.
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Micro-Electrode-Dot-Array Digital Microfluidic Biochips: Technology, Design Automation, and Test Techniques
IEEE Transactions on Biomedical Circuits and Systems, 2019Co-Authors: Zhanwei Zhong, Zipeng Li, Tsung-yi HoAbstract:Digital microfluidic biochips (DMFBs) are being increasingly used for DNA sequencing, point-of-care clinical diagnostics, and immunoassays. DMFBs based on a micro-electrode-dot-array (Meda) architecture have recently been proposed, and fundamental droplet manipulations, e.g., droplet mixing and splitting, have also been experimentally demonstrated on Meda biochips. There can be thousands of microelectrodes on a single Meda biochip, and the fine-grained control of nanoliter volumes of biochemical samples and reagents is also enabled by this technology. Meda biochips offer the benefits of real-time sensitivity, lower cost, easy system integration with CMOS modules, and full automation. This review paper first describes recent design tools for high-level synthesis and optimization of map bioassay protocols on a Meda biochip. It then presents recent advances in scheduling of fluidic operations, placement of fluidic modules, droplet-size-aware routing, adaptive error recovery, sample preparation, and various testing techniques. With the help of these tools, biochip users can concentrate on the development of nanoscale bioassays, leaving details of chip optimization and implementation to software tools.
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efficient and adaptive error recovery in a micro electrode dot array digital microfluidic biochip
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018Co-Authors: Zipeng Li, Po-hsien Yu, John Mccrone, Miroslav Pajic, Tsung-yi HoAbstract:A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. In recent years, DMFBs based on a micro-electrode-dot-array (Meda) architecture have been proposed. Meda biochips can provide advantages of better capability of droplet manipulation and real-time sensing ability. However, errors are likely to occur due to defects, chip degradation, and the lack of precision inherent in biochemical experiments. Therefore, an efficient error-recovery strategy is essential to ensure the correctness of assays executed on Meda biochips. By exploiting Meda-specific advances in droplet sensing, we present a novel error-recovery technique to dynamically reconfigure the biochip using real-time data provided by on-chip sensors. Local recovery strategies based on probabilistic-timed-automata are presented for various types of errors. An online synthesis technique and a control flow are also proposed to connect local-recovery procedures with global error recovery for the complete bioassay. Moreover, an integer linear programming-based method is also proposed to select the optimal local-recovery time for each operation. Laboratory experiments using a fabricated Meda chip are used to characterize the outcomes of key droplet operations. The PRISM model checker and three benchmarks are used for an extensive set of simulations. Our results highlight the effectiveness of the proposed error-recovery strategy.
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error recovery in a micro electrode dot array digital microfluidic biochip
International Conference on Computer Aided Design, 2016Co-Authors: Zipeng Li, Po-hsien Yu, Miroslav Pajic, Tsung-yi HoAbstract:A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. However, today's DMFBs suffer from several limitations: (i) constraints on droplet size and the inability to vary droplet volume in a fine-grained manner; (ii) the lack of integrated sensors for real-time detection; (iii) the need for special fabrication processes and the associated reliability/yield concerns. To overcome the above problems, DMFBs based on a micro-electrode-dot-array (Meda) architecture have been proposed recently, and droplet manipulation on these devices has been experimentally demonstrated. Errors are likely to occur due to defects, chip degradation, and the lack of precision inherent in biochemical experiments. Therefore, an efficient error-recovery strategy is essential to ensure the correctness of assays executed on Meda biochips. By exploiting Meda-specific advances in droplet sensing, we present a novel error-recovery technique to dynamically reconfigure the biochip using real-time data provided by on-chip sensors. Local recovery strategies based on probabilistic-timed-automata are presented for various types of errors. A control flow is also proposed to connect local recovery procedures with global error recovery for the complete bioassay. Laboratory experiments using a fabricated Meda chip are used to characterize the outcomes of key droplet operations. The PRISM model checker and three analytical chemistry benchmarks are used for an extensive set of simulations. Our results highlight the effectiveness of the proposed error-recovery strategy.
Praveen Thokala - One of the best experts on this subject based on the ideXlab platform.
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multiple criteria decision analysis for health care decision making an introduction report 1 of the ispor mcda emerging good practices task force
Value in Health, 2016Co-Authors: Praveen Thokala, Zoltán Kaló, Nancy Devlin, Kevin Marsh, Rob Baltussen, Meindert Boysen, Thomas Longrenn, Filip Mussen, Stuart Peacock, John B WatkinsAbstract:Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting, objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making and a set of techniques, known under the collective heading multiple criteria decision analysis (MCDA), are useful for this purpose. MCDA methods are widely used in other sectors, and recently there has been an increase in health care applications. In 2014, ISPOR established an MCDA Emerging Good Practices Task Force. It was charged with establishing a common definition for MCDA in health care decision making and developing good practice guidelines for conducting MCDA to aid health care decision making. This initial ISPOR MCDA task force report provides an introduction to MCDA - it defines MCDA; provides examples of its use in different kinds of decision making in health care (including benefit risk analysis, health technology assessment, resource allocation, portfolio decision analysis, shared patient clinician decision making and prioritizing patients’ access to services); provides an overview of the principal methods of MCDA; and describes the key steps involved. Upon reviewing this report, readers should have a solid overview of MCDA methods and their potential for supporting health care decision making.
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multiple criteria decision analysis for health technology assessment
Value in Health, 2012Co-Authors: Praveen Thokala, Alejandra DuenasAbstract:Abstract Objectives Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. Methods This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. Results A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. Conclusions There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process.
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multiple criteria decision analysis for health technology assessment
Value in Health, 2012Co-Authors: Praveen Thokala, Alejandra DuenasAbstract:Abstract Objectives Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. Methods This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. Results A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. Conclusions There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process.
Alejandra Duenas - One of the best experts on this subject based on the ideXlab platform.
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multiple criteria decision analysis for health technology assessment
Value in Health, 2012Co-Authors: Praveen Thokala, Alejandra DuenasAbstract:Abstract Objectives Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. Methods This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. Results A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. Conclusions There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process.
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multiple criteria decision analysis for health technology assessment
Value in Health, 2012Co-Authors: Praveen Thokala, Alejandra DuenasAbstract:Abstract Objectives Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. Methods This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. Results A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. Conclusions There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process.