Respiratory rate (RR) is an important physiological parameter whose abnormality has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to perform, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies.

https://iopscience.iop.org/article/10.1088/1361-6579/ab299e/pdf

Recent development of respiratory rate measurement technologies

Droplet-based microfluidics is a colloidal and interfacial system that has rapidly progressed in the past decade because of the advantages of low fabrication costs, small sample volumes, reduced analysis durations, high-throughput analysis with exceptional sensitivity, enhanced operational flexibility, and facile automation. This technology has emerged as a new tool for many recently used applications in molecular detection, imaging, drug delivery, diagnostics, cell biology and other fields. Herein, we review recent applications of droplet microfluidics proposed since 2013.

Recent Advances in Applications of Droplet Microfluidics

Human Physiology An Integrated Approach

Microfluidic synthesis control technology and its application in drug delivery, bioimaging, biosensing, environmental analysis and cell analysis

An intelligent digital microfluidic processor for biomedical detection is presented. This potential architecture solves lots of traditional development bottlenecks to implement the easy-to-control, easy-to-monitor, system automation and high accuracy for bioassay detection purposes. The proposed processor integrates the functions of microfluidic actuation, droplet location readback and high sensitivity measurement window to demonstrate a novel prototype for personalized medicine. Furthermore, the droplet location map and reaction behaviors are visible on a 2-dimentional (2D) graphical user-interface due to the micro electrode dot array (MEDA) architecture and capacitive sensing technology, and hence system automation is achievable. Fabricated in standard 0.35 μm CMOS process, this work integrates 900 microelectrodes with measurement window in 3.2 mm2, where the high sensitivity capacitive readout circuit occupies only 0.048 mm2. Measurement results show that microdroplet actuation and 2D location map are activated under 1KHz. In addition, the function of digital signal extraction, processing, as well as statistical analysis can be operated under 1 MHz respectively.

An Intelligent Digital Microfluidic Processor for Biomedical Detection

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.

High-level synthesis for micro-electrode-dot-array digital microfluidic biochips

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.

Droplet Size-Aware High-Level Synthesis for Micro-Electrode-Dot-Array Digital Microfluidic Biochips

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.

Error recovery in a micro-electrode-dot-array digital microfluidic biochip?

This paper presents a programmable lab-on-CMOS (LoCMOS) with micro-electrode cell array. Array structure is suitable for programmable like CMOS VLSIs. In order to improve the utilization, each micro-electrode cell is composed of actuation and sensing circuit. In addition, a CMOS-compatible extended drain MOSFET (EDMOS) is adopted under a 3V supply. This LoCMOS platform is composed of 1,800 microelectrodes with exploiting EDMOS to enable droplet actuations. Through its field programmability, the chip can successfully perform all microfluidic operations, droplet moving/cutting/mixing on a 2-dimenional microelectrode cell array. Implemented in 0.35um standard CMOS process, the LoCMOS platform demonstrates microfluidic functions and droplet detection. Measured results show successfully for actuation and real-time droplet location sensing.

Kelvin Yi-Tse Lai

Papers

An Intelligent Digital Microfluidic Processor for Biomedical Detection

High-level synthesis for micro-electrode-dot-array digital microfluidic biochips

Droplet Size-Aware High-Level Synthesis for Micro-Electrode-Dot-Array Digital Microfluidic Biochips

Error recovery in a micro-electrode-dot-array digital microfluidic biochip?

Design of a micro-electrode cell for programmable lab-on-CMOS platform