Intelligent learning systems for hotspots detection in ISFET arrays

电化学传感器已经开始通过将最先进的实验室芯片技术应用于各种医疗应用，从而彻底改变医疗保健。离子敏感场效应晶体管（ISFET）具有显著的优势，因为它们与大规模互补金属氧化物半导体（CMOS）技术兼容，从而实现强大、低成本和可扩展的解决方案[1]。isfet是一种能够测量溶液中离子浓度的晶体管。这一特点可以被利用来实现特定DNA或RNA序列的DNA杂交。这在检测特定病毒方面具有重要应用，并可对临床应用产生巨大影响。ISFET阵列能够执行电化学成像，以快速帧速率提供大量丰富的数据，这为信号处理带来了一些机遇和挑战。例如，ISFET阵列用于在护理点快速准确地检测冠状病毒SARS- COV-2，从而产生低成本和便携式诊断方法[5]。在当前的大流行期间，这是至关重要的，并将对英国在追踪感染病毒的人的同时恢复标准活动产生巨大影响。在生物启发技术中心，这是通过使用由数千个传感器组成的阵列来实现的，这些传感器的数据在芯片上和芯片外进行处理。然而，ISFET技术的现状远未达到最佳状态。由于ISFET传感器的非理想性，与该方法相关的挑战出现了：例如，ISFET具有高噪声，并且经常在输出信号中引入漂移信号和捕获电荷，这些信号和期望的数据[6]不容易区分。这些通常是通过平均和其他技术来解决的，这些技术降低了样本的空间和时间分辨率。本研究的目的是开发方法来改善ISFET阵列的诊断和患者结果。这涉及芯片上的数据处理，以减少输出信号的非理想性和芯片外的算法创建，以重建信号的重要特征。这些智能系统将探索信号处理和机器学习的不同范例，以及数学优化和图形信号处理等工具。拟议的研究具有超越特定ISFET应用的影响潜力。我相信，在Pantelis Georgiou博士的指导下，他的研究重点与上述挑战相匹配，有可能在许多应用领域进行有影响力的研究。参考文献[1]Toumazou， Christofer，等，同时DNA扩增和检测使用ph传感半导体系统，自然方法10.7 (2013):641[1]N. Moser， T. S. Lande， C. Toumazou和P. Georgiou， isfet在CMOS和仪器仪表的新兴趋势：回顾，在IEEE传感器杂志，卷16，no。17, pp. 6496-6514, 2016年9月1日，doi: 10.1109/JSEN.2016.2585920.[3]Rodriguez-Manzano， J., Moser， N., Malpartida-Cardenas， K.等。利用基于核酸的芯片实验室诊断系统快速检测动员粘菌素耐药性。《科学通报》，2016,44(1)。https://doi.org/10.1038/s41598-020-64612-1[4] Malpartida-Cardenas K, Miscourides N, Rodriguez-Manzano J, Yu LS N, Moser N, Baum J, Georgiou P.基于CMOS实验室芯片平台的恶性疟原虫疟疾定量快速诊断和青蒿素耐药性检测。生物电子学报。2019;12;45:111678。doi: 10.1016 / j.bios.2019.111678。Epub 2019 9月7日。PMID: 31541787;PMCID: PMC7224984。[5]Jesus Rodriguez-Manzano、Kenny Malpartida-Cardenas、Nicolas Moser、Ivana Pennisi、Matthew Cavuto、Luca Miglietta、Ahmad Moniri、Rebecca Penn、Giovanni Satta、Paul Randell、Frances Davies、Frances Bolt、Wendy Barclay、Alison Holmes、Pante

Electrochemical sensors have already started to revolutionise healthcare by applying state-of-the-art Lab-on- Chip technology to a variety of medical applications. The ion-sensitive field-effect transistor (ISFET) offers significant advantages due to their compatibility with large-scale Complementary Metal-Oxide-Semiconductor (CMOS) technology, allowing for a robust, low cost and scalable solution [1]. ISFETs are transistors that are capable of measuring the ion concentration in a solution [2]. This feature can be exploited to achieve DNA hybridisation of a specific DNA or RNA sequence. This has major applications in the detection of specific viruses and can have a huge impact in clinical applications [3] [4]. ISFET arrays are able to perform electrochemical imaging, providing a large amount of rich data at a fast frame rate which raises several opportunities and challenges for signal processing.For example, ISFET arrays are used for rapid and accurate detection of the Coronavirus SARS- COV-2 at the point of care, resulting in a low-cost and portable diagnosis method [5]. This is essential during the current pandemic and would have a huge impact to allow the UK to return to standard activities while tracing people that contracted the virus. At the the Centre for Bio-inspired Technology, this is achieved by employing an array of thousand of sensors whose data is processed on-chip and off-chip.However, the state of art of the ISFET technology is far from being optimal. There are challenges associated with this method that arise as a consequence of the non-idealities of the ISFET sensors: for instance, ISFETS are highly noisy and often introduce drift signals and trapped charge in the output signal that are not easily distinguishable from the desired data [6]. These are normally tackled by averaging and other techniques that reduce the spatial and temporal resolution of the samples.The aim of the proposed research is to develop methods to improve diagnostic and patient outcomes of the ISFET arrays. This involves on-chip data processing to reduce the output signal non-idealities and off-chip creation of algorithms to reconstruct the significant features of the signal. These intelligent systems will explore different paradigms in signal processing and machine learning, alongside tools such as mathematical optimisation and graph signal processing.The proposed research has the potential to be impactful beyond the specific ISFET application. I believe that under the supervision of Dr. Pantelis Georgiou, whose research focus matches the aforementioned challenges, there is a potential to conduct impactful research across many applications.References[1] Toumazou, Christofer, et al., Simultaneous DNA amplification and detection using a pH-sensing semicon- ductor system, Nature methods 10.7 (2013): 641[2] N. Moser, T. S. Lande, C. Toumazou and P. Georgiou, ISFETs in CMOS and Emergent Trends in Instrumentation: A Review, in IEEE Sensors Journal, vol. 16, no. 17, pp. 6496-6514, Sept.1, 2016, doi: 10.1109/JSEN.2016.2585920.[3] Rodriguez-Manzano, J., Moser, N., Malpartida-Cardenas, K. et al. Rapid Detection of Mobilized Colistin Resistance using a Nucleic Acid Based Lab-on-a-Chip Diagnostic System. Sci Rep 10, 8448 (2020). https://doi.org/10.1038/s41598-020-64612-1[4] Malpartida-Cardenas K, Miscourides N, Rodriguez-Manzano J, Yu LS, Moser N, Baum J, Georgiou P., Quantitative and rapid Plasmodium falciparum malaria diagnosis and artemisinin-resistance de- tection using a CMOS Lab-on-Chip platform. Biosens Bioelectron. 2019 Dec 1;145:111678. doi: 10.1016/j.bios.2019.111678. Epub 2019 Sep 7. PMID: 31541787; PMCID: PMC7224984.[5] Jesus Rodriguez-Manzano, Kenny Malpartida-Cardenas, Nicolas Moser, Ivana Pennisi, Matthew Cavuto, Luca Miglietta, Ahmad Moniri, Rebecca Penn, Giovanni Satta, Paul Randell, Frances Davies, Frances Bolt, Wendy Barclay, Alison Holmes, Pante