Matti Kaisti

Bio: Matti Kaisti is an academic researcher from University of Turku. The author has contributed to research in topics: Computer science & ISFET. The author has an hindex of 13, co-authored 35 publications receiving 655 citations. Previous affiliations of Matti Kaisti include Imperial College London.

Clinical assessment of a non-invasive wearable MEMS pressure sensor array for monitoring of arterial pulse waveform, heart rate and detection of atrial fibrillation.

Abstract: There is an unmet clinical need for a low cost and easy to use wearable devices for continuous cardiovascular health monitoring. A flexible and wearable wristband, based on microelectromechanical sensor (MEMS) elements array was developed to support this need. The performance of the device in cardiovascular monitoring was investigated by (i) comparing the arterial pressure waveform recordings to the gold standard, invasive catheter recording (n = 18), (ii) analyzing the ability to detect irregularities of the rhythm (n = 7), and (iii) measuring the heartrate monitoring accuracy (n = 31). Arterial waveforms carry important physiological information and the comparison study revealed that the recordings made with the wearable device and with the gold standard device resulted in almost identical (r = 0.9–0.99) pulse waveforms. The device can measure the heart rhythm and possible irregularities in it. A clustering analysis demonstrates a perfect classification accuracy between atrial fibrillation (AF) and sinus rhythm. The heartrate monitoring study showed near perfect beat-to-beat accuracy (sensitivity = 99.1%, precision = 100%) on healthy subjects. In contrast, beat-to-beat detection from coronary artery disease patients was challenging, but the averaged heartrate was extracted successfully (95% CI: −1.2 to 1.1 bpm). In conclusion, the results indicate that the device could be useful in remote monitoring of cardiovascular diseases and personalized medicine.

Agile methods for embedded systems development - a literature review and a mapping study

Abstract: There is a wide area of applications that use embedded systems, and the number of such systems keeps growing. The required functionality and complexity of embedded systems are also constantly increasing, and development of such products is becoming increasingly harder. This requires new thinking on the product development processes, and one such emerging philosophy is the agile methods. These methods were created by the software engineering community where they are commonly used. Since then, they have been adopted in embedded systems development; however, whether they can improve the embedded systems product development processes remains an open question. This study aims to bring forth what is known about agile methods in embedded systems development and to find out if agile practices are suitable in this domain and what evidence is there to support the findings. We conducted a literature review and a mapping study to answer these questions. The scope of this study is not only limited to embedded software development, but also to embedded hardware and integrated circuits. We have found that agile methods can be used in the embedded domain, but the methods and practices need to be adapted to suit the more constrained field of embedded product development. Furthermore, the field of embedded product development has wide diversity of products with different needs and domain-specific problems so that no single method is applicable, but rather many methods and practices are needed for different situations.

Hand-Held Transistor Based Electrical and Multiplexed Chemical Sensing System

Abstract: We describe a hand-held sensing system using a transistor based multiplexed platform and a detector that couples the electrochemical information wirelessly to a smartphone. The custom disposable platform exploits the ion-sensitive FET (ISFET) technology. Via simple surface modifications the design allows a broad range of analytes to be tested with low cost. We compared our read-out device to a commercial potentiometer using K+ as an example species analyte. The developed sensing system has a slightly better limit of detection and is notably less susceptible to external noise which is commonly observed with potentiometers. The designed platform is fabricated using standard electronic processes with gold surface and we used commercial discrete transistors as the transducing element. It can be mass produced with high yield and low cost. To circumvent the drift that typically occurs with modified solid state electrodes we incorporated a transducing layer between the electric conductor (gold pad) and the ionic...

An Ion-Sensitive Floating Gate FET Model: Operating Principles and Electrofluidic Gating

Abstract: We present a model that can be used to compute the charging and potential at any point of the electrochemical system comprising the ion-sensitive floating gate FET (ISFGFET) exposed to an electrolyte solution. In contrast to ion-sensitive FETs, the sensor has an additional control input gate. The model predicts the possibility for electrofluidic gating when the control gate (CG) is used in conjunction with a reference electrode (RE). Electrofluidic gating is the field-effect control over the electric double layer. We consider the applicability of electrofluidic gating in realizable devices and simulate the relationships between oxide properties and electrolyte solution to varying potentials of the CG and the RE. The oxide/electrolyte solution model is merged to the SPICE model of the transistor to create a unified model that can be used to simulate the transfer characteristics of the sensor in absolute terms to change input and electrolyte solution conditions. We simulate the sensor transfer characteristics with common Al2O3 surface to change the pH of the electrolyte solution and compare them to measurements. The results clarify the operation of ISFGFET and its applicability in electrofluidic gating.

Antibody tests for identification of current and past infection with SARS‐CoV‐2

Abstract: Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify current infection, rule out infection, identify people in need of care escalation, or to test for past infection and immune response. Serology tests to detect the presence of antibodies to SARS-CoV-2 aim to identify previous SARS-CoV-2 infection, and may help to confirm the presence of current infection. Objectives To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS-CoV-2 infection, and the accuracy of antibody tests for use in seroprevalence surveys. Search methods We undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 27 April 2020. Selection criteria We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in people suspected of current or previous SARS-CoV-2 infection, or where tests were used to screen for infection. We also included studies of people either known to have, or not to have SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR) and clinical diagnostic criteria). Data collection and analysis We assessed possible bias and applicability of the studies using the QUADAS-2 tool. We extracted 2x2 contingency table data and present sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data using random-effects logistic regression where appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs). Main results We included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n = 38), Europe (n = 15), and the USA and China (n = 1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n = 28) of the studies included were only available as preprints. We had concerns about risk of bias and applicability. Common issues were use of multi-group designs (n = 29), inclusion of only COVID-19 cases (n = 19), lack of blinding of the index test (n = 49) and reference standard (n = 29), differential verification (n = 22), and the lack of clarity about participant numbers, characteristics and study exclusions (n = 47). Most studies (n = 44) only included people hospitalised due to suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n = 33) defined COVID-19 cases based on RT-PCR results alone, ignoring the potential for false-negative RT-PCR results. We observed evidence of selective publication of study findings through omission of the identity of tests (n = 5). We observed substantial heterogeneity in sensitivities of IgA, IgM and IgG antibodies, or combinations thereof, for results aggregated across different time periods post-symptom onset (range 0% to 100% for all target antibodies). We thus based the main results of the review on the 38 studies that stratified results by time since symptom onset. The numbers of individuals contributing data within each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond three weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). There are insufficient studies to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range expected by chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity between assay type, but methodological concerns and sparse data prevent comparisons between test brands. Authors' conclusions The sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative, or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after the onset of symptoms. However, the duration of antibody rises is currently unknown, and we found very little data beyond 35 days post-symptom onset. We are therefore uncertain about the utility of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalised patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution and reporting of studies of the accuracy of COVID-19 tests requires considerable improvement. Studies must report data on sensitivity disaggregated by time since onset of symptoms. COVID-19-positive cases who are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are available in the public domain to prevent selective reporting. This is a fast-moving field and we plan ongoing updates of this living systematic review.

Steric effects in the dynamics of electrolytes at large applied voltages: I. Double-layer charging

Abstract: The classical Poisson-Boltzmann (PB) theory of electrolytes assumes a dilute solution of point charges with mean-field electrostatic forces. Even for very dilute solutions, however, it predicts absurdly large ion concentrations (exceeding close packing) for surface potentials of only a few tenths of a volt, which are often exceeded, e.g. in microfluidic pumps and electrochemical sensors. Since the 1950s, several modifications of the PB equation have been proposed to account for the finite size of ions in equilibrium, but in this two-part series, we consider steric effects on diffuse charge dynamics (in the absence of electro-osmotic flow). In this first part, we review the literature and analyze two simple models for the charging of a thin double layer, which must form a condensed layer of close-packed ions near the surface at high voltage. A surprising prediction is that the differential capacitance typically varies non-monotonically with the applied voltage, and thus so does the response time of an electrolytic system. In PB theory, the capacitance blows up exponentially with voltage, but steric effects actually cause it to decrease above a threshold voltage where ions become crowded near the surface. Other nonlinear effects in PB theory are also strongly suppressed by steric effects: The net salt adsorption by the double layers in response to the applied voltage is greatly reduced, and so is the tangential "surface conduction" in the diffuse layer, to the point that it can often be neglected compared to bulk conduction (small Dukhin number).

Electrically-Transduced Chemical Sensors Based on Two-Dimensional Nanomaterials

Abstract: Electrically–transduced sensors, with their simplicity and compatibility with standard electronic technologies, produce signals that can be efficiently acquired, processed, stored, and analyzed. Two dimensional (2D) nanomaterials, including graphene, phosphorene (BP), transition metal dichalcogenides (TMDCs), and others, have proven to be attractive for the fabrication of high–performance electrically-transduced chemical sensors due to their remarkable electronic and physical properties originating from their 2D structure. This review highlights the advances in electrically-transduced chemical sensing that rely on 2D materials. The structural components of such sensors are described, and the underlying operating principles for different types of architectures are discussed. The structural features, electronic properties, and surface chemistry of 2D nanostructures that dictate their sensing performance are reviewed. Key advances in the application of 2D materials, from both a historical and analytical pers...