A Brief Review of OPT101 Sensor Application in Near-Infrared Spectroscopy Instrumentation for Intensive Care Unit Clinics

The optoelectronic sensor OPT101 have merits in advanced optoelectronic response characteristics at wavelength range for medical near-infrared spectroscopy and small-size chip design with build-in trans-impedance amplifier. Our lab is devoted to developing a series of portable near-infrared spectroscopy (NIRS) devices embedded with OPT101 for applications in intensive care unit clinics, based on NIRS principle. Here we review the characteristics and advantages of OPT101 relative to clinical NIRS instrumentation, and the most recent achievements, including early-diagnosis and therapeutic effect evaluation of thrombus, noninvasive monitoring of patients\u27 shock severity, and fatigue evaluation. The future prospect on OPT101 improvements in noninvasive clinical applications is also discussed

Towards a portable platform integrated with multi-spectral non-contact probes for delineating normal and breast cancer tissue based on near-infrared spectroscopy

Currently, the confirmation of diagnosis of breast cancer is made by microscopic examination of an ultra-thin slice of a needle biopsy specimen. This slice is conventionally formalin-fixed and stained with hematoxylin-eosin and visually examined under a light microscope. This process is labor-intensive and requires highly skilled doctors (pathologists). In this paper, we report a novel tool based on near-infrared spectroscopy (Spectral-IRDx) which is a portable, non-contact, and cost-effective system and could provide a rapid and accurate diagnosis of cancer. The Spectral-IRDx tool performs absorption spectroscopy at near-infrared (NIR) wavelengths of 850 nm, 935 nm, and 1060 nm. We measure normalized detected voltage (Vdn) with the tool in 10 deparaffinized breast biopsy tissue samples, 5 of which were cancer (C) and 5 were normal (N) tissues. The difference in Vdn at 935 nm and 1060 nm between cancer and normal tissues is statistically significant with p-values of 0.0038 and 0.0022 respectively. Absorption contrast factor (N/C) of 1.303, 1.551, and 1.45 are observed for 850 nm, 935 nm, and 1060 nm respectively. The volume fraction contrast (N/C) of lipids and collagens are reported as 1.28 and 1.10 respectively. Higher absorption contrast factor (N/C) and volume fraction contrast (N/C) signifies higher concentration of lipids in normal tissues as compared to cancerous tissues, a basis for delineation. These preliminary results support the envisioned concept for non-invasive and non-carcinogenic NIR-based breast cancer diagnostic platform, which will be tested using a larger number of samples

Desenvolvimento e avaliação de um sistema de espectroscopia funcional de infravermelho próximo para detecção de movimento intencional com base na atividade cerebral

Dissertação (Mestrado em Engenharia Biomédica)–Programa de pós-graduação em Engenharia Biomédica, Universidade de Brasília, Brasília, 2020.Pessoas que possuem doenças do neurônio motor têm dificuldades de interagir e de se comunicar com o ambiente ao seu redor. Umas das doenças do neurônio motor mais comuns é a Esclerose Lateral Amiotrófica (ELA), em que os acometidos pela doença perdem a capacidade de se comunicar verbalmente. Em um estágio avançado da ELA, chamado de Síndrome do Encarceramento Total, do inglês Complete Locked-In State (CLIS), os pacientes perdem o controle de todas as resposta musculares voluntárias, porém possuem um estado de consciência normal. Uma das alternativas para pessoas que possuem essas síndromes é a utilização de uma Interface Cérebro Computador (ICC) como mecanismo de comunicação. ICCs são sistemas eletrônicos que tentam discernir padrões em sinais de atividades encefalográficas para utilizá-los como auxílio à seres humanos com mobilidades reduzidas. Dentre as técnicas utilizadas para captar esses sinais encefalográficos, a Espectroscopia Funcional de Infravermelho Próximo, do inglês functional Near Infrared Spectroscopy (fNIRS), tem sido objeto crescente de estudo nos últimos anos. A fNIRS é uma técnica não-invasiva, que utiliza uma abordagem óptica para adquirir tais sinais. Seu principio baseia-se em mensurar as taxas de oxigenação e desoxigenação do fluxo sanguíneo no córtex cerebral. Ela situa-se em um meio termo entre as técnicas de Eletroencefalografia (EEG) e Imagem por Ressonância Magnética Funcional, do inglês functional Magnetic Resonance Imaging (fMRI), porém com maior flexibilidade e menor risco à saúde de quem a utiliza. Nesse contexto, a pesquisa propôs a desenvolver um sistema eletrônico de aquisição multicanal de sinais de fNIRS, e avaliá-lo em um cenário de classificação de sinais reais de humanos, buscando diferenciar movimentos intencionais de não-intencionais. A metodologia consistiu em projetar a instrumentação de aquisição, implementar um modelo de classificação SVM, e coletar sinais do córtex cerebral de humanos, com base em um protocolo experimental aprovado por um Comitê de Ética. O processo de classificação foi realizado utilizando um modelo preditivo do tipo SVM, com kernel gaussiano. Para estimar melhor as métricas de desempenho do modelo, foi utilizada a técnica de validação cruzada K-Fold, com k=5. Ao todo foram avaliados três cenários distintos de classificação. Participaram das coletas, no total, cinco voluntários. Cada sessão de coleta teve duração de 6 minutos, onde cada participante foi instruído a passar metade do tempo em repouso e a outra metade realizando movimentos sequenciais com as mãos. O primeiro consistiu em adquirir sinais com apenas um canal, formado por uma topologia simples de uma fonte de luz com um fotodetector. Os sinais foram coletados em duas sessões em um mesmo dia, com condições de iluminação controladas. Cada sessão utilizou uma fonte de emissão distinta uma da outra. A acurácia média obtida ficou superior a 90% para os dois participantes. O segundo experimento avaliou um cenário de classificação com a aquisição de 10 canais simultaneamente, adquiridos com 3 voluntários, em um mesmo dia cada. Os 10 canais foram gerados utilizando duas fontes de emissão em conjunto com cinco fotodetectores. A acurácia média para esse cenário foi de 98%, indicando que o modelo conseguiu discernir bem a presença da ausência de movimento. O último experimento teve como objetivo avaliar o desempenho de classificação com sinais coletados em dias distintos para um mesmo participante, simulando condições de iluminação distintas. Para tal, foram repetidas as coletas com os últimos 3 voluntários, dois dias após às primeiras sessões. O modelo foi treinado com os sinais da primeira sessão, e a inferência foi feita com os sinais da segunda sessão. Nesse cenário, as métricas de desempenho obtidas revelaram que não foi possível discernir com boa acurácia as classes avaliadas. No geral, os resultados obtidos com os experimentos foram similares aos de trabalhos da literatura levantada, validando o sistema de aquisição implementado.People who suffers from motor neuron diseases have difficulties to interact and communicate with the environment around them. One of the most common motor neuron diseases is Amyotrophic Lateral Sclerosis (ALS), in which those affected by the disease lose the ability to communicate verbally. In an advanced stage of ALS, called Complete Locked-In State (CLIS), patients lose control of all voluntary muscle responses, but still have a normal conscious state. One of the possible alternatives for people who have these syndromes is a Brain Computer Interface (BCI), for use as a communication mechanism. BCIs are electronic systems that try to discern patterns in signals of encephalographic activities, using these patterns as an aid to humans with reduced mobility. Among the techniques used to capture these encephalographic signals, the functional Near Infrared Spectroscopy (fNIRS) has been an object of increasing study in recent years. fNIRS is a non-invasive technique that uses an optical approach to acquire such signals. Its principle is based on measuring the oxygenation and deoxygenation rates of blood flow in the cerebral cortex. It situates between the techniques of Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI), but with greater flexibility and less risk to the health of those who use it. In this context, the research proposed to develop an electronic system for multichannel acquisition of fNIRS signals, and to evaluate it in a scenario of classification of real human signals, seeking to differentiate intentional from unintentional movements. The methodology consisted of designing the acquisition instrumentation, implementing an SVM classification model, and collecting signals from the human cerebral cortex, based on an experimental protocol approved by a Human Ethics Committee. The classification process was performed using a predictive model of the SVM type, with Gaussian kernel. To better estimate the model's performance metrics, the K-Fold cross-validation technique was used, with k=5. Three different classification scenarios were evaluated, and five volunteers participated of the experiments. Each acquisition session lasted 6 minutes, and each participant was instructed to spend half the time at rest and the other half to perform sequential hand movements. The first consisted of acquiring signals with only one channel, formed by a simple topology of one light source with one photodetector. The signals were collected in two sessions on the same day, with controlled lighting conditions. Each session used a different emission source. The average accuracy obtained was greater than 90% for the two participants. The second experiment evaluated a classification scenario with the acquisition simultaneously of 10 channels, acquired with 3 volunteers, on the same day each. The 10 channels were generated using two emission sources together with five photodetectors. The average accuracy for this scenario was 98%, indicating that the model was able to discern well the presence of the absence of movement. The last experiment aimed to evaluate the classification performance with signals collected on different days for the same participant, simulating different lighting conditions. For this, collections were repeated with the last 3 volunteers, two days after the first sessions. The model was trained with the signals from the first session, and the inference was made with the signals from the second session. In this scenario, the performance metrics obtained revealed that it was not possible to discern the evaluated classes, with the adopted methodology. In general, the results obtained with the experiments were similar to those of studies in the literature, validating the implemented acquisition system

Métodos y recursos en la instrumentación científica alternativa orientada a la enseñanza en ciencias e ingeniería

As a result of the development of low cost and high-performance scientific instruments, it has been developed some experimental set ups, measurement methods and tools (numerical and graphic) in order to obtain trustable results. Some of the assays were proof of concept that, in spite of been qualitative, have been rescued taking into account their value in the understanding of physical and chemical phenomena useful for teaching Science and Engineering. Some cases, developed by using two of the resources normally standard in personal computers such as the microphone and web cam, for sound-based tests and visible light as well as Raman spectrometry, are presented. The techniques have been developed in support of the development of Scientific Alternative Instruments (ICA in Spanish).Como resultado del desarrollo de instrumentos científicos de bajo costo y buen desempeño, se han realizado algunos arreglos experimentales, aplicación de métodos de medición y herramientas (tanto gráficas como formales) para obtener resultados confiables. Muchos de los ensayos fueron pruebas de concepto que, a pesar de no ser cuantitativos, han sido rescatados por su valor en el entendimiento de algunos fenómenos físicos y químicos, útiles en la enseñanza de ciencias e ingeniería. Se analizan algunos métodos usando dos de los recursos disponibles normalmente en una computadora personal: el micrófono y la cámara web; el primero para pruebas basadas en sonido y la segunda para espectrometría tanto de radiación visible como de fotones Raman. Las técnicas descritas han sido examinadas como apoyo al desarrollo de instrumentos científicos alternativos (ICA)

Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples

Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU.mu L-1. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV- 2 pandemic.This research was funded by grants number COV20-00080 and COV20-00173 of the 2020 Emergency Call for Research Projects about the SARS-CoV-2 virus and the COVID-19 disease of the Institute of Health 'Carlos III', Spanish Ministry of Science and Innovation, and by grant number EQC2019-006240-P of the 2019 Call for Acquisition of Scientific Equipment, FEDER Program, Spanish Ministry of Science and Innovation. This work has been supported by the European Commission through the JRC HUMAINT project. ABR was supported by grant number RTI2018-094465-J funded by the Spanish National Agency of Research. The authors would like to gratefully acknowledge the assistance of the members of the EOD-CBRN Group of the Spanish National Police, whose identities cannot be disclosed, and who are represented here by JMNG. Authors thank continuous support from their institutions

Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples

Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU·μL−1. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV-2 pandemic.Instituto de Salud Carlos III COV20-00080 and COV20-00173Ministerio de Ciencia e Innovación EQC2019-006240-PComisión Europea JRC HUMAINT projec

Comparison of Dual Beam Dispersive and FTNIR Spectroscopy for Lactate Detection

Near Infrared (800–2500 nm) spectroscopy has been extensively used in biomedical applications, as it offers rapid, in vivo, bed-side monitoring of important haemodynamic parameters, which is especially important in critical care settings. However, the choice of NIR spectrometer needs to be investigated for biomedical applications, as both the dual beam dispersive spectrophotomer and the FTNIR spectrometer have their own advantages and disadvantages. In this study, predictive analysis of lactate concentrations in whole blood were undertaken using multivariate techniques on spectra obtained from the two spectrometer types simultaneously and results were compared. Results showed significant improvement in predicting analyte concentration when analysis was performed on full range spectral data. This is in comparison to analysis of limited spectral regions or lactate signature peaks, which yielded poorer prediction models. Furthermore, for the same region, FTNIR showed 10% better predictive capability than the dual beam dispersive NIR spectrometer

A Newcomer\u27s Guide to Functional Near Infrared Spectroscopy Experiments

This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs

A Brief Review of OPT101 Sensor Application in Near-Infrared Spectroscopy Instrumentation for Intensive Care Unit Clinics

The optoelectronic sensor OPT101 have merits in advanced optoelectronic response characteristics at wavelength range for medical near-infrared spectroscopy and small-size chip design with build-in trans-impedance amplifier. Our lab is devoted to developing a series of portable near-infrared spectroscopy (NIRS) devices embedded with OPT101 for applications in intensive care unit clinics, based on NIRS principle. Here we review the characteristics and advantages of OPT101 relative to clinical NIRS instrumentation, and the most recent achievements, including early-diagnosis and therapeutic effect evaluation of thrombus, noninvasive monitoring of patients\u27 shock severity, and fatigue evaluation. The future prospect on OPT101 improvements in noninvasive clinical applications is also discussed