PEREIRA, Mário Wilson Paiva. Arquitetura de hardware para monitor de UTI segundo padrão IEEE 1451: uma prova de conceito. 2017. 125 f. Dissertação (Mestrado em Engenharia de Teleinformática)–Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2017. / Submitted by Renato Vasconcelos (ppgeti@ufc.br) on 2017-11-17T18:30:25Z No. of bitstreams: 1 2017_dis_mwppereira.pdf: 12636405 bytes, checksum: 9101596c0294db74704566e056987670 (MD5) / Rejected by Marlene Sousa (mmarlene@ufc.br), reason: Prezado Mário Wilson: Existe uma orientação para que normalizemos as dissertações e teses da UFC, em suas paginas pré-textuais e lista de referencias, pelas regras da ABNT. Por esse motivo, sugerimos consultar o modelo de template, para ajudar nesta tarefa, disponível em: http://www.biblioteca.ufc.br/educacao-de-usuarios/templates/ Vamos agora as correções sempre de acordo com o template: 1. 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Teds-easy - descricão automática de transducer electronic data sheet MARCONDES, A. Desenvolvimento de protótipo de gravador de TEDS e de etiqueta eletrônica TEDS PRIYA, M. et al. Embedded based wireless ICU monitoring system ROSSI, S. R.; RODRIGUES DA SILVA, A. C.; SANTOS FILHO, T. A. D. IEEE 1451.2- based sensor system with JAVA-TEDS software Tool TESTER, S. N. C. et al. An IEEE 1451 TEDS compiler and serial network compliance tester. Att. Marlene 3366-9620 on 2017-11-29T17:00:56Z (GMT) / Submitted by Renato Vasconcelos (ppgeti@ufc.br) on 2017-12-01T14:14:36Z No. of bitstreams: 1 2017_dis_mwppereira.pdf: 13128245 bytes, checksum: f6b50d91d6917b0407cfdedeba21bf03 (MD5) / Approved for entry into archive by Marlene Sousa (mmarlene@ufc.br) on 2017-12-01T16:28:19Z (GMT) No. of bitstreams: 1 2017_dis_mwppereira.pdf: 13128245 bytes, checksum: f6b50d91d6917b0407cfdedeba21bf03 (MD5) / Made available in DSpace on 2017-12-01T16:28:19Z (GMT). No. of bitstreams: 1 2017_dis_mwppereira.pdf: 13128245 bytes, checksum: f6b50d91d6917b0407cfdedeba21bf03 (MD5) Previous issue date: 2017-07-28 / This work presents the development of a hardware architecture for ICU monitors, combining design stages of embedded systems, biomedical instrumentation, intelligent sensors and the IEEE 1451 protocol. The method used defines operational requirements, system decomposition into modules, architecture definition and implementation using commercial development platforms. The entire process is based on national and international standards and protocols, seeking to design the system within the constraints of a product and validate the concept through printed circuit board prototypes. The proposed architecture establishes a network of intelligent biomedical sensors, called STIM, controlled by a central node, called NCAP. The use of this architecture provides modular, self-configuring, easy-to-maintain, plug and play sensors with standardized communication and data interface. The work also describes the process of creating electronic data sheets of the STIMs, called TEDS, which contain the operation characteristics of each smart sensor. / Este trabalho apresenta o desenvolvimento de uma arquitetura de hardware para moni- tores de UTI combinando etapas do projeto de sistemas embarcados, instrumentação biomédica, sensores inteligentes e o protocolo IEEE 1451. A metodologia empregada define requisitos operacionais, decomposição do sistema em módulos, definição da arquitetura e implementação utilizando plataformas de desenvolvimento comerciais. Todo o processo é baseado em normas e protocolos de órgãos nacionais e internacionais procurando projetar o sistema dentro das restrições de um produto e validar o conceito por meio de protótipos em placas de circuito impresso. A arquitetura proposta estabelece uma rede de sensores biomédicos inteligentes, denominados STIM, controlados por um elemento cental, denominado NCAP. A utilização desta arquitetura proporciona sensores modulares, autoconfiguráveis, de fácil manutenção, plug and play, com interface de comunicação e dados padronizados. O trabalho também descreve o processo de criação de folhas de dados eletrônicas dos STIMs, denominadas TEDS, que contêm as características de operação de cada sensor inteligente.

As diversas áreas da Engenharia, em parceria com a ciência médica, têm contribuído de forma eficaz para o avanço do conhecimento e dos resultados em aplicações práticas na vida do deficiente físico. De forma geral, pesquisas com este foco têm permitido o desenvolvimento de dispositivos e recursos com o objetivo de oferecer novamente a mobilidade e a liberdade perdidas com a deficiência. Este trabalho tem a finalidade de desenvolver um sistema que utiliza Eletromiografia de Superfície e Máquina de Vetores de Suporte para a caracterização de determinados movimentos de um braço humano, possibilitando, futuramente, a integração em sistemas de reabilitação. Primeiramente os sinais mioelétricos são obtidos nos músculos do braço de voluntários através de eletrodos de superfície ligados a um eletromiógrafo. O sinal é adquirido, utilizando como padrão um modelo virtual que demonstra ao voluntário os movimentos do segmento mão-braço que devem ser imitados. Esses movimentos são executados e seus sinais mioelétricos adquiridos. Posteriormente, esses sinais são processados e características são extraídas. Em seguida, são alocadas algumas de suas características (RMS, média, variância, desvio padrão, skewness e kurtosis) na entrada da Máquina de Vetores de Suporte, que apresenta, como saída, o reconhecimento, ou não, do movimento previamente executado pelo voluntário. No final do processo, observou-se que aumentando o número de canais elevou-se a taxa de acerto dos movimentos e, com a retirada de determinada característica, houve decréscimo na taxa de acerto do sistema. Nestes casos, os 9 movimentos distintos atingiram uma taxa de acerto média de 83,2%, para dois canais, e 91,3%, para oito canais, e, em ambos sistemas de canais, com as seis características. / A wide range of engineering scopes, along with the knowledge from the medical science, has efficiently been contributing to further knowledge and results for practical applications in the life of the physically challenged. In general, such researches have allowed the development of devices and resources aimed at giving back the mobility and freedom lost with the deficiency. This paper intends to develop a system that uses Surface Electromyography and Support-Vector Machines (SVM) for the characterization of specific movements of a human arm enabling the future integration in rehabilitation systems. At first, myoelectric signals are obtained in the arm muscles of volunteers by means of surface electrodes attached to an Electromyography. The signal is acquired using a virtual model as pattern demonstrating to the volunteer the hand-arm movements which are to be replicated by the subject. As these movements are done, its respective myoelectric signals are acquired. Later on, these signals are processed and their characteristics extracted. Some of these features (such as RMS, standard deviation, variance, mean, kurtosis, skewness) will then be inserted in as input data in the Support- Vector Machine, which shows as an output a valid or null recognition of the movement earlier executed by the volunteer. At the end of the process, it was observed that increasing the number of channels increased by hit rate movements and, with the removal of certain characteristic, there was a decrease in the hit rate of the system. In these cases, nine distinct movements reached an average accuracy of 83.2% for two channels, and 91.3% for eight channels, and in both systems of channels, with six features.

As diversas áreas da Engenharia, em parceria com a ciência médica, têm contribuído de forma eficaz para o avanço do conhecimento e dos resultados em aplicações práticas na vida do deficiente físico. De forma geral, pesquisas com este foco têm permitido o desenvolvimento de dispositivos e recursos com o objetivo de oferecer novamente a mobilidade e a liberdade perdidas com a deficiência. Este trabalho tem a finalidade de desenvolver um sistema que utiliza Eletromiografia de Superfície e Máquina de Vetores de Suporte para a caracterização de determinados movimentos de um braço humano, possibilitando, futuramente, a integração em sistemas de reabilitação. Primeiramente os sinais mioelétricos são obtidos nos músculos do braço de voluntários através de eletrodos de superfície ligados a um eletromiógrafo. O sinal é adquirido, utilizando como padrão um modelo virtual que demonstra ao voluntário os movimentos do segmento mão-braço que devem ser imitados. Esses movimentos são executados e seus sinais mioelétricos adquiridos. Posteriormente, esses sinais são processados e características são extraídas. Em seguida, são alocadas algumas de suas características (RMS, média, variância, desvio padrão, skewness e kurtosis) na entrada da Máquina de Vetores de Suporte, que apresenta, como saída, o reconhecimento, ou não, do movimento previamente executado pelo voluntário. No final do processo, observou-se que aumentando o número de canais elevou-se a taxa de acerto dos movimentos e, com a retirada de determinada característica, houve decréscimo na taxa de acerto do sistema. Nestes casos, os 9 movimentos distintos atingiram uma taxa de acerto média de 83,2%, para dois canais, e 91,3%, para oito canais, e, em ambos sistemas de canais, com as seis características. / A wide range of engineering scopes, along with the knowledge from the medical science, has efficiently been contributing to further knowledge and results for practical applications in the life of the physically challenged. In general, such researches have allowed the development of devices and resources aimed at giving back the mobility and freedom lost with the deficiency. This paper intends to develop a system that uses Surface Electromyography and Support-Vector Machines (SVM) for the characterization of specific movements of a human arm enabling the future integration in rehabilitation systems. At first, myoelectric signals are obtained in the arm muscles of volunteers by means of surface electrodes attached to an Electromyography. The signal is acquired using a virtual model as pattern demonstrating to the volunteer the hand-arm movements which are to be replicated by the subject. As these movements are done, its respective myoelectric signals are acquired. Later on, these signals are processed and their characteristics extracted. Some of these features (such as RMS, standard deviation, variance, mean, kurtosis, skewness) will then be inserted in as input data in the Support- Vector Machine, which shows as an output a valid or null recognition of the movement earlier executed by the volunteer. At the end of the process, it was observed that increasing the number of channels increased by hit rate movements and, with the removal of certain characteristic, there was a decrease in the hit rate of the system. In these cases, nine distinct movements reached an average accuracy of 83.2% for two channels, and 91.3% for eight channels, and in both systems of channels, with six features.

As diversas áreas da Engenharia, em parceria com a ciência médica, têm contribuído de forma eficaz para o avanço do conhecimento e dos resultados em aplicações práticas na vida do deficiente físico. De forma geral, pesquisas com este foco têm permitido o desenvolvimento de dispositivos e recursos com o objetivo de oferecer novamente a mobilidade e a liberdade perdidas com a deficiência. Este trabalho tem a finalidade de desenvolver um sistema que utiliza Eletromiografia de Superfície e Máquina de Vetores de Suporte para a caracterização de determinados movimentos de um braço humano, possibilitando, futuramente, a integração em sistemas de reabilitação. Primeiramente os sinais mioelétricos são obtidos nos músculos do braço de voluntários através de eletrodos de superfície ligados a um eletromiógrafo. O sinal é adquirido, utilizando como padrão um modelo virtual que demonstra ao voluntário os movimentos do segmento mão-braço que devem ser imitados. Esses movimentos são executados e seus sinais mioelétricos adquiridos. Posteriormente, esses sinais são processados e características são extraídas. Em seguida, são alocadas algumas de suas características (RMS, média, variância, desvio padrão, skewness e kurtosis) na entrada da Máquina de Vetores de Suporte, que apresenta, como saída, o reconhecimento, ou não, do movimento previamente executado pelo voluntário. No final do processo, observou-se que aumentando o número de canais elevou-se a taxa de acerto dos movimentos e, com a retirada de determinada característica, houve decréscimo na taxa de acerto do sistema. Nestes casos, os 9 movimentos distintos atingiram uma taxa de acerto média de 83,2%, para dois canais, e 91,3%, para oito canais, e, em ambos sistemas de canais, com as seis características. / A wide range of engineering scopes, along with the knowledge from the medical science, has efficiently been contributing to further knowledge and results for practical applications in the life of the physically challenged. In general, such researches have allowed the development of devices and resources aimed at giving back the mobility and freedom lost with the deficiency. This paper intends to develop a system that uses Surface Electromyography and Support-Vector Machines (SVM) for the characterization of specific movements of a human arm enabling the future integration in rehabilitation systems. At first, myoelectric signals are obtained in the arm muscles of volunteers by means of surface electrodes attached to an Electromyography. The signal is acquired using a virtual model as pattern demonstrating to the volunteer the hand-arm movements which are to be replicated by the subject. As these movements are done, its respective myoelectric signals are acquired. Later on, these signals are processed and their characteristics extracted. Some of these features (such as RMS, standard deviation, variance, mean, kurtosis, skewness) will then be inserted in as input data in the Support- Vector Machine, which shows as an output a valid or null recognition of the movement earlier executed by the volunteer. At the end of the process, it was observed that increasing the number of channels increased by hit rate movements and, with the removal of certain characteristic, there was a decrease in the hit rate of the system. In these cases, nine distinct movements reached an average accuracy of 83.2% for two channels, and 91.3% for eight channels, and in both systems of channels, with six features.

<p><a>Preeclampsia leads to increased risk of morbidity and mortality for both mother and fetus. Most previous studies have largely neglected mechanical compression of the left renal vein by the gravid uterus as a potential mechanism. In this study we first used a murine model to investigate the pathophysiology of left renal vein constriction. The results indicate that prolonged renal vein stenosis after 14 days can cause renal necrosis and an increase in blood pressure (BP) of roughly 30 mmHg. The second part of this study aimed to automate a diagnostic tool, known as the supine pressor test (SPT), to enable pregnant women to assess their preeclampsia development risk. A positive SPT has been previously defined as an increase of at least 20 mmHg in diastolic BP when switching between left lateral recumbent and supine positions. The results from this study established a baseline BP increase between the two body positions in non-pregnant female subjects and demonstrated the feasibility and utility of an automated SPT in pregnant women. Our results demonstrate that there is a baseline increase in BP of roughly 10-14 mmHg and that pregnant women can autonomously perform the SPT. Overall, this work in both rodents and humans suggests that 1) stenosis of the left renal vein in mice leads to elevation in BP and acute renal failure, 2) non-pregnant women experience a baseline increase in BP when they shift from left lateral recumbent to supine position, and 3) the SPT can be automated and used autonomously.</a></p> <br> <p> </p>

Autonomic control of the heart results in variations in the intervals between heart beats, known as heart rate variability. One of the defining components of autonomic control is the baroreflex, a negative feedback controller that balances heart rate and blood pressure. The baroreflex is under constant command from the branches of the autonomic nervous system. To better understand how the autonomic nervous system commands the baroreflex, a baroreflex reflexogenic animal protocol was carried out. Heart rate variability analysis and baroreflex sensitivity were used to quantify the neural control of the heart. This thesis reconfirmed the existence of sexually dimorphic properties in the baroreflex through the use of heart rate variability analysis and baroreflex sensitivity. It was discovered that there are many caveats to utilizing heart rate variability analysis, which have to be addressed both in the experimental protocol and the signal processing technique. Furthermore, it was suggested that the slope method for quantifying baroreflex sensitivity also has many caveats, and that other baroreflex sensitivity methods are likely more optimal for quantifying sustained activation of the baroreflex. By utilizing various heart rate variability signal processing algorithms to assess autonomic tone in Sprague-Dawley rats during rest and sustained electrical activation of the baroreflex, the null hypothesis was rejected.

Atherosclerosis accounts of 50% of the deaths in the western world leading to a plethora of diseases that include myocardial infarction, stroke, and peripheral artery disease. Currently available imaging modalities have inherent limitations, including ionizing radiation, lack of compositional information, and difficulty acquiring volumetric data that constrain their use in studying cardiovascular disease. Photoacoustic Tomography (PAT) has emerged as a promising modality that could address these limitations to improve the characterization and diagnosis of atherosclerosis-related conditions. Non-ionizing pulsed laser light is delivered to tissue leading to thermoelastic expansion followed by propagation of a pressure transient that can be detected with an ultrasound transducer. The magnitude of the ultrasonic PAT signal is proportional to the optical absorption at that location, revealing physiologically relevant compositional information of the tissue. The objective of this work is to therefore develop advanced volumetric imaging techniques to characterize disease progression in a murine model of atherosclerosis. The novelty of this work lies in the methodology and validation presented towards characterization of small animal vascular lipid accumulation with a high-resolution PAT system that utilizes the second near-infrared window (1100-1300nm). Additionally, we utilized <i>in situ </i>PAT to cross-sectionally assess lipid deposition and <i>in vivo</i>ultrasound to longitudinally assess hemodynamic, kinematic, and morphological changes during atherosclerosis progression. Together, this dissertation lays the foundation towards utilizing dual-modality PAT and ultrasound for various applications including understanding atherosclerosis pathophysiology, evaluation of novel therapeutics, and translation of clinically relevant techniques.

Stroke is amongst the leading causes of death and disability worldwide. Today diagnosis of Stroke is restricted to fixed imaging facilities which do not provide a rapid diagnostic. A portable device which could provide a non invasive assessment of stroke would therefore decrease the time of diagnosis and increase the chance of survival. Recent studies have confirmed that Implementing Electrical Bioimpedance in a portable device could provide a reliable means for Stroke diagnostic. However in order to be able to use the brain impedance as an indicator of Stroke, the invariance of brain impedance with time in healthy individuals should be studied first. Experimental Bioimpedance Spectroscopy (BIS) measurements from a healthy control group of 10 subjects have been used in this study to inspect the variation of brain impedance in the span of two weeks. The results of this study suggest that the cap which was used for brain impedance measurements together with  the available device have not been an optimal way of measuring the brain impedance and therefore have affected the data by causing artifacts for the results. With the artifacts available in the data acquired in this study it is not possible to make any statements about the variation of brain impedance and therefore a deeper analysis of collected data using descriptive analysis is required in order to be able to judge on the significance of the obtained errors. In the future a larger study group should be considered in order to increase the predictive power of the observations. / Stroke är bland de ledande orsakerna till död och funktionshinder i  hela världen.I dagsläget är diagnos av stroke begränsad till fasta bildenheter som inte möjliggör en snabb diagnos. En bärbar enhet som möjliggör en icke invasiv bedömning av sjukdomen skulle minska diagnos tiden och följaktligen öka chansen att överleva sjukdomen. Genomförda studier i ämnet har bekräftat att implementering av  Electrical Bioimpedance i en bärbar enhet kan räknas som ett effektivt sätt för Stroke diagnostik. För att kunna använda hjärnans impedans för Stroke diagnostik, bör först en studie av hjärnans impedans på friska individer utföras för att kunna visa att impedansen är oförändrad med tiden. Experimentell Bioimpedans Spektroskopi (BIS) mätningar från en frisk kontrollgrupp av 10 försökspersoner har utförts i denna studie för att inspektera variationen av hjärnans impedans under två veckor. Resultaten från denna studie tyder på att sättet av impedans mätningen i dagsläget är inte optimalt. Artefakter presenterad i resultatet gör det omöjligt för att kunna komma till ett beslut om hjärnans impedans variation . För fortsätta studier bör man överväga en större kontrollgrupp och även en analysering av data med hjälp av t-statistik som var inte inom ramen av denna studie.

<p>Circulating tumor cells (CTCs) have been proved to possess great value and potential in detection, diagnosis, and <a>prognosis</a> of non-haematologic cancers. Their unique characteristics in providing both phenotypic as well as genotypic information make them highly valuable in liquid biopsy assays. A<a>t the same time, though numerous studies and research have been done, identification and enumeration of CTCs is still technically challenging due to their rarity and heterogeneity</a>. The primary goal of the thesis is to develop a CTC detection and isolation system with ultra-high sensitivity and purity, while keeping it fast and scalable. We proposed a microfluidic system that integrates positive immunomagnetic capturing, high-throughput parallel flow and size filtration. In this thesis, two generations of the system have been developed to achieve the goal, and are approved to be able to effectively detect and isolate CTCs from hundreds of breast cancer blood samples in real clinical applications. </p> <p>The first-generation system is based on a sandwich-structured microfluidic chamber, which has a micro-aperture chip as the core to detect and isolate immunomagnetically targeted CTCs. The system achieves high detection yield (>95%) and purity (>99.9998% depletion of leukocytes) by streamlining the workflow and using unprocessed whole blood (without centrifuging), as well as utilizing an advanced surface coating approach to passivate the microchip surface. <a>We first demonstrate experiments for determining the optimal detection parameters. Then we characterize the system by isolating deterministically spiked 1, 10, and 100 single MCF-7 breast cancer cells into tubes of whole blood, and show that >95% of cells were captured. A detection yield of 100% from single cell spiking experiments (n = 6) demonstrates excellent detection capability and repeatability of the system. We finally demonstrate the use of the system for CTC detection in the context of a phase II clinical trial of early-stage triple-negative breast cancer (TNBC) patients. As a part of the trial, 182 blood samples were collected from 124 early-stage TNBC patients at high-risk of relapse. We detected CTCs in 36.3% of patients who had already completed chemotherapy and surgery for curative intent and were thus nominally expected to have very few to zero CTCs. </a>Moreover, increasing CTC count from the same patients shows good correlation with <a></a><a>their clinical course</a>. The ability to detect CTCs’ presence using this first-generation system illustrates its important clinical utility.</p> <p>The second-generation system applies a similar detection strategy but employs an upgraded microchip and device, as well as a further streamlined process flow to achieve an even higher detection efficiency, especially for capturing the target cells with low surface marker expression level. We first did modeling and simulation of the new system to find the optimal magnet configuration and verify the detection sensitivity improvement on the first-generation system. Then we characterized the new system by detecting spiked JEG-3 and JAR cells in both cell culture medium and human blood. The result demonstrates that the detection yield increased by ~20% using the second-generation system under the same experiment condition. Next, we applied the system to a phase I clinical trial for CTC detection from metastatic triple-negative breast cancer (mTNBC) patient blood samples. CTCs of mTNBC are known to with in the low marker expression phenotype, which requires ultra-high detection sensitivity. Our system captured CTCs from 48 out of 102 (47%) blood samples, the positivity rate agrees with the conclusions from other studies and presents the reliability to the system. Finally, we explored a novel 4-marker panel for CTC detection from mTNBC patient blood samples. We conducted paired comparisons using the 4-marker panel versus a single marker for detection. The 4-marker panel yielded more CTCs in 5/8 complete paired assessments, and less CTCs in 1/8. The association missed the significance level only slightly (p = 0.08), and the result strongly illustrates the potential for using the panel to cover the mTNBC cells’ heterogeneity for enhanced CTC detection. Furthermore, the presence of CTCs from blood samples correlates well with the patient’s disease progression.</p> <p>Finally, we demonstrated downstream analysis ability of the CTCs detected by the second-generation system. Captured CTCs can be readily released from our system without any loss or damage to a secondary microchip device to be further isolated as single cells, and picked up individually for downstream analysis like DNA/RNA sequencing or single-cell cultivation. Directions for future work is also discussed. We envision this versatile and efficient system to be highly beneficial in a broad range of clinical and research applications regarding CTCs.</p>

<p>  </p> <p>An optical technique that discriminates microbial organisms using an elastic light scatter (ELS) pattern, known as BActeria Rapid Detection using Optical Technology (BARDOT), has shown excellence in pathogen screening which effectively saves time and cost during the identification. Owing to the successful implementation of the light-scattering technique in microbiology, a series of studies on the light scatter pattern have been conducted to improve the technology. As an extended study of the multispectral application in BARDOT, a hyperspectral elastic light-scatter phenotyping instrument (HESPI) was developed to increase the ability to discriminate and detect foodborne pathogens. The newly designed instrument integrated a supercontinuum (SC) laser into the traditional BARDOT system to provide a broad spectrum of the light source. An acousto-optic tunable filter (AOTF) was utilized to select the wavelength of interest, allowing multiple spectral patterns in a single measurement. Owing to the filtering mechanism of AOTF, the wavelength of the laser was shifted rapidly so the overall acquisition time of 80 hyperspectral patterns was less than30 seconds. A pair of optical lenses were used to compensate for the beam spot movement caused by the wavelength-dependent separation angle at the exit of AOTF. To capture the transmitted scattering patterns, a complementary metal-oxide-semiconductor (CMOS) sensor was placed under the bacteria sample plate.</p> <p>For a comprehensive understanding of the ELS patterns, at first, the diverse nature of bacterial colony morphology was explored. Using the optical scatter model based on the scalar diffraction theory, the forward light-scatter patterns were simulated with respect to various colony shapes. The numerical predictions were then compared to the scattering patterns that were experimentally obtained from the colonies with various elevation profiles. The experimental verification proved a strong correlation between the colony morphology and the ELS pattern, as an excellent agreement between the simulation and the experiment observed. Second, the wavelength-dependent characteristics of the ELS patterns were investigated. Based on the theoretical and experimental interrogation, the wavelength of the incident laser beam affected the shape of ELS patterns by the overall size, the number of diffraction rings, and the gap distance between the rings. </p> <p>The performance of HESPI was validated by differentiating green leafy microflora using the hyperspectral ELS patterns. A group of bacteria that were poorly classified with the traditional single-wavelength method was selected to prove the improvement of the classification by the hyperspectral application. HESPI was utilized to measure the hyperspectral ELS patterns of their colonies, and for the classification, the descriptive features were extracted from the patterns at 70 selected wavelengths within the 473 – 709 nm region. A classification model was constructed for every wavelength, and the classification accuracy of the individual model ranged from 88.7% to 93.2%. The classification result also showed that colonies of varied species produced distinctive scatter features at a particular spectral band. When employing the entire wavelengths for the classification, the more number of wavelengths consequently led to an increase in the number of scatter-pattern features. This could cause the classifier's overfitting and negatively affect the classification. Therefore, the presented work incorporated various feature reduction and selection procedures to enhance the robustness and ultimately lessen the complexity of data collection. A classification model with feature reduction improved the overall classification rate to 95.9% after selecting meaningful predictors.</p>