Pub Date : 2021-09-08DOI: 10.18287/JBPE21.07.040302
Luís Fernandes, H. Silva, Inês H Martins, S. Carvalho, I. Carneiro, R. Henrique, V. Tuchin, Luís Manuel Couto Oliveira
In this paper we present three studies that demonstrate the applicability of spectroscopy methods and optical clearing treatments in pathology identification and monitoring. In the first study, by obtaining the absorption spectra of human healthy and pathological (adenocarcinoma) colorectal mucosa tissues, it was possible to identify a higher content of a pigment in the diseased tissues. This study also shows that machine learning methods can be used to reach the same differentiated results in vivo through diffuse reflectance spectroscopy. In the second study, the combination of collimated transmittance spectroscopy with optical clearing treatments allowed to obtain the diffusion coefficients of glucose in healthy and pathological colorectal mucosa as: D glucose =5.8x 10 – 7 cm 2 /s and D glucose =4.4x 10 – 7 cm 2 /s, respectively. This study also demonstrated that the diseased tissues contains about 5% more mobile water than the healthy tissues. The third study was performed to evaluate the protein dissociation mechanism of optical clearing. By treating both healthy and pathological colorectal mucosa tissues with 93%-glycerol, a protein dissociation rate of about 3 times higher was obtained for the pathological mucosa. All the discriminating parameters that result from these studies can be obtained in the in vivo situation through diffuse reflectance spectroscopy and further studies to evaluate their values in different stages of cancer progression are of great importance to develop disease monitoring protocols.
在本文中，我们提出了三项研究，证明了光谱方法和光学清除处理在病理学鉴定和监测中的适用性。在第一项研究中，通过获得人类健康和病理性（腺癌）结肠直肠粘膜组织的吸收光谱，可以确定病变组织中较高含量的色素。这项研究还表明，机器学习方法可以通过漫反射光谱在体内达到相同的差异化结果。在第二项研究中，将准直透射光谱与光学清除处理相结合，可以获得葡萄糖在健康和病理性结肠直肠粘膜中的扩散系数，分别为：D葡萄糖=5.8x 10–7 cm 2/s和D葡萄糖=4.4x 10–7cm 2/s。这项研究还表明，患病组织比健康组织多含约5%的流动水。第三项研究评估了光学清除剂的蛋白质解离机制。通过用93%的甘油治疗健康和病理性结肠直肠粘膜组织，病理性粘膜的蛋白质解离率提高了约3倍。这些研究得出的所有判别参数都可以通过漫反射光谱在体内情况下获得，进一步研究评估其在癌症进展不同阶段的价值对制定疾病监测方案具有重要意义。
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Pub Date : 2021-09-07DOI: 10.18287/10.18287/JBPE21.07.040201
Vandana Joshi, Nirali R. Nanavati
Neurological disorders are diseases that affect the brain and the central autonomic nervous systems. These disorders take a huge toll on an individual's health and general well-being. After cardiovascular diseases, neurological disorders are the main cause of death. These disorders include epilepsy, Alzheimer ’ s disease, dementia, cerebrovascular diseases including stroke, migraine, Parkinso n ’s disease and numerous other disorders. This manuscript presents a state-of-the-art consolidated review of research on the diagnosis of the three most common neurological disorders using electroencephalogram (EEG) signals with machine learning techniques. The disorders discussed in this manuscript are the more prevalent disorders like epilepsy, Attention-deficit/hyperactivity disorder (ADHD), and Alzheimer’s disease. This manuscript helps in understanding the details about EEG signal processing for diagnosis and analysis of neurological disorders along with a discussion of the datasets, limitations, results and research scope of the various techniques.
{"title":"A Review of EEG Signal Analysis for Diagnosis of Neurological Disorders using Machine Learning","authors":"Vandana Joshi, Nirali R. Nanavati","doi":"10.18287/10.18287/JBPE21.07.040201","DOIUrl":"https://doi.org/10.18287/10.18287/JBPE21.07.040201","url":null,"abstract":"Neurological disorders are diseases that affect the brain and the central autonomic nervous systems. These disorders take a huge toll on an individual's health and general well-being. After cardiovascular diseases, neurological disorders are the main cause of death. These disorders include epilepsy, Alzheimer ’ s disease, dementia, cerebrovascular diseases including stroke, migraine, Parkinso n ’s disease and numerous other disorders. This manuscript presents a state-of-the-art consolidated review of research on the diagnosis of the three most common neurological disorders using electroencephalogram (EEG) signals with machine learning techniques. The disorders discussed in this manuscript are the more prevalent disorders like epilepsy, Attention-deficit/hyperactivity disorder (ADHD), and Alzheimer’s disease. This manuscript helps in understanding the details about EEG signal processing for diagnosis and analysis of neurological disorders along with a discussion of the datasets, limitations, results and research scope of the various techniques.","PeriodicalId":52398,"journal":{"name":"Journal of Biomedical Photonics and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48807425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-28DOI: 10.18287/JBPE21.07.040501
V. Doubrovski, S. V. Markov, S. O. Torbin, E. P. Karpocheva
A comparative analysis of the sedimentation rates of free erythrocytes and their associates – aggregates and agglutinates was carried out. The influence of a standing ultrasonic (US) wave on the blood sedimentation process was investigated. The problem was dictated not only by a purely scientific interest in the sedimentation of micro–objects in a liquid medium, but from a practical point of view also – the development of an instrumental acousto–optical method for human blood group typing. Registration of the blood sedimentation process was carried out by means of digital video recording with subsequent computer processing of the photographic images obtained. The magnitude of blood sedimentation rate was experimentally determined for various samples and conditions: 1) blood solutions with / without ultrasound exposure for different time dosages; 2) a mixture of blood samples with hemagglutinating substances (Tsoliklon) without / with ultrasonic action both for a positive agglutination reaction (formation of agglutinates) and negative ones (absence of agglutinates). Two approaches were used to process the photographic images: 1) in the case of agglutinates sedimentation the discrete counting and analysis of agglutinate parameters were used; 2) in other cases, the blood sedimentation rate was determined by the movement of the "supernatant – sediment" (plasma solution – erythrocytes mass) boundary. For the experimental conditions accepted the blood sedimentation rates were compared and, correspondently, the influence of the ultrasonic standing wave upon the process under study was estimated. It was shown that in the presence of ultrasound the sedimentation rate of RBC agglutinates (positive agglutination reaction) is more than an order higher than the sedimentation rate of free erythrocytes and their aggregates (negative agglutination reaction). Such a great difference in the sedimentation rates of agglutinates in comparison with free erythrocytes and their aggregates makes it possible to obtain a high degree of resolution of acousto–optical method for instrumental blood typing, and, hence, high reliability in blood group determination.
{"title":"The Sedimentation Rate of Free Erythrocytes and Their Associates, the Influence of a Standing Ultrasonic Wave","authors":"V. Doubrovski, S. V. Markov, S. O. Torbin, E. P. Karpocheva","doi":"10.18287/JBPE21.07.040501","DOIUrl":"https://doi.org/10.18287/JBPE21.07.040501","url":null,"abstract":"A comparative analysis of the sedimentation rates of free erythrocytes and their associates – aggregates and agglutinates was carried out. The influence of a standing ultrasonic (US) wave on the blood sedimentation process was investigated. The problem was dictated not only by a purely scientific interest in the sedimentation of micro–objects in a liquid medium, but from a practical point of view also – the development of an instrumental acousto–optical method for human blood group typing. Registration of the blood sedimentation process was carried out by means of digital video recording with subsequent computer processing of the photographic images obtained. The magnitude of blood sedimentation rate was experimentally determined for various samples and conditions: 1) blood solutions with / without ultrasound exposure for different time dosages; 2) a mixture of blood samples with hemagglutinating substances (Tsoliklon) without / with ultrasonic action both for a positive agglutination reaction (formation of agglutinates) and negative ones (absence of agglutinates). Two approaches were used to process the photographic images: 1) in the case of agglutinates sedimentation the discrete counting and analysis of agglutinate parameters were used; 2) in other cases, the blood sedimentation rate was determined by the movement of the \"supernatant – sediment\" (plasma solution – erythrocytes mass) boundary. For the experimental conditions accepted the blood sedimentation rates were compared and, correspondently, the influence of the ultrasonic standing wave upon the process under study was estimated. It was shown that in the presence of ultrasound the sedimentation rate of RBC agglutinates (positive agglutination reaction) is more than an order higher than the sedimentation rate of free erythrocytes and their aggregates (negative agglutination reaction). Such a great difference in the sedimentation rates of agglutinates in comparison with free erythrocytes and their aggregates makes it possible to obtain a high degree of resolution of acousto–optical method for instrumental blood typing, and, hence, high reliability in blood group determination.","PeriodicalId":52398,"journal":{"name":"Journal of Biomedical Photonics and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48909618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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