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Wang K, Li G, Cheng L, Wang S, Lin L. High-precision spectra captured by a spectral camera and suppression of their nonlinearity. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2024; 41:1082-1088. [PMID: 38856420 DOI: 10.1364/josaa.521937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 04/22/2024] [Indexed: 06/11/2024]
Abstract
The high sensitivity of photoplethysmography (PPG) spectral signals provides conditions for extracting dynamic spectra carrying nonlinear information. By the idea of spatial conversion precision, this paper uses a spectral camera to collect highly sensitive spectral data of 24 wavelengths and proposes a method for extracting dynamic spectra of three different optical path lengths and their joint modeling. In the experiment, the models of the red blood cells and white blood cells established by the joint spectra achieved good results, with the correlation coefficients above 0.77. This study has great significance for achieving high-precision noninvasive quantitative analysis of human blood components.
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Giulbudagian M, Battisini B, Bäumler W, Blass Rico AM, Bocca B, Brungs C, Famele M, Foerster M, Gutsche B, Houben V, Hauri U, Karpienko K, Karst U, Katz LM, Kluger N, Serup J, Schreiver I, Schubert S, van der Bent SAS, Wolf C, Luch A, Laux P. Lessons learned in a decade: Medical-toxicological view of tattooing. J Eur Acad Dermatol Venereol 2024. [PMID: 38709160 DOI: 10.1111/jdv.20072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/15/2024] [Indexed: 05/07/2024]
Abstract
Tattooing has been part of the human culture for thousands of years, yet only in the past decades has it entered the mainstream of the society. With the rise in popularity, tattoos also gained attention among researchers, with the aim to better understand the health risks posed by their application. 'A medical-toxicological view of tattooing'-a work published in The Lancet almost a decade ago, resulted from the international collaboration of various experts in the field. Since then, much understanding has been achieved regarding adverse effects, treatment of complications, as well as their regulation for improving public health. Yet major knowledge gaps remain. This review article results from the Second International Conference on Tattoo Safety hosted by the German Federal Institute for Risk Assessment (BfR) and provides a glimpse from the medical-toxicological perspective, regulatory strategies and advances in the analysis of tattoo inks.
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Affiliation(s)
- Michael Giulbudagian
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Beatrice Battisini
- Department of Environment and Health, Istituto Superiore di Sanità (ISS), Rome, Italy
| | - Wolfgang Bäumler
- Department of Dermatology, University of Regensburg, Regensburg, Germany
| | - Ana M Blass Rico
- European Commission, DG Internal Market, Industry, Entrepreneurship and SMEs (GROW), Brussels, Belgium
| | - Beatrice Bocca
- Department of Environment and Health, Istituto Superiore di Sanità (ISS), Rome, Italy
| | - Corinna Brungs
- Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany
| | - Marco Famele
- National Centre for Chemicals, Cosmetic Products and Consumer's Health Protection - Istituto Superiore di Sanità (ISS), Rome, Italy
| | - Milena Foerster
- Environment and Lifestyle Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France
| | - Birgit Gutsche
- Karlsruhe Chemical and Veterinary Investigation Authority, Karlsruhe, Germany
| | | | - Urs Hauri
- Kanton Basel-Stadt, Kantonales Laboratorium, Basel, Switzerland
| | - Katarzyna Karpienko
- Department of Metrology and Optoelectronics, Faculty of Electronics, Telecommunication, and Informatics, Gdansk University of Technology, Gdansk, Poland
| | - Uwe Karst
- Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany
| | - Linda M Katz
- Office of Cosmetics and Colors, United States Food and Drug Administration (FDA), College Park, Maryland, USA
| | - Nicolas Kluger
- Department of Dermatology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- "Tattoo Consultation", Department of Dermatology, Bichat - Claude Bernard Hospital, Paris, France
- EADV Tattoo and Body Art Task Force, Lugano, Switzerland
| | - Jørgen Serup
- Department of Dermatology, the Tattoo Clinic, Bispebjerg University Hospital, Copenhagen, Denmark
| | - Ines Schreiver
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Steffen Schubert
- Information Network of Departments of Dermatology - IVDK, Institute at the University Medical Center Göttingen, Göttingen, Germany
| | | | - Carina Wolf
- Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany
| | - Andreas Luch
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Peter Laux
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Berlin, Germany
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Yang E, Kim JH, Tressler CM, Shen XE, Brown DR, Johnson CC, Hahm TH, Barman I, Glunde K. RaMALDI: Enabling simultaneous Raman and MALDI imaging of the same tissue section. Biosens Bioelectron 2023; 239:115597. [PMID: 37597501 PMCID: PMC10544780 DOI: 10.1016/j.bios.2023.115597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/02/2023] [Accepted: 08/11/2023] [Indexed: 08/21/2023]
Abstract
Multimodal tissue imaging techniques that integrate two complementary modalities are powerful discovery tools for unraveling biological processes and identifying biomarkers of disease. Combining Raman spectroscopic imaging (RSI) and matrix-assisted laser-desorption/ionization (MALDI) mass spectrometry imaging (MSI) to obtain fused images with the advantages of both modalities has the potential of providing spatially resolved, sensitive, specific biomolecular information, but has so far involved two separate sample preparations, or even consecutive tissue sections for RSI and MALDI MSI, resulting in images with inherent disparities. We have developed RaMALDI, a streamlined, integrated, multimodal imaging workflow of RSI and MALDI MSI, performed on a single tissue section with one sample preparation protocol. We show that RaMALDI imaging of various tissues effectively integrates molecular information acquired from both RSI and MALDI MSI of the same sample, which will drive discoveries in cell biology, biomedicine, and pathology, and advance tissue diagnostics.
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Affiliation(s)
- Ethan Yang
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Jeong Hee Kim
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Caitlin M Tressler
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Xinyi Elaine Shen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Dalton R Brown
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Cole C Johnson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Tae-Hun Hahm
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Ishan Barman
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
| | - Kristine Glunde
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA; Departments of Oncology and Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
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Kim JH, Zhang C, Sperati CJ, Barman I, Bagnasco SM. Hyperspectral Raman Imaging for Automated Recognition of Human Renal Amyloid. J Histochem Cytochem 2023; 71:643-652. [PMID: 37833851 PMCID: PMC10617441 DOI: 10.1369/00221554231206858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 09/15/2023] [Indexed: 10/15/2023] Open
Abstract
In the clinical setting, routine identification of the main types of tissue amyloid deposits, light-chain amyloid (AL) and serum amyloid A (AA), is based on histochemical staining; rarer types of amyloid require mass spectrometry analysis. Raman spectroscopic imaging is an analytical tool, which can be used to chemically map, and thus characterize, the molecular composition of fluid and solid tissue. In this proof-of-concept study, we tested the feasibility of applying Raman spectroscopy combined with artificial intelligence to detect and characterize amyloid deposits in unstained frozen tissue sections from kidney biopsies with pathologic diagnosis of AL and AA amyloidosis and control biopsies with no amyloidosis (NA). Raman hyperspectral images, mapped in a 2D grid-like fashion over the tissue sections, were obtained. Three machine learning-assisted analysis models of the hyperspectral images could accurately distinguish AL (types λ and κ), AA, and NA 93-100% of the time. Although very preliminary, these findings illustrate the potential of Raman spectroscopy as a technique to identify, and possibly, subtype renal amyloidosis.
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Affiliation(s)
- Jeong Hee Kim
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Chi Zhang
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - C. John Sperati
- Division of Nephrology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Serena M. Bagnasco
- Clinical Renal Biopsy Service, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
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Lin M, Chang J, Meng Y, Wang S, Liu S, Wang Q. Development of a micro-Raman system for in vivo studying the mechanism of laser biological effects. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 291:122382. [PMID: 36739781 DOI: 10.1016/j.saa.2023.122382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 01/03/2023] [Accepted: 01/14/2023] [Indexed: 06/18/2023]
Abstract
The laser irradiation on organism will produce a series of biological effects, which can be used for basic medical research, diagnosis and treatments of diseases. However, the mechanism of this biological effects is still unclear. As a sensitive molecular monitoring technique, Raman spectroscopy has became a very popular detection method in biomedical research especially in vivo study. In this paper, we present a compact and flexible micro-Raman system for in vivo studying the mechanism of laser biological effects. The system has the two functions of laser induction and Raman measurement, which can realize the micro-area radiation of laser and simultaneously collect the corresponding Raman spectra in vivo. The detection method provided by this home-built system is able to deepen the understanding of laser biological effects mechanism at molecular level, so it is expected that the system is significant for the treatments and diagnosis of diseases in the near future.
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Affiliation(s)
- Manman Lin
- School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China.
| | - Jing Chang
- School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
| | - Yanhong Meng
- School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
| | - Shenghao Wang
- School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
| | - Sheng Liu
- School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
| | - Qiaozhen Wang
- Laboratory of Biophysics, Guangxi Academy of Sciences, Nanning 530003, China
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Liang H, Shi R, Wang H, Zhou Y. Advances in the application of Raman spectroscopy in haematological tumours. Front Bioeng Biotechnol 2023; 10:1103785. [PMID: 36704299 PMCID: PMC9871369 DOI: 10.3389/fbioe.2022.1103785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 12/29/2022] [Indexed: 01/12/2023] Open
Abstract
Hematologic malignancies are a diverse collection of cancers that affect the blood, bone marrow, and organs. They have a very unpredictable prognosis and recur after treatment. Leukemia, lymphoma, and myeloma are the most prevalent symptoms. Despite advancements in chemotherapy and supportive care, the incidence rate and mortality of patients with hematological malignancies remain high. Additionally, there are issues with the clinical diagnosis because several hematological malignancies lack defined, systematic diagnostic criteria. This work provided an overview of the fundamentals, benefits, and limitations of Raman spectroscopy and its use in hematological cancers. The alterations of trace substances can be recognized using Raman spectroscopy. High sensitivity, non-destructive, quick, real-time, and other attributes define it. Clinicians must promptly identify disorders and keep track of analytes in biological fluids. For instance, surface-enhanced Raman spectroscopy is employed in diagnosing gene mutations in myelodysplastic syndromes due to its high sensitivity and multiple detection benefits. Serum indicators for multiple myeloma have been routinely used for detection. The simultaneous observation of DNA strand modifications and the production of new molecular bonds by tip-enhanced Raman spectroscopy is of tremendous significance for diagnosing lymphoma and multiple myeloma with unidentified diagnostic criteria.
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Affiliation(s)
- Haoyue Liang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
| | - Ruxue Shi
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Haoyu Wang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
| | - Yuan Zhou
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China,*Correspondence: Yuan Zhou,
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Todaro B, Begarani F, Sartori F, Luin S. Is Raman the best strategy towards the development of non-invasive continuous glucose monitoring devices for diabetes management? Front Chem 2022; 10:994272. [PMID: 36226124 PMCID: PMC9548653 DOI: 10.3389/fchem.2022.994272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 08/24/2022] [Indexed: 11/27/2022] Open
Abstract
Diabetes has no well-established cure; thus, its management is critical for avoiding severe health complications involving multiple organs. This requires frequent glycaemia monitoring, and the gold standards for this are fingerstick tests. During the last decades, several blood-withdrawal-free platforms have been being studied to replace this test and to improve significantly the quality of life of people with diabetes (PWD). Devices estimating glycaemia level targeting blood or biofluids such as tears, saliva, breath and sweat, are gaining attention; however, most are not reliable, user-friendly and/or cheap. Given the complexity of the topic and the rise of diabetes, a careful analysis is essential to track scientific and industrial progresses in developing diabetes management systems. Here, we summarize the emerging blood glucose level (BGL) measurement methods and report some examples of devices which have been under development in the last decades, discussing the reasons for them not reaching the market or not being really non-invasive and continuous. After discussing more in depth the history of Raman spectroscopy-based researches and devices for BGL measurements, we will examine if this technique could have the potential for the development of a user-friendly, miniaturized, non-invasive and continuous blood glucose-monitoring device, which can operate reliably, without inter-patient variability, over sustained periods.
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Affiliation(s)
- Biagio Todaro
- NEST Laboratory, Scuola Normale SuperiorePisa, Italy
- Correspondence: Biagio Todaro, ; Stefano Luin,
| | - Filippo Begarani
- P.B.L. SRL, Solignano, PR, Italy
- Omnidermal Biomedics SRL, Solignano, PR, Italy
| | - Federica Sartori
- P.B.L. SRL, Solignano, PR, Italy
- Omnidermal Biomedics SRL, Solignano, PR, Italy
| | - Stefano Luin
- NEST Laboratory, Scuola Normale SuperiorePisa, Italy
- NEST, Istituto Nanoscienze, CNR, Pisa, Italy
- Correspondence: Biagio Todaro, ; Stefano Luin,
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Virtual Spectral Selectivity in a Modulated Thermal Infrared Emitter with Lock-In Detection. SENSORS 2022; 22:s22145451. [PMID: 35891137 PMCID: PMC9325177 DOI: 10.3390/s22145451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 07/15/2022] [Accepted: 07/19/2022] [Indexed: 01/25/2023]
Abstract
The need for affordable low-power devices has led MEMS-based thermal emitters to become an interesting option for optical gas sensors. Since these emitters have a low thermal mass, they can be easily modulated and combined with a lock-in amplifier for detection. In this paper, we show that the signal measured by a lock-in amplifier from a thermal emitter that varies its temperature periodically can have different spectral profiles, depending on the reference signal used. These virtual emitters appear because the Fourier series expansion of the emitted radiance, as a function of time, has different coefficients for each wavelength, and this spectral signature, which is different for each harmonic, can be retrieved using a reference signal that corresponds to its frequency. In this study, the effect is first proved theoretically and then is measured experimentally. For this purpose, we performed measurements with an IR camera provided with six different spectral filters of a modulated emitter, in combination with lock-in amplification via software. Finally, we show a potential application of this effect using multiple virtual emitters to gain spectral selectivity and distinguish between two gases, CO2 and CH4.
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Cheng KS, Su YL, Kuo LC, Yang TH, Lee CL, Chen W, Liu SH. Muscle Mass Measurement Using Machine Learning Algorithms with Electrical Impedance Myography. SENSORS 2022; 22:s22083087. [PMID: 35459072 PMCID: PMC9031580 DOI: 10.3390/s22083087] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/15/2022] [Accepted: 04/16/2022] [Indexed: 02/04/2023]
Abstract
Sarcopenia is a wild chronic disease among elderly people. Although it does not entail a life-threatening risk, it will increase the adverse risk due to the associated unsteady gait, fall, fractures, and functional disability. The import factors in diagnosing sarcopenia are muscle mass and strength. The examination of muscle mass must be carried in the clinic. However, the loss of muscle mass can be improved by rehabilitation that can be performed in non-medical environments. Electronic impedance myography (EIM) can measure some parameters of muscles that have the correlations with muscle mass and strength. The goal of this study is to use machine learning algorithms to estimate the total mass of thigh muscles (MoTM) with the parameters of EIM and body information. We explored the seven major muscles of lower limbs. The feature selection methods, including recursive feature elimination (RFE) and feature combination, were used to select the optimal features based on the ridge regression (RR) and support vector regression (SVR) models. The optimal features were the resistance of rectus femoris normalized by the thigh circumference, phase of tibialis anterior combined with the gender, and body information, height, and weight. There were 96 subjects involved in this study. The performances of estimating the MoTM used the regression coefficient (r2) and root-mean-square error (RMSE), which were 0.800 and 0.929, and 1.432 kg and 0.980 kg for RR and SVR models, respectively. Thus, the proposed method could have the potential to support people examining their muscle mass in non-medical environments.
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Affiliation(s)
- Kuo-Sheng Cheng
- Department of Biomedical Engineering, National Cheng Kung University, Tainai 701, Taiwan; (K.-S.C.); (Y.-L.S.); (T.-H.Y.)
| | - Ya-Ling Su
- Department of Biomedical Engineering, National Cheng Kung University, Tainai 701, Taiwan; (K.-S.C.); (Y.-L.S.); (T.-H.Y.)
| | - Li-Chieh Kuo
- Department of Occupational Therapy, National Cheng Kung University, Tainan 701, Taiwan;
| | - Tai-Hua Yang
- Department of Biomedical Engineering, National Cheng Kung University, Tainai 701, Taiwan; (K.-S.C.); (Y.-L.S.); (T.-H.Y.)
| | - Chia-Lin Lee
- Department of Physical Education, National Kaohsiung Normal University, Kaohsiung City 80201, Taiwan;
| | - Wenxi Chen
- Biomedical Information Engineering Laboratory, The University of Aizu, Aizu-Wakamatsu City, Fukushima 965-8580, Japan;
| | - Shing-Hong Liu
- Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan
- Correspondence: ; Tel.: +886-4-233230000-7811
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Optimization and Evaluation of an Intelligent Short-Term Blood Glucose Prediction Model Based on Noninvasive Monitoring and Deep Learning Techniques. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:8956850. [PMID: 35449869 PMCID: PMC9017442 DOI: 10.1155/2022/8956850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 03/18/2022] [Indexed: 11/18/2022]
Abstract
Continuous noninvasive blood glucose monitoring and estimation management by using photoplethysmography (PPG) technology always have a series of problems, such as substantial time variability, inaccuracy, and complex nonlinearity. This paper proposes a blood glucose (BG) prediction model for more precise prediction based on BG series decomposition by complete aggregation empirical mode decomposition based on adaptive white noise (CEEMDAN) and the gated recurrent unit (GRU) that is optimized by improved bacterial foraging optimization (IBFO). Hierarchical clustering technology recombines the decomposed BG series according to their sample entropy and the correlations with the original BG trends. Dynamic BG trends are regressed separately for each recombined BG series by the GRU model to realize the more precise estimations, which are optimized by IBFO for its structure and superparameters. Through experiments, the optimized and basic LSTM, RNN, and support vector regression (SVR) are compared to evaluate the performance of the proposed model. The experimental results indicate that the root mean square error (RMSE) and mean absolute percentage error (MAPE) of the 15-min IBFO-GRU prediction is improved on average by about 13.1% and 18.4%, respectively, compared with those of the RNN and LSTM optimized by IBFO. Meanwhile, the proposed model improved the Clarke error grid results by about 2.6% and 5.0% compared with those of the IBFO-LSTM and IBFO-RNN in 30-min prediction and by 4.1% and 6.6% in 15-min ahead forecast, respectively. The evaluation outcomes of our proposed CEEMDAN-IBFO-GRU model have high accuracy and adaptability and can effectively provide early intervention control of the occurrence of hyperglycemic complications.
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