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Nguyen N, Nguyen L, Li H, Bordallo López M, Álvarez Casado C. Evaluation of video-based rPPG in challenging environments: Artifact mitigation and network resilience. Comput Biol Med 2024; 179:108873. [PMID: 39053334 DOI: 10.1016/j.compbiomed.2024.108873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 07/05/2024] [Accepted: 07/08/2024] [Indexed: 07/27/2024]
Abstract
Video-based remote photoplethysmography (rPPG) has emerged as a promising technology for non-contact vital sign monitoring, especially under controlled conditions. However, the accurate measurement of vital signs in real-world scenarios faces several challenges, including artifacts induced by videocodecs, low-light noise, degradation, low dynamic range, occlusions, and hardware and network constraints. In this article, a systematic and comprehensive investigation of these issues is conducted, measuring their detrimental effects on the quality of rPPG measurements. Additionally, practical strategies are proposed for mitigating these challenges to improve the dependability and resilience of video-based rPPG systems. Methods for effective biosignal recovery in the presence of network limitations are detailed, along with denoising and inpainting techniques aimed at preserving video frame integrity. Compared to previous studies, this paper addresses a broader range of variables and demonstrates improved accuracy across various rPPG methods, emphasizing generalizability for practical applications in diverse scenarios with varying data quality. Extensive evaluations and direct comparisons demonstrate the effectiveness of these approaches in enhancing rPPG measurements under challenging environments, contributing to the development of more reliable and effective remote vital sign monitoring technologies.
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Affiliation(s)
- Nhi Nguyen
- Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland.
| | - Le Nguyen
- Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland.
| | - Honghan Li
- Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland; Division of Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan.
| | - Miguel Bordallo López
- Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Oulu, Finland; VTT Technical Research Center of Finland Ltd., Oulu, Finland.
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2
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Ayala L, Mindroc-Filimon D, Rees M, Hübner M, Sellner J, Seidlitz S, Tizabi M, Wirkert S, Seitel A, Maier-Hein L. The SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA) for video-rate functional imaging of the skin. Sci Data 2024; 11:536. [PMID: 38796545 PMCID: PMC11127995 DOI: 10.1038/s41597-024-03307-y] [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: 06/20/2023] [Accepted: 04/24/2024] [Indexed: 05/28/2024] Open
Abstract
Spectral imaging has the potential to become a key technique in interventional medicine as it unveils much richer optical information compared to conventional RBG (red, green, and blue)-based imaging. Thus allowing for high-resolution functional tissue analysis in real time. Its higher information density particularly shows promise for the development of powerful perfusion monitoring methods for clinical use. However, even though in vivo validation of such methods is crucial for their clinical translation, the biomedical field suffers from a lack of publicly available datasets for this purpose. Closing this gap, we generated the SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA). It comprises ten spectral videos (∼20 Hz, approx. 20,000 frames each) systematically recorded of the hands of ten healthy human participants in different functional states. We paired each spectral video with concisely tracked regions of interest, and corresponding diffuse reflectance measurements recorded with a spectrometer. Providing the first openly accessible in human spectral video dataset for perfusion monitoring, our work facilitates the development and validation of new functional imaging methods.
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Affiliation(s)
- Leonardo Ayala
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.
- Medical Faculty, Heidelberg University, Heidelberg, Germany.
| | - Diana Mindroc-Filimon
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Maike Rees
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
| | - Marco Hübner
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
| | - Jan Sellner
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- Helmholtz Information and Data Science School for Health, Karlsruhe/Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
| | - Silvia Seidlitz
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- Helmholtz Information and Data Science School for Health, Karlsruhe/Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
| | - Minu Tizabi
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Sebastian Wirkert
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Alexander Seitel
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
| | - Lena Maier-Hein
- German Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany
- Medical Faculty, Heidelberg University, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- Helmholtz Information and Data Science School for Health, Karlsruhe/Heidelberg, Germany
- National Center for Tumor Diseases (NCT) Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Heidelberg, Germany
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Bhatti F, Engel G, Hampel J, Khalil C, Reber A, Kray S, Greiner T. Non-Contact Face Temperature Measurement by Thermopile-Based Data Fusion. SENSORS (BASEL, SWITZERLAND) 2023; 23:7680. [PMID: 37765738 PMCID: PMC10537608 DOI: 10.3390/s23187680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/03/2023] [Accepted: 09/04/2023] [Indexed: 09/29/2023]
Abstract
Thermal imaging cameras and infrared (IR) temperature measurement devices act as state-of-the-art techniques for non-contact temperature determination of the skin surface. The former is cost-intensive in many cases for widespread application, and the latter requires manual alignment to the measuring point. Due to this background, this paper proposes a new method for automated, non-contact, and area-specific temperature measurement of the facial skin surface. It is based on the combined use of a low-cost thermopile sensor matrix and a 2D image sensor. The temperature values as well as the 2D image data are fused using a parametric affine transformation. Based on face recognition, this allows temperature values to be assigned to selected facial regions and used specifically to determine the skin surface temperature. The advantages of the proposed method are described. It is demonstrated by means of a participant study that the temperature absolute values, which are achieved without manual alignment in an automated manner, are comparable to a commercially available IR-based forehead thermometer.
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Affiliation(s)
- Faraz Bhatti
- Department of Engineering, Pforzheim University, 75175 Pforzheim, Germany
| | - Grischan Engel
- Department of Engineering, Pforzheim University, 75175 Pforzheim, Germany
| | - Joachim Hampel
- Department of Engineering, Pforzheim University, 75175 Pforzheim, Germany
| | | | - Andreas Reber
- Department of Engineering, Pforzheim University, 75175 Pforzheim, Germany
| | - Stefan Kray
- Department of Engineering, Pforzheim University, 75175 Pforzheim, Germany
| | - Thomas Greiner
- Department of Engineering, Pforzheim University, 75175 Pforzheim, Germany
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4
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Moukaddam N, Lamichhane B, Salas R, Goodman W, Sabharwal A. Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder. Behav Neurol 2023; 2023:8552180. [PMID: 37575401 PMCID: PMC10423091 DOI: 10.1155/2023/8552180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 06/28/2023] [Accepted: 07/29/2023] [Indexed: 08/15/2023] Open
Abstract
Introduction Suicide is one of the leading causes of death across different age groups. The persistence of suicidal ideation and the progression of suicidal ideations to action could be related to impulsivity, the tendency to act on urges with low temporal latency, and little forethought. Quantifying impulsivity could thus help suicidality estimation and risk assessments in ideation-to-action suicidality frameworks. Methods To model suicidality with impulsivity quantification, we obtained questionnaires, behavioral tests, heart rate variability (HRV), and resting state functional magnetic resonance imaging measurements from 34 participants with mood disorders. The participants were categorized into three suicidality groups based on their Mini-International Neuropsychiatric Interview: none, low, and moderate to severe. Results Questionnaire and HRV-based impulsivity measures were significantly different between the suicidality groups with higher subscales of impulsivity associated with higher suicidality. A multimodal system to characterize impulsivity objectively resulted in a classification accuracy of 96.77% in the three-class suicidality group prediction task. Conclusions This study elucidates the relative sensitivity of various impulsivity measures in differentiating participants with suicidality and demonstrates suicidality prediction with high accuracy using a multimodal objective impulsivity characterization in participants with mood disorders.
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Affiliation(s)
- Nidal Moukaddam
- Menninger Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Bishal Lamichhane
- Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Ramiro Salas
- Menninger Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
- The Menninger Clinic, Houston, TX, USA
- Center for Translational Research on Inflammatory Diseases, Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | - Wayne Goodman
- Menninger Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
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Muhammad R, Htun KT, Nettey-Oppong EE, Ali A, Jeon DK, Jeong HW, Byun KM, Choi SH. Pulse Oximetry Imaging System Using Spatially Uniform Dual Wavelength Illumination. SENSORS (BASEL, SWITZERLAND) 2023; 23:3723. [PMID: 37050784 PMCID: PMC10099045 DOI: 10.3390/s23073723] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 02/25/2023] [Accepted: 03/16/2023] [Indexed: 06/19/2023]
Abstract
Pulse oximetry is a non-invasive method for measuring blood oxygen saturation. However, its detection scheme heavily relies on single-point measurements. If the oxygen saturation is measured at a single location, the measurements are influenced by the profile of illumination, spatial variations in blood flow, and skin pigment. To overcome these issues, imaging systems that measure the distribution of oxygen saturation have been demonstrated. However, previous imaging systems have relied on red and near-infrared illuminations with different profiles, resulting in inconsistent ratios between transmitted red and near-infrared light over space. Such inconsistent ratios can introduce fundamental errors when calculating the spatial distribution of oxygen saturation. In this study, we developed a novel illumination system specifically designed for a pulse oximetry imaging system. For the illumination system, we customized the integrating sphere by coating a mixture of barium sulfate and white paint inside it and by coupling eight red and eight near-infrared LEDs. The illumination system created identical patterns of red and near-infrared illuminations that were spatially uniform. This allowed the ratio between transmitted red and near-infrared light to be consistent over space, enabling the calculation of the spatial distribution of oxygen saturation. We believe our developed pulse oximetry imaging system can be used to obtain spatial information on blood oxygen saturation that provides insight into the oxygenation of the blood contained within the peripheral region of the tissue.
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Affiliation(s)
- Riaz Muhammad
- Department of Biomedical Engineering, Yonsei University, Wonju 26493, Republic of Korea; (R.M.); (K.T.H.); (E.E.N.-O.); (A.A.)
| | - Kay Thwe Htun
- Department of Biomedical Engineering, Yonsei University, Wonju 26493, Republic of Korea; (R.M.); (K.T.H.); (E.E.N.-O.); (A.A.)
| | - Ezekiel Edward Nettey-Oppong
- Department of Biomedical Engineering, Yonsei University, Wonju 26493, Republic of Korea; (R.M.); (K.T.H.); (E.E.N.-O.); (A.A.)
| | - Ahmed Ali
- Department of Biomedical Engineering, Yonsei University, Wonju 26493, Republic of Korea; (R.M.); (K.T.H.); (E.E.N.-O.); (A.A.)
- Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan
| | - Dae Keun Jeon
- Mediana, R&D Center, Wonju 26365, Republic of Korea;
| | - Hyun-Woo Jeong
- Department of Biomedical Engineering, Eulji University, Seongnam 13135, Republic of Korea;
| | - Kyung Min Byun
- Department of Biomedical Engineering, Kyung Hee University, Yongin 17104, Republic of Korea
- Department of Electronics and Information Convergence Engineering, Kyung Hee University, Yongin 17104, Republic of Korea
| | - Seung Ho Choi
- Department of Biomedical Engineering, Yonsei University, Wonju 26493, Republic of Korea; (R.M.); (K.T.H.); (E.E.N.-O.); (A.A.)
- Department of Integrative Medicine, Major in Digital Healthcare, Yonsei University College of Medicine, Seoul 06229, Republic of Korea
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6
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Ayala L, Adler TJ, Seidlitz S, Wirkert S, Engels C, Seitel A, Sellner J, Aksenov A, Bodenbach M, Bader P, Baron S, Vemuri A, Wiesenfarth M, Schreck N, Mindroc D, Tizabi M, Pirmann S, Everitt B, Kopp-Schneider A, Teber D, Maier-Hein L. Spectral imaging enables contrast agent-free real-time ischemia monitoring in laparoscopic surgery. SCIENCE ADVANCES 2023; 9:eadd6778. [PMID: 36897951 PMCID: PMC10005169 DOI: 10.1126/sciadv.add6778] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 02/03/2023] [Indexed: 06/18/2023]
Abstract
Laparoscopic surgery has evolved as a key technique for cancer diagnosis and therapy. While characterization of the tissue perfusion is crucial in various procedures, such as partial nephrectomy, doing so by means of visual inspection remains highly challenging. We developed a laparoscopic real-time multispectral imaging system featuring a compact and lightweight multispectral camera and the possibility to complement the conventional surgical view of the patient with functional information at a video rate of 25 Hz. To enable contrast agent-free ischemia monitoring during laparoscopic partial nephrectomy, we phrase the problem of ischemia detection as an out-of-distribution detection problem that does not rely on data from any other patient and uses an ensemble of invertible neural networks at its core. An in-human trial demonstrates the feasibility of our approach and highlights the potential of spectral imaging combined with advanced deep learning-based analysis tools for fast, efficient, reliable, and safe functional laparoscopic imaging.
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Affiliation(s)
- Leonardo Ayala
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Tim J. Adler
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
| | - Silvia Seidlitz
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- Helmholtz Information and Data Science School for Health, Karlsruhe/Heidelberg, Germany
| | - Sebastian Wirkert
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Alexander Seitel
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jan Sellner
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- Helmholtz Information and Data Science School for Health, Karlsruhe/Heidelberg, Germany
| | | | | | - Pia Bader
- Städtisches Klinikum Karlsruhe, Karlsruhe, Germany
| | | | - Anant Vemuri
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Manuel Wiesenfarth
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Nicholas Schreck
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Diana Mindroc
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Minu Tizabi
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sebastian Pirmann
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Brittaney Everitt
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Dogu Teber
- Städtisches Klinikum Karlsruhe, Karlsruhe, Germany
| | - Lena Maier-Hein
- Division of Intelligent Medical Systems, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Medical Faculty, Heidelberg University, Heidelberg, Germany
- Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany
- Helmholtz Information and Data Science School for Health, Karlsruhe/Heidelberg, Germany
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7
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Volkov IY, Sagaidachnyi AA, Fomin AV. Photoplethysmographic Imaging of Hemodynamics and Two-Dimensional Oximetry. OPTICS AND SPECTROSCOPY 2022; 130:452-469. [PMID: 36466081 PMCID: PMC9708136 DOI: 10.1134/s0030400x22080057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 01/30/2022] [Accepted: 02/04/2022] [Indexed: 06/17/2023]
Abstract
The review of recent papers devoted to actively developing methods of photoplethysmographic imaging (the PPGI) of blood volume pulsations in vessels and non-contact two-dimensional oximetry on the surface of a human body has been carried out. The physical fundamentals and technical aspects of the PPGI and oximetry have been considered. The manifold of the physiological parameters available for the analysis by the PPGI method has been shown. The prospects of the PPGI technology have been discussed. The possibilities of non-contact determination of blood oxygen saturation SpO2 (pulse saturation O2) have been described. The relevance of remote determination of the level of oxygenation in connection with the spread of a new coronavirus infection SARS-CoV-2 (COVID-19) has been emphasized. Most of the works under consideration cover the period 2010-2021.
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Affiliation(s)
| | | | - A. V. Fomin
- Saratov State University, 410012 Saratov, Russia
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8
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Li N, Okmi A, Jabegu T, Zheng H, Chen K, Lomashvili A, Williams W, Maraba D, Kravchenko I, Xiao K, He K, Lei S. van der Waals Semiconductor Empowered Vertical Color Sensor. ACS NANO 2022; 16:8619-8629. [PMID: 35436098 DOI: 10.1021/acsnano.1c09875] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Biomimetic artificial vision is receiving significant attention nowadays, particularly for the development of neuromorphic electronic devices, artificial intelligence, and microrobotics. Nevertheless, color recognition, the most critical vision function, is missed in the current research due to the difficulty of downscaling of the prevailing color sensing devices. Conventional color sensors typically adopt a lateral color sensing channel layout and consume a large amount of physical space, whereas compact designs suffer from an unsatisfactory color detection accuracy. In this work, we report a van der Waals semiconductor-empowered vertical color sensing structure with the emphasis on compact device profile and precise color recognition capability. More attractive, we endow color sensor hardware with the function of chromatic aberration correction, which can simplify the design of an optical lens system and, in turn, further downscales the artificial vision systems. Also, the dimension of a multiple pixel prototype device in our study confirms the scalability and practical potentials of our developed device architecture toward the above applications.
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Affiliation(s)
- Ningxin Li
- Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia 30303, United States
| | - Aisha Okmi
- Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia 30303, United States
- Department of Physics, Jazan University, Jazan 45142, Saudi Arabia
| | - Tara Jabegu
- Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia 30303, United States
| | - Hongkui Zheng
- Department of Materials Science and Engineering, Clemson University, Clemson, South Carolina 29634, United States
| | - Kuangcai Chen
- Department of Chemistry, Georgia State University, Atlanta, Georgia 30303, United States
| | - Alexander Lomashvili
- Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia 30303, United States
| | - Westley Williams
- Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia 30303, United States
| | - Diren Maraba
- Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia 30303, United States
| | - Ivan Kravchenko
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Kai Xiao
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Kai He
- Department of Materials Science and Engineering, Clemson University, Clemson, South Carolina 29634, United States
- Department of Material Science and Engineering, University of California, Irvine, California 92697, United States
| | - Sidong Lei
- Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia 30303, United States
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9
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Almarshad MA, Islam MS, Al-Ahmadi S, BaHammam AS. Diagnostic Features and Potential Applications of PPG Signal in Healthcare: A Systematic Review. Healthcare (Basel) 2022; 10:547. [PMID: 35327025 PMCID: PMC8950880 DOI: 10.3390/healthcare10030547] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/03/2022] [Accepted: 03/11/2022] [Indexed: 02/04/2023] Open
Abstract
Recent research indicates that Photoplethysmography (PPG) signals carry more information than oxygen saturation level (SpO2) and can be utilized for affordable, fast, and noninvasive healthcare applications. All these encourage the researchers to estimate its feasibility as an alternative to many expansive, time-wasting, and invasive methods. This systematic review discusses the current literature on diagnostic features of PPG signal and their applications that might present a potential venue to be adapted into many health and fitness aspects of human life. The research methodology is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines 2020. To this aim, papers from 1981 to date are reviewed and categorized in terms of the healthcare application domain. Along with consolidated research areas, recent topics that are growing in popularity are also discovered. We also highlight the potential impact of using PPG signals on an individual's quality of life and public health. The state-of-the-art studies suggest that in the years to come PPG wearables will become pervasive in many fields of medical practices, and the main domains include cardiology, respiratory, neurology, and fitness. Main operation challenges, including performance and robustness obstacles, are identified.
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Affiliation(s)
- Malak Abdullah Almarshad
- Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia; (M.S.I.); (S.A.-A.)
- Computer Science Department, College of Computer and Information Sciences, Al-Imam Mohammad Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia
| | - Md Saiful Islam
- Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia; (M.S.I.); (S.A.-A.)
| | - Saad Al-Ahmadi
- Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia; (M.S.I.); (S.A.-A.)
| | - Ahmed S. BaHammam
- The University Sleep Disorders Center, Department of Medicine, College of Medicine, King Saud University, Riyadh 11324, Saudi Arabia;
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10
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Fernanda Loera-Diaz L, Granados-Castro L, Gutierrez-Navarro O, Campos-Delgado DU. Multispectral Imaging for Hemoglobin Estimation by PCA. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:3161-3164. [PMID: 34891912 DOI: 10.1109/embc46164.2021.9629574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Tissular blood perfusion is helpful to assess the health condition of a subject and even monitor superficial lesions. Current state of the art is focused on developing non-invasive, quantitative and accessible methods for blood flow monitoring in large areas. This paper presents an approach based on multispectral images on the VIS-NIR range to quantify blood perfusion. Our goal is to estimate the changes in deoxygenated hemoglobin. To do so, we employ principal component analysis followed by a linear regression model. The proposal was evaluated using in-vivo data from a vascular occlusion protocol, and the results were validated against photoplethysmography measurements. Although the number of subjects in the protocol was limited, our model made a prediction with an average similarity of 91.53% with a mean R-squared adjusted of 0.8104.
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11
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Hunt B, Ruiz AJ, Pogue BW. Smartphone-based imaging systems for medical applications: a critical review. JOURNAL OF BIOMEDICAL OPTICS 2021; 26:JBO-200421VR. [PMID: 33860648 PMCID: PMC8047775 DOI: 10.1117/1.jbo.26.4.040902] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 03/29/2021] [Indexed: 05/15/2023]
Abstract
SIGNIFICANCE Smartphones come with an enormous array of functionality and are being more widely utilized with specialized attachments in a range of healthcare applications. A review of key developments and uses, with an assessment of strengths/limitations in various clinical workflows, was completed. AIM Our review studies how smartphone-based imaging (SBI) systems are designed and tested for specialized applications in medicine and healthcare. An evaluation of current research studies is used to provide guidelines for improving the impact of these research advances. APPROACH First, the established and emerging smartphone capabilities that can be leveraged for biomedical imaging are detailed. Then, methods and materials for fabrication of optical, mechanical, and electrical interface components are summarized. Recent systems were categorized into four groups based on their intended application and clinical workflow: ex vivo diagnostic, in vivo diagnostic, monitoring, and treatment guidance. Lastly, strengths and limitations of current SBI systems within these various applications are discussed. RESULTS The native smartphone capabilities for biomedical imaging applications include cameras, touchscreens, networking, computation, 3D sensing, audio, and motion, in addition to commercial wearable peripheral devices. Through user-centered design of custom hardware and software interfaces, these capabilities have the potential to enable portable, easy-to-use, point-of-care biomedical imaging systems. However, due to barriers in programming of custom software and on-board image analysis pipelines, many research prototypes fail to achieve a prospective clinical evaluation as intended. Effective clinical use cases appear to be those in which handheld, noninvasive image guidance is needed and accommodated by the clinical workflow. Handheld systems for in vivo, multispectral, and quantitative fluorescence imaging are a promising development for diagnostic and treatment guidance applications. CONCLUSIONS A holistic assessment of SBI systems must include interpretation of their value for intended clinical settings and how their implementations enable better workflow. A set of six guidelines are proposed to evaluate appropriateness of smartphone utilization in terms of clinical context, completeness, compactness, connectivity, cost, and claims. Ongoing work should prioritize realistic clinical assessments with quantitative and qualitative comparison to non-smartphone systems to clearly demonstrate the value of smartphone-based systems. Improved hardware design to accommodate the rapidly changing smartphone ecosystem, creation of open-source image acquisition and analysis pipelines, and adoption of robust calibration techniques to address phone-to-phone variability are three high priority areas to move SBI research forward.
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Affiliation(s)
- Brady Hunt
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire, United States
- Address all correspondence to Brady Hunt,
| | - Alberto J. Ruiz
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire, United States
| | - Brian W. Pogue
- Dartmouth College, Thayer School of Engineering, Hanover, New Hampshire, United States
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Lasisi T. The constraints of racialization: How classification and valuation hinder scientific research on human variation. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2021; 175:376-386. [PMID: 33675042 DOI: 10.1002/ajpa.24264] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 02/15/2021] [Accepted: 02/17/2021] [Indexed: 12/18/2022]
Abstract
Human biological variation has historically been studied through the lens of racialization. Despite a general shift away from the use of overt racial terminologies, the underlying racialized frameworks used to describe and understand human variation still remain. Even in relatively recent anthropological and biomedical work, we can observe clear manifestations of such racial thinking. This paper shows how classification and valuation are two specific processes which facilitate racialization and hinder attempts to move beyond such frameworks. The bias induced by classification distorts descriptions of phenotypic variation in a way that erroneously portrays European populations as more variable than others. Implicit valuation occurs in tandem with classification and produces narratives of superiority/inferiority for certain phenotypic variants without an objective biological basis. The bias of racialization is a persistent impediment stemming from the inheritance of scientific knowledge developed under explicitly racial paradigms. It is also an internalized cognitive distortion cultivated through socialization in a world where racialization is inescapable. Though undeniably challenging, this does not present an insurmountable barrier, and this bias can be mitigated through the critical evaluation of past work, the active inclusion of marginalized perspectives, and the direct confrontation of institutional structures enforcing racialized paradigms.
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Affiliation(s)
- Tina Lasisi
- Department of Anthropology, Pennsylvania State University, State College, Pennsylvania, USA
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Falotico JM, Shinozaki K, Saeki K, Becker LB. Advances in the Approaches Using Peripheral Perfusion for Monitoring Hemodynamic Status. Front Med (Lausanne) 2020; 7:614326. [PMID: 33365323 PMCID: PMC7750533 DOI: 10.3389/fmed.2020.614326] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 11/16/2020] [Indexed: 12/27/2022] Open
Abstract
Measures of peripheral perfusion can be used to assess the hemodynamic status of critically ill patients. By monitoring peripheral perfusion status, clinicians can promptly initiate life-saving therapy and reduce the likelihood of shock-associated death. Historically, abnormal perfusion has been indicated by the observation of pale, cold, and clammy skin with increased capillary refill time. The utility of these assessments has been debated given that clinicians may vary in their clinical interpretation of body temperature and refill time. Considering these constraints, current sepsis bundles suggest the need to revise resuscitation guidelines. New technologies have been developed to calculate capillary refill time in the hopes of identifying a new gold standard for clinical care. These devices measure either light reflected at the surface of the fingertip (reflected light), or light transmitted through the inside of the fingertip (transmitted light). These new technologies may enable clinicians to monitor peripheral perfusion status more accurately and may increase the potential for ubiquitous hemodynamic monitoring across different clinical settings. This review will summarize the different methods available for peripheral perfusion monitoring and will discuss the advantages and disadvantages of each approach.
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Affiliation(s)
- Julianne M Falotico
- Department of Emergency Medicine, North Shore University Hospital, Northwell Health, Manhasset, NY, United States
| | - Koichiro Shinozaki
- Department of Emergency Medicine, North Shore University Hospital, Northwell Health, Manhasset, NY, United States.,The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
| | - Kota Saeki
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States.,Nihon Kohden Innovation Center, Cambridge, MA, United States
| | - Lance B Becker
- Department of Emergency Medicine, North Shore University Hospital, Northwell Health, Manhasset, NY, United States.,The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States
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