Non-invasive hemoglobin measurement using embedded platform

Pinto, Caje; Parab, Jivan S.; Naik, Gourish M.

doi:10.1016/j.sbsr.2020.100370

Cited by 18 publications

(10 citation statements)

References 6 publications

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“…With the growing interest in tele-home healthcare, PPG embedded in wearable sensors have started to be used to detect multiple cardiovascular diseases (CVD) and indexes, such as atrial fibrillation, heart rate, heart rate variability and blood glucose level. The photoplethysmographic waveform depends on several factors such as the wavelength emitted light, on the anatomical recorded site, on tissue reflectance, on blood volume, cardiac cycle phase, aging and the possible presence of pathologies [42][43][44]. The finger, earlobe and wrist appear to be the best measurement sites with, respectively, 95%, 81% and 86% analyzable waveforms due to the rich arterial supply [45].…”

Section: Photopletysmographymentioning

confidence: 99%

Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review

Zanelli

Ammi

Hallab³

et al. 2022

Sensors

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(1) Background: Diabetes mellitus (DM) is a chronic, metabolic disease characterized by elevated levels of blood glucose. Recently, some studies approached the diabetes care domain through the analysis of the modifications of cardiovascular system parameters. In fact, cardiovascular diseases are the first leading cause of death in diabetic subjects. Thanks to their cost effectiveness and their ease of use, electrocardiographic (ECG) and photoplethysmographic (PPG) signals have recently been used in diabetes detection, blood glucose estimation and diabetes-related complication detection. This review’s aim is to provide a detailed overview of all the published methods, from the traditional (non machine learning) to the deep learning approaches, to detect and manage diabetes using PPG and ECG signals. This review will allow researchers to compare and understand the differences, in terms of results, amount of data and complexity that each type of approach provides and requires. (2) Method: We performed a systematic review based on articles that focus on the use of ECG and PPG signals in diabetes care. The search was focused on keywords related to the topic, such as “Diabetes”, “ECG”, “PPG”, “Machine Learning”, etc. This was performed using databases, such as PubMed, Google Scholar, Semantic Scholar and IEEE Xplore. This review’s aim is to provide a detailed overview of all the published methods, from the traditional (non machine learning) to the deep learning approaches, to detect and manage diabetes using PPG and ECG signals. This review will allow researchers to compare and understand the differences, in terms of results, amount of data and complexity that each type of approach provides and requires. (3) Results: A total of 78 studies were included. The majority of the selected studies focused on blood glucose estimation (41) and diabetes detection (31). Only 7 studies focused on diabetes complications detection. We present these studies by approach: traditional, machine learning and deep learning approaches. (4) Conclusions: ECG and PPG analysis in diabetes care showed to be very promising. Clinical validation and data processing standardization need to be improved in order to employ these techniques in a clinical environment.

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Section: Photopletysmographymentioning

confidence: 99%

Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review

Zanelli

Ammi

Hallab³

et al. 2022

Sensors

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“…Reasons for this include the usual advantages using NIR light, such as deeper tissue penetration, lower autofluorescence, and enhanced image resolution due to reduced scattering; along with the specific advantage of attenuated signal interference caused by variation in the blood oxygen level (a common circumstance in hypoxia imaging) because oxyhemoglobin and deoxyhemoglobin have isosbestic points near 808 nm. [32][33][34] With these desired probe wavelength properties in mind, we decided to synthesize and evaluate homologous next-generation versions of probes 1 and 3 with redshifted absorption/emission wavelengths. A specific goal was to determine if a red-shifted derivative exhibited hyperchromism and produced enhanced photon output when excited at 808 nm.…”

Section: Introductionmentioning

confidence: 99%

Structure‐Activity Studies of Nitroreductase‐Responsive Near‐Infrared Heptamethine Cyanine Fluorescent Probes

et al. 2022

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Two new classes of near‐infrared molecular probes were prepared and shown to exhibit “turn on” fluorescence when cleaved by the nitroreductase enzyme, a well‐known biomarker of cell hypoxia. The fluorescent probes are heptamethine cyanine dyes with a central 4‘‐carboxylic ester group on the heptamethine chain that is converted by a self‐immolative fragmentation mechanism to a 4‘‐caboxylate group that greatly enhances the fluorescence brightness. Each compound was prepared by ring opening of a Zincke salt. The chemical structures have either terminal benzoindolinenes or propargyloxy auxochromes, which provide favorable red‐shifted absorption/emission wavelengths and a hyperchromic effect that enhances the photon output when excited by 808 nm light. A fluorescent probe with terminal propargyloxy‐indolenines exhibited less self‐aggregation and was rapidly activated by nitroreductase with large “turn on“ fluorescence; thus, it is the preferred choice for translation towards in vivo applications.

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“…Further, a pulsatile change in the blood volume was caused by the variation of transmitted or reflected lights. [46][47][48] In addition, the transmission-mode PPG sensors require high D * because of the relatively long light transmission distances compared to those in the reflection-mode PPG sensors. We tested the performance of a transmission-mode PPG sensor using an OPD based on COTCN2 featuring a high D * and well-minimized noise current.…”

Section: Resultsmentioning

confidence: 99%

Effect of Cyano Substitution on Non‐Fullerene Acceptor for Near‐Infrared Organic Photodetectors above 1000 nm

Eun

Park

et al. 2022

Adv Funct Materials

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Near‐infrared organic photodetectors (NIR OPDs) comprising ultra‐narrow bandgap non‐fullerene acceptors (NFA, over 1000 nm) typically exhibit high dark current density under applied reverse bias. Therefore, suppression of dark current density is crucial to achieve high‐performance of such NIR OPDs. Herein, cyano (CN) with a strong electron‐withdrawing property is introduced into alkoxy thiophene as a π‐bridge to adjust its optoelectronic characteristics, and the correlation between dark current density and charge injection barrier is investigated. Compared with their motivated NFA (COTH), the novel CN‐substituted NFAs, COTCN and COTCN2, exhibited deeper‐lying highest occupied molecular orbital energy levels and narrower optical bandgap (<1.10 eV), owing to the strong inductive and resonance effect of CN. The dark current and total noise currents are minimized as the number of substituted CN increases because of the larger hole injection barrier. Consequently, PTB7‐Th:COTCN2 exhibited the best shot‐noise limited detectivity (D*sh, 1.18 × 1012 Jones) and total noise detectivity (D*n, 1.33 × 1011 Jones) compared with those of PTB7‐Th:COTH (D*sh, 2.47 × 1011 Jones and D*n, 1.96 × 1010 Jones).

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Non-invasive hemoglobin measurement using embedded platform

Cited by 18 publications

References 6 publications

Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review

Diabetes Detection and Management through Photoplethysmographic and Electrocardiographic Signals Analysis: A Systematic Review

Structure‐Activity Studies of Nitroreductase‐Responsive Near‐Infrared Heptamethine Cyanine Fluorescent Probes

Effect of Cyano Substitution on Non‐Fullerene Acceptor for Near‐Infrared Organic Photodetectors above 1000 nm

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