Noninvasive Monitoring of Blood Glucose Using Color-Coded Photoplethysmographic Images of the Illuminated Fingertip Within the Visible and Near-Infrared Range: Opportunities and Questions

Vahlsing, Thorsten; Delbeck, Sven; Leonhardt, Steffen; Heise, H. M.

doi:10.1177/1932296818798347

Cited by 25 publications

(9 citation statements)

References 41 publications

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“…Global companies are developing other innovative medical devices as well, including non-invasive glucose meters. 30 31 Such bio-signal monitoring devices can be used for disease management and treatment in different hospital environments, such as intensive care unit, operating room, emergency room, and recovery room, in addition to being used for predicting and diagnosing diseases based on the accumulated real-time information. One prime example of this is the collaboration between Medtronic and IBM in developing Sugar.IQ by combining Medtronic's continuous glucose monitoring and IBM's AI Watson.…”

Section: Ai Application Areas In Health Carementioning

confidence: 99%

Artificial Intelligence in Health Care: Current Applications and Issues

et al. 2020

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In recent years, artificial intelligence (AI) technologies have greatly advanced and become a reality in many areas of our daily lives. In the health care field, numerous efforts are being made to implement the AI technology for practical medical treatments. With the rapid developments in machine learning algorithms and improvements in hardware performances, the AI technology is expected to play an important role in effectively analyzing and utilizing extensive amounts of health and medical data. However, the AI technology has various unique characteristics that are different from the existing health care technologies. Subsequently, there are a number of areas that need to be supplemented within the current health care system for the AI to be utilized more effectively and frequently in health care. In addition, the number of medical practitioners and public that accept AI in the health care is still low; moreover, there are various concerns regarding the safety and reliability of AI technology implementations. Therefore, this paper aims to introduce the current research and application status of AI technology in health care and discuss the issues that need to be resolved.

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Section: Ai Application Areas In Health Carementioning

confidence: 99%

Artificial Intelligence in Health Care: Current Applications and Issues

et al. 2020

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“…One of the shortcomings of this method is the inability to address interference that may come from other devices. Vahlsing et al [32] proposed a photoplethysmograph signal-based smart sensor method which obtains sensors from a device attached to a diabetes patient so that glucose level can be continuously monitored to maintain patient health status. The limitation of this method is that it doesn't show directly how glucose reading can be estimated but rather serve as a trial method.…”

Section: Smart Sensor Methodsmentioning

confidence: 99%

Smart Health Internet of Thing for Continuous Glucose Monitoring: A Survey

Yusuf

Hamza

Muhammad

et al. 2020

IJIE

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Health monitoring system allows patients to monitor the health-related problem to avoid further complications which could result in loss of life. Smart health is one of the categories of a health monitoring system that uses Smartphone’s and sensors to effectively monitor patient health status. However, the smart health internet of thing methods for glucose monitoring still does not provide accurate glucose reading. Hence, diabetes patient can easily loss life. To help understand this challenge, a comprehensive survey focused on smart health internet of thing methods for continuous glucose monitoring was conducted. The paper discusses the benefit and challenge of each method applicable to glucose monitoring. It was observed that several smart health methods required sensor to function. Smart vehicles and remote monitoring have less attention. However, when accommodates can provide future opportunities.

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“…Still, spectroscopic signals originating from glucose molecules are weak, which challenges the signal-to-noise ratio (SNR) of the instrumentation. [16][17][18][19] Fundamentally, the SNR for the instrumentation must be sufficient to enable measurement of the weak signals from glucose over background noise and other sources of instrumental variation. In addition, the measurement signal must be selective relative to all other components of skin, including membranes, glycosylated structures, and soluble compounds within the ISF matrix, such as albumin, urea, amino acids, and ascorbic acid.…”

Section: Technological Approaches For Glucose Monitoring Productsmentioning

confidence: 99%

Products for Monitoring Glucose Levels in the Human Body With Noninvasive Optical, Noninvasive Fluid Sampling, or Minimally Invasive Technologies

Shang

Zhang

Thomas³

et al. 2021

J Diabetes Sci Technol

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Background: Conventional home blood glucose measurements require a sample of blood that is obtained by puncturing the skin at the fingertip. To avoid the pain associated with this procedure, there is high demand for medical products that allow glucose monitoring without blood sampling. In this review article, all such products are presented. Methods: In order to identify such products, four different sources were used: (1) PubMed, (2) Google Patents, (3) Diabetes Technology Meeting Startup Showcase participants, and (4) experts in the field of glucose monitoring. The information obtained were filtered by using two inclusion criteria: (1) regulatory clearance, and/or (2) significant coverage in Google News starting in the year 2016, unless the article indicated that the product had been discontinued. The identified bloodless monitoring products were classified into three categories: (1) noninvasive optical, (2) noninvasive fluid sampling, and (3) minimally invasive devices. Results: In total, 28 noninvasive optical, 6 noninvasive fluid sampling, and 31 minimally invasive glucose monitoring products were identified. Subsequently, these products were characterized according to their regulatory, technological, and consumer features. Products with regulatory clearance are described in greater detail according to their advantages and disadvantages, and with design images. Conclusions: Based on favorable technological features, consumer features, and other advantages, several bloodless products are commercially available and promise to enhance diabetes management. Paths for future products are discussed with an emphasis on understanding existing barriers related to both technical and non-technical issues.

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Noninvasive Monitoring of Blood Glucose Using Color-Coded Photoplethysmographic Images of the Illuminated Fingertip Within the Visible and Near-Infrared Range: Opportunities and Questions

Cited by 25 publications

References 41 publications

Artificial Intelligence in Health Care: Current Applications and Issues

Artificial Intelligence in Health Care: Current Applications and Issues

Smart Health Internet of Thing for Continuous Glucose Monitoring: A Survey

Products for Monitoring Glucose Levels in the Human Body With Noninvasive Optical, Noninvasive Fluid Sampling, or Minimally Invasive Technologies

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