Microwave Hydration Monitoring: System Assessment Using Fasting Volunteers

Besler, Brendon C.; Fear, Elise C.

doi:10.3390/s21216949

Cited by 6 publications

(5 citation statements)

References 36 publications

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“…A simple time of flight technique for estimating permittivity was used to investigate microwave-based hydration assessment using a population of volunteers. 6 Comparing the estimated changes in permittivity to changes in weight and the times fails to establish a clear relationship between permittivity and hydration. Assessing the subtle changes in hydration found in a population of sedentary, healthy adults proves difficult.…”

Section: Highlights Of the Year's Literaturementioning

confidence: 99%

Ramadan Fasting in Health and Disease in 2021: A Narrative Review

Hassan-Beck

Hafidh

Badi³

et al. 2022

Ibnosina Journal of Medicine and Biomedical Sciences

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Introduction: The literature on the health aspects of Ramadan fasting (RF) is widely spread in many journals. Materials and Methods: This is a narrative review of data obtained from the PubMed database (National Library of Medicine, Bethesda, Maryland, United States). We used the search term “Ramadan fasting,” and relevant records were examined. The publications are narrated thematically. Results: The publications spanned fundamental, clinical, professional, cultural, and advocacy facets. The publications crossed conventional disciplinary lines and geographical locations and appeared in journals with different access systems. The contents are presented under the themes that emerged depending on the retrieved literature. This year basic coverage included changes in physiology and nutrition during Ramadan. However, the clinical issues included a wide range of topics. These included the impact of RF on nonalcoholic fatty liver disease and adjustments needed in endocrine replacement therapy for hypothyroidism and adrenal insufficiency. Coverage also included chronic kidney disease. The impact on maternal health, fetal well-being, and long-term effects of RF exposures were addressed in several studies. Studies in cardiovascular medicine focused on blood pressure and cardiovascular risk factors. Sports medicine and athletes' well-being received somewhat prominent coverage. The impact on renal function, particularly in patients with chronic kidney disease, was investigated by a few authors. Several groups addressed the eyes' structure and function, neurological conditions, especially headache disorders, and hematological and oncological conditions. Finally, the impact of RF on several aspects of mental health and well-being was addressed by various groups. Conclusions: Health aspects of RF received a sustained academic interest with a broad spectrum in 2021. This narration provides an overview of the year's scholarly health-related literature on various aspects of health and disease. It should help researchers and clinicians catch up quickly with the health concerns during Ramadan.

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Section: Highlights Of the Year's Literaturementioning

confidence: 99%

Ramadan Fasting in Health and Disease in 2021: A Narrative Review

Hassan-Beck

Hafidh

Badi³

et al. 2022

Ibnosina Journal of Medicine and Biomedical Sciences

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“…The permittivities of skin after dehydration were estimated from the transmission coefficients. The same system was used for dehydration after fasting by measuring reflection and transmission coefficients up to 10 GHz [474]. The results indicated the challenges in measuring the hydration levels of human bodies including the creation of controllable and repeatable scenarios and conditions.…”

Section: ) Hydration Sensormentioning

confidence: 99%

Applications of Microwaves in Medicine

Chiao

Lin

et al. 2023

IEEE J. Microw.

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Advances and updates in medical applications utilizing microwave techniques and technologies are reviewed in this paper. The article aims to provide an overview of enablers for microwave medical applications and their recent progress. The emphasis focuses on the applications of microwaves, in the following order, for 1) signal and data communication for implants and wearables through the human body, 2) electromagnetic energy transfer through tissues, 3) noninvasive, remote or in situ physical and biochemical sensing, and 4) therapeutic purposes by changing tissue properties with controlled thermal effects. For signal and data communication and wireless power transfer, implant and wearable applications are discussed in the categories of pacemakers, endoscopic capsules, brain interfaces, intraocular, cardiac and intracranial pressure sensors, neurostimulators, endoluminal implants, artificial retina, smart lenses, and cochlear implants. For noninvasive sensing, remote vital sign radar, biological cell probing, magnetic resonance and microwave imaging, biochemical, blood glucose, hydration and biomarker sensing applications are introduced. For therapeutic uses, the developments of microwave ablation, balloon angioplasty, and hyperthermia applications are reviewed. The scopes of this article mainly concentrate on the research and development efforts in the past 20 years. Recent review articles on specific topics are cited with accomplishment highlights and trends deliberated. At the end of this article, a brief history of the IEEE Microwave Theory and Techniques Society (MTT-S) Biological Effects and Medical Applications committee and the contributions by its members to the promotion and advancement of microwave technologies in medical fields are chronicled.

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“…There is ongoing progress in the development of biochemical sensors that can measure the concentration of different electrolytes in sweat and hence determine the hydration state of the human body [10]. Side by side with the great ongoing research to develop different types of sensors [11,12], machine learning research is going on to learn from body signals that can be collected from different sensors to detect dehydration based on the effect of cognitive stress triggered by dehydration on the autonomic reactions of the body [7,13,14]. In this section, a short overview is presented for the previous studies in dehydration detection based on machine learning.…”

Section: Background and Related Workmentioning

confidence: 99%

Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device’s Data

Sabry

Eltaras

Labda

et al. 2022

Sensors

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With the ongoing advances in sensor technology and miniaturization of electronic chips, more applications are researched and developed for wearable devices. Hydration monitoring is among the problems that have been recently researched. Athletes, battlefield soldiers, workers in extreme weather conditions, people with adipsia who have no sensation of thirst, and elderly people who lost their ability to talk are among the main target users for this application. In this paper, we address the use of machine learning for hydration monitoring using data from wearable sensors: accelerometer, magnetometer, gyroscope, galvanic skin response sensor, photoplethysmography sensor, temperature, and barometric pressure sensor. These data, together with new features constructed to reflect the activity level, were integrated with personal features to predict the last drinking time of a person and alert the user when it exceeds a certain threshold. The results of applying different models are compared for model selection for on-device deployment optimization. The extra trees model achieved the least error for predicting unseen data; random forest came next with less training time, then the deep neural network with a small model size, which is preferred for wearable devices with limited memory. Embedded on-device testing is still needed to emphasize the results and test for power consumption.

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Microwave Hydration Monitoring: System Assessment Using Fasting Volunteers

Cited by 6 publications

References 36 publications

Ramadan Fasting in Health and Disease in 2021: A Narrative Review

Ramadan Fasting in Health and Disease in 2021: A Narrative Review

Applications of Microwaves in Medicine

Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device’s Data

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