Non-Invasive Electromagnetic Biological Microwave Testing

Blood glucose monitoring is a primary tool for the care of diabetic patients. At present, there is no noninvasive monitoring technique of blood glucose concentration that is widely accepted in the medical industry. New noninvasive measurement techniques are being investigated. This work focuses on the possibility of a monitor that noninvasively measures blood glucose levels using electromagnetic waves. The technique is based on relating a monitoring antenna’s resonant frequency to the permittivity, and conductivity of skin, which in turn, is related to the glucose levels. This becomes a hot researched field in recent years. Different types of antennas (wideband and narrowband) have been designed, constructed, and tested in free space. An analytical model for the antenna has been developed, which has been validated with simulations. Microstrip antenna is one of the most common planar antenna structures used. Extensive research development aimed at exploiting its advantages such as lightweight, low cost, conformal configurations, and compatibility with integrated circuits have been carried out. Rectangular and circular patches are the basic shapes that are the most commonly used in microstrip antennas. Ideally, the dielectric constant εr, however, and other performance requirements may dictate the use of substrate whose dielectric constant can be greater. As in our prototype blood sensor, the miniaturized size is one of the main challenges

The future of laboratory medicine - A 2014 perspective.

Predicting the future is a difficult task. Not surprisingly, there are many examples and assumptions that have proved to be wrong. This review surveys the many predictions, beginning in 1887, about the future of laboratory medicine and its sub-specialties such as clinical chemistry and molecular pathology. It provides a commentary on the accuracy of the predictions and offers opinions on emerging technologies, economic factors and social developments that may play a role in shaping the future of laboratory medicine

Precision medicine and artificial intelligence : a pilot study on deep learning for hypoglycemic events detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal

Precision medicine and artificial intelligence : a pilot study on deep learning for hypoglycemic events detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal

Vital Sensory Kit For Use With Telemedicine In Developing Countries

In many developing countries, a large percentage of the population lacks access to adequate healthcare. This is especially true in India where close to 70% of the population lives in rural areas and has little to no access to hospitals or clinics. People living in rural India often times cannot afford to pay to see a doctor should they need to make the journey to a hospital. Telemedicine, a breakthrough in the past couple decades, has broken down the barrier between the patient and the physician. It has slowly been implemented in India to make doctors more available to patients through the use of video conferences and other forms of communication. A compact and affordable kit has been developed that will be used to take a patient’s blood pressure, heart rate, blood glucose concentration and oxygen saturation. Our most novel contribution is the non-invasive glucose sensor that will use a near-infrared LED and photodiode in the patient’s earlobe. Currently millions of diabetics do this by pricking their finger. By wirelessly sending data results from the vital sign kit, the first essential part of a treatment can be carried out via wireless communication, saving the doctor and patient time and money

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

Background: Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially. Approach: An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence-Based Laboratory Medicine Committee of the American Association for Clinical Chemistry jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association. Content: In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A$_{1c}$ (HbA$_{1c}$) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of HbA$_{1c}$. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. Summary: The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended

Near infrared spectroscopy (NIRS) applications in medical: non-invasive and invasive leukemia screening

Near Infrared Spectroscopy (NIRS) has been applied as analytical tool in numerous field of study due to its ability in non-invasive application. NIRS with the ability in providing the information on biological molecules shows a high potential as a diagnosis tool in medical as diseased related to biochemistry changes of the cell and tissue. This paper reviewed the application of NIR spectroscopy in leukemia screening and in other medical application. General comparison between invasive and non-invasive NIR spectroscopy method is provided. The author also proposed a new non-invasive NIRS method in leukemia screening and compared it with the previous invasive NIRS method

Wearable electrochemical biosensors in North America

Tremendous research and commercialization efforts around the world are focused on developing novel wearable electrochemical biosensors that can noninvasively and continuously screen for biochemical markers in body fluids for the prognosis, diagnosis and management of diseases, as well as the monitoring of fitness. Researchers in North America are leading the development of innovative wearable platforms that can comfortably comply to the human body and efficiently sample fluids such as sweat, interstitial fluids, tear and saliva for the electrochemical detection of biomarkers through various sensing approaches such as potentiometric ion selective electrodes and amperometric enzymatic sensors. We start this review with a historical timeline overviewing the major milestones in the development of wearable electrochemical sensors by North American institutions. We then describe how such research efforts have led to pioneering developments and are driving the advancement and commercialization of wearable electrochemical sensors: from minimally invasive continuous glucose monitors for chronic disease management to non-invasive sweat electrolyte sensors for dehydration monitoring in fitness applications. While many countries across the globe have contributed significantly to this rapidly emerging field, their contributions are beyond the scope of this review. Furthermore, we share our perspective on the promising future of wearable electrochemical sensors in applications spanning from remote and personalized healthcare to wellness

Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information

Vibrational spectroscopy has emerged as a promising tool for non-invasive, multiplexed measurement of blood constituents - an outstanding problem in biophotonics. Here, we propose a novel analytical framework that enables spectroscopy-based longitudinal tracking of chemical concentration without necessitating extensive a priori concentration information. The principal idea is to employ a concentration space transformation acquired from the spectral information, where these estimates are used together with the concentration profiles generated from the system kinetic model. Using blood glucose monitoring by Raman spectroscopy as an illustrative example, we demonstrate the efficacy of the proposed approach as compared to conventional calibration methods. Specifically, our approach exhibits a 35% reduction in error over partial least squares regression when applied to a dataset acquired from human subjects undergoing glucose tolerance tests. This method offers a new route at screening gestational diabetes and opens doors for continuous process monitoring without sample perturbation at intermediate time points.National Institute for Biomedical Imaging and Bioengineering (U.S.) (9P41EB015871-27)Kwansei Gakuin University (Grant 126004