Biosensors

Editorial

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2 pages, 165 KiB

Open AccessEditorial

Non-Invasive Breath Analysis for Disease Screening and Diagnoses

by Hyun Jin Jung and Ronny Priefer

Biosensors 2022, 12(4), 235; https://doi.org/10.3390/bios12040235 - 12 Apr 2022

Cited by 1 | Viewed by 2577

Abstract

Lower respiratory infections are a deadly communicable disease ranked as the fourth leading cause of death globally, with nearly 2 [...] Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

Research

Jump to: Editorial, Review

10 pages, 2159 KiB

Open AccessArticle

In Silico Investigation of SNR and Dermis Sensitivity for Optimum Dual-Channel Near-Infrared Glucose Sensor Designs for Different Skin Colors

by Murad Althobaiti

Biosensors 2022, 12(10), 805; https://doi.org/10.3390/bios12100805 - 29 Sep 2022

Cited by 7 | Viewed by 2750

Abstract

Diabetes is a serious health condition that requires patients to regularly monitor their blood glucose level, making the development of practical, compact, and non-invasive techniques essential. Optical glucose sensors—and, specifically, NIR sensors—have the advantages of being non-invasive, compact, inexpensive, and user-friendly devices. However, [...] Read more.

Diabetes is a serious health condition that requires patients to regularly monitor their blood glucose level, making the development of practical, compact, and non-invasive techniques essential. Optical glucose sensors—and, specifically, NIR sensors—have the advantages of being non-invasive, compact, inexpensive, and user-friendly devices. However, these sensors have low accuracy and are yet to be adopted by healthcare providers. In our previous work, we introduced a non-invasive dual-channel technique for NIR sensors, in which a long channel is utilized to measure the glucose level in the inner skin (dermis) layer, while a short channel is used to measure the noise signal of the superficial skin (epidermis) layer. In this work, we investigated the use of dual-NIR channels for patients with different skin colors (i.e., having different melanin concentrations). We also adopted a Monte Carlo simulation model that takes into consideration the differences between different skin layers, in terms of blood content, water content, melanin concentration in the epidermis layer, and skin optical proprieties. On the basis of the signal-to-noise ratio, as well as the sensitivities of both the epidermis and dermis layers, we suggest the selection of wavelengths and source-to-detector separation for optimal NIR channels under different skin melanin concentrations. This work facilitates the improved design of a compact and non-invasive NIR glucose sensor that can be utilized by patients with different skin colors. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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16 pages, 6872 KiB

Open AccessArticle

Real-Time Cuffless Continuous Blood Pressure Estimation Using 1D Squeeze U-Net Model: A Progress toward mHealth

by Tasbiraha Athaya and Sunwoong Choi

Biosensors 2022, 12(8), 655; https://doi.org/10.3390/bios12080655 - 18 Aug 2022

Cited by 7 | Viewed by 2790

Abstract

Measuring continuous blood pressure (BP) in real time by using a mobile health (mHealth) application would open a new door in the advancement of the healthcare system. This study aimed to propose a real-time method and system for measuring BP without using a [...] Read more.

Measuring continuous blood pressure (BP) in real time by using a mobile health (mHealth) application would open a new door in the advancement of the healthcare system. This study aimed to propose a real-time method and system for measuring BP without using a cuff from a digital artery. An energy-efficient real-time smartphone-application-friendly one-dimensional (1D) Squeeze U-net model is proposed to estimate systolic and diastolic BP values, using only raw photoplethysmogram (PPG) signal. The proposed real-time cuffless BP prediction method was assessed for accuracy, reliability, and potential usefulness in the hypertensive assessment of 100 individuals in two publicly available datasets: Multiparameter Intelligent Monitoring in Intensive Care (MIMIC-I) and Medical Information Mart for Intensive Care (MIMIC-III) waveform database. The proposed model was used to build an android application to measure BP at home. This proposed deep-learning model performs best in terms of systolic BP, diastolic BP, and mean arterial pressure, with a mean absolute error of 4.42, 2.25, and 2.56 mmHg and standard deviation of 4.78, 2.98, and 3.21 mmHg, respectively. The results meet the grade A performance requirements of the British Hypertension Society and satisfy the AAMI error range. The result suggests that only using a short-time PPG signal is sufficient to obtain accurate BP measurements in real time. It is a novel approach for real-time cuffless BP estimation by implementing an mHealth application and can measure BP at home and assess hypertension. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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9 pages, 980 KiB

Open AccessCommunication

Masticatory Myoelectric Side Modular Ratio Asymmetry during Maximal Biting in Women with and without Temporomandibular Disorders

by Felipe Acácio de Paiva, Kariny Realino Ferreira, Michelle Almeida Barbosa and Alexandre Carvalho Barbosa

Biosensors 2022, 12(8), 654; https://doi.org/10.3390/bios12080654 - 18 Aug 2022

Cited by 2 | Viewed by 1488

Abstract

There is no consensus on the role of electromyographic analysis in detecting and characterizing the asymmetries of jaw muscle excitation in patients with temporomandibular disorders (TMD). To analyze the TMD patients (n = 72) in comparison with the healthy controls (n [...] Read more.

There is no consensus on the role of electromyographic analysis in detecting and characterizing the asymmetries of jaw muscle excitation in patients with temporomandibular disorders (TMD). To analyze the TMD patients (n = 72) in comparison with the healthy controls (n = 30), the surface electromyography (sEMG) of the temporalis anterior muscle (TA) and masseter muscle (M) was recorded while a maximal biting task was performed. The differences in the asymmetry of the relationship between the masseter muscles were assessed in a module to determine the sensitivity (Sn) of binomial logistic models, based on the dominance of the TA or the M muscle, in accurately predicting the presence of TMD. All assumptions were met, and comparisons between the groups showed significant differences for the TA muscle ratio (p = 0.007), but not for the M muscle ratio (p = 0.13). The left side was predominant over the right side in the TMD group for both the TA (p = 0.02) and M muscles (p = 0.001), while the non-TMD group had a higher frequency of the right side. Binary logistic regression showed a significant model (χ² = 9.53; p = 0.002) for the TA muscle with Sn = 0.843. The model for the M muscle also showed significance (χ² = 8.03; p = 0.005) with Sn = 0.837. The TMD patients showed an increased TA muscle ratio and asymmetry of left dominance, compared to the healthy subjects. Both of the binomial logistic models, based on muscle dominance TA or M, were moderately sensitive for predicting the presence of TMD. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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8 pages, 1844 KiB

Open AccessCommunication

Short-Term Effect of Cigarette Smoke on Exhaled Volatile Organic Compounds Profile Analyzed by an Electronic Nose

by Silvano Dragonieri, Vitaliano Nicola Quaranta, Enrico Buonamico, Claudia Battisti, Teresa Ranieri, Pierluigi Carratu and Giovanna Elisiana Carpagnano

Biosensors 2022, 12(7), 520; https://doi.org/10.3390/bios12070520 - 13 Jul 2022

Cited by 8 | Viewed by 2246

Abstract

Breath analysis using an electronic nose (e-nose) is an innovative tool for exhaled volatile organic compound (VOC) analysis, which has shown potential in several respiratory and systemic diseases. It is still unclear whether cigarette smoking can be considered a confounder when analyzing the [...] Read more.

Breath analysis using an electronic nose (e-nose) is an innovative tool for exhaled volatile organic compound (VOC) analysis, which has shown potential in several respiratory and systemic diseases. It is still unclear whether cigarette smoking can be considered a confounder when analyzing the VOC-profile. We aimed to assess whether an e-nose can discriminate exhaled breath before and after smoking at different time periods. We enrolled 24 healthy smokers and collected their exhaled breath as follows: (a) before smoking, (b) within 5 min after smoking, (c) within 30 min after smoking, and (d) within 60 min after smoking. Exhaled breath was collected by a previously validated method and analyzed by an e-nose (Cyranose 320). By principal component analysis, significant variations in the exhaled VOC profile were shown for principal component 1 and 2 before and after smoking. Significance was higher 30 and 60 min after smoking than 5 min after (p < 0.01 and <0.05, respectively). Canonical discriminant analysis confirmed the above findings (cross-validated values: baseline vs. 5 min = 64.6%, AUC = 0.833; baseline vs. 30 min = 83.6%, AUC = 0.927; baseline vs. 60 min = 89.6%, AUC = 0.933). Thus, the exhaled VOC profile is influenced by very recent smoking. Interestingly, the effect seems to be more closely linked to post-cigarette inflammation than the tobacco-related odorants. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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11 pages, 1877 KiB

Open AccessArticle

Identifying the Posture of Young Adults in Walking Videos by Using a Fusion Artificial Intelligent Method

by Posen Lee, Tai-Been Chen, Chin-Hsuan Liu, Chi-Yuan Wang, Guan-Hua Huang and Nan-Han Lu

Biosensors 2022, 12(5), 295; https://doi.org/10.3390/bios12050295 - 3 May 2022

Cited by 5 | Viewed by 2323

Abstract

Many neurological and musculoskeletal disorders are associated with problems related to postural movement. Noninvasive tracking devices are used to record, analyze, measure, and detect the postural control of the body, which may indicate health problems in real time. A total of 35 young [...] Read more.

Many neurological and musculoskeletal disorders are associated with problems related to postural movement. Noninvasive tracking devices are used to record, analyze, measure, and detect the postural control of the body, which may indicate health problems in real time. A total of 35 young adults without any health problems were recruited for this study to participate in a walking experiment. An iso-block postural identity method was used to quantitatively analyze posture control and walking behavior. The participants who exhibited straightforward walking and skewed walking were defined as the control and experimental groups, respectively. Fusion deep learning was applied to generate dynamic joint node plots by using OpenPose-based methods, and skewness was qualitatively analyzed using convolutional neural networks. The maximum specificity and sensitivity achieved using a combination of ResNet101 and the naïve Bayes classifier were 0.84 and 0.87, respectively. The proposed approach successfully combines cell phone camera recordings, cloud storage, and fusion deep learning for posture estimation and classification. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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12 pages, 4223 KiB

Open AccessArticle

Paper-Based Substrate for a Surface-Enhanced Raman Spectroscopy Biosensing Platform—A Silver/Chitosan Nanocomposite Approach

by Yuri Kang, Hyeok Jung Kim, Sung Hoon Lee and Hyeran Noh

Biosensors 2022, 12(5), 266; https://doi.org/10.3390/bios12050266 - 22 Apr 2022

Cited by 11 | Viewed by 3396

Abstract

Paper is a popular platform material in all areas of sensor research due to its porosity, large surface area, and biodegradability, to name but a few. Many paper-based nanocomposites have been reported in the last decade as novel substrates for surface-enhanced Raman spectroscopy [...] Read more.

Paper is a popular platform material in all areas of sensor research due to its porosity, large surface area, and biodegradability, to name but a few. Many paper-based nanocomposites have been reported in the last decade as novel substrates for surface-enhanced Raman spectroscopy (SERS). However, there are still limiting factors, like the low density of hot spots or loss of wettability. Herein, we designed a process to fabricate a silver–chitosan nanocomposite layer on paper celluloses by a layer-by-layer method and pH-triggered chitosan assembly. Under microscopic observation, the resulting material showed a nanoporous structure, and silver nanoparticles were anchored evenly over the nanocomposite layer. In SERS measurement, the detection limit of 4-aminothiophenol was 5.13 ppb. Furthermore, its mechanical property and a strategy toward further biosensing approaches were investigated. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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17 pages, 1971 KiB

Open AccessArticle

Application of a Novel Biosensor for Salivary Conductivity in Detecting Chronic Kidney Disease

by Chen-Wei Lin, Yuan-Hsiung Tsai, Yen-Pei Lu, Jen-Tsung Yang, Mei-Yen Chen, Tung-Jung Huang, Rui-Cian Weng and Chun-Wu Tung

Biosensors 2022, 12(3), 178; https://doi.org/10.3390/bios12030178 - 17 Mar 2022

Cited by 6 | Viewed by 3648

Abstract

The prevalence of chronic kidney disease (CKD) is increasing, and it brings an enormous healthcare burden. The traditional measurement of kidney function needs invasive blood tests, which hinders the early detection and causes low awareness of CKD. We recently designed a device with [...] Read more.

The prevalence of chronic kidney disease (CKD) is increasing, and it brings an enormous healthcare burden. The traditional measurement of kidney function needs invasive blood tests, which hinders the early detection and causes low awareness of CKD. We recently designed a device with miniaturized coplanar biosensing probes for measuring salivary conductivity at an extremely low volume (50 μL). Our preliminary data discovered that the salivary conductivity was significantly higher in the CKD patients. This cross-sectional study aims to validate the relationship between salivary conductivity and kidney function, represented by the estimated glomerular filtration rate (eGFR). We enrolled 214 adult participants with a mean age of 63.96 ± 13.53 years, of whom 33.2% were male. The prevalence rate of CKD, defined as eGFR < 60 mL/min/1.73 m², is 11.2% in our study. By multivariate linear regression analyses, we found that salivary conductivity was positively related to age and fasting glucose but negatively associated with eGFR. We further divided subjects into low, medium, and high groups according to the tertials of salivary conductivity levels. There was a significant trend for an increment of CKD patients from low to high salivary conductivity groups (4.2% vs. 12.5% vs. 16.9%, p for trend: 0.016). The receiver operating characteristic (ROC) curves disclosed an excellent performance by using salivary conductivity combined with age, gender, and body weight to diagnose CKD (AUC equal to 0.8). The adjusted odds ratio of CKD is 2.66 (95% CI, 1.10–6.46) in subjects with high salivary conductivity levels. Overall, salivary conductivity can serve as a good surrogate marker of kidney function; this real-time, non-invasive, and easy-to-use portable biosensing device may be a reliable tool for screening CKD. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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11 pages, 20017 KiB

Open AccessArticle

Cu₂O-Based Electrochemical Biosensor for Non-Invasive and Portable Glucose Detection

by Fabiane Fantinelli Franco, Richard A. Hogg and Libu Manjakkal

Biosensors 2022, 12(3), 174; https://doi.org/10.3390/bios12030174 - 14 Mar 2022

Cited by 32 | Viewed by 5879

Abstract

Electrochemical voltammetric sensors are some of the most promising types of sensors for monitoring various physiological analytes due to their implementation as non-invasive and portable devices. Advantages in reduced analysis time, cost-effectiveness, selective sensing, and simple techniques with low-powered circuits distinguish voltammetric sensors [...] Read more.

Electrochemical voltammetric sensors are some of the most promising types of sensors for monitoring various physiological analytes due to their implementation as non-invasive and portable devices. Advantages in reduced analysis time, cost-effectiveness, selective sensing, and simple techniques with low-powered circuits distinguish voltammetric sensors from other methods. In this work, we developed a Cu₂O-based non-enzymatic portable glucose sensor on a graphene paste printed on cellulose cloth. The electron transfer of Cu₂O in a NaOH alkaline medium and sweat equivalent solution at very low potential (+0.35 V) enable its implementation as a low-powered portable glucose sensor. The redox mechanism of the electrodes with the analyte solution was confirmed through cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy studies. The developed biocompatible, disposable, and reproducible sensors showed sensing performance in the range of 0.1 to 1 mM glucose, with a sensitivity of 1082.5 ± 4.7% µA mM⁻¹ cm⁻² on Cu₂O coated glassy carbon electrode and 182.9 ± 8.83% µA mM⁻¹ cm⁻² on Cu₂O coated graphene printed electrodes, making them a strong candidate for future portable, non-invasive glucose monitoring devices on biodegradable substrates. For portable applications we demonstrated the sensor on artificial sweat in 0.1 M NaOH solution, indicating the Cu₂O nanocluster is selective to glucose from 0.0 to +0.6 V even in the presence of common interference such as urea and NaCl. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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6 pages, 1560 KiB

Open AccessCommunication

A Portable RT-LAMP/CRISPR Machine for Rapid COVID-19 Screening

by Meysam Rezaei, Sajad Razavi Bazaz, Dorsa Morshedi Rad, Olga Shimoni, Dayong Jin, William Rawlinson and Majid Ebrahimi Warkiani

Biosensors 2021, 11(10), 369; https://doi.org/10.3390/bios11100369 - 2 Oct 2021

Cited by 18 | Viewed by 5155

Abstract

The COVID-19 pandemic has changed people’s lives and has brought society to a sudden standstill, with lockdowns and social distancing as the preferred preventative measures. To lift these measurements and reduce society’s burden, developing an easy-to-use, rapid, and portable system to detect SARS-CoV-2 [...] Read more.

The COVID-19 pandemic has changed people’s lives and has brought society to a sudden standstill, with lockdowns and social distancing as the preferred preventative measures. To lift these measurements and reduce society’s burden, developing an easy-to-use, rapid, and portable system to detect SARS-CoV-2 is mandatory. To this end, we developed a portable and semi-automated device for SARS-CoV-2 detection based on reverse transcription loop-mediated isothermal amplification followed by a CRISPR/Cas12a reaction. The device contains a heater element mounted on a printed circuit board, a cooler fan, a proportional integral derivative controller to control the temperature, and designated areas for 0.2 mL Eppendorf^® PCR tubes. Our system has a limit of detection of 35 copies of the virus per microliter, which is significant and has the capability of being used in crisis centers, mobile laboratories, remote locations, or airports to diagnose individuals infected with SARS-CoV-2. We believe the current methodology that we have implemented in this article is beneficial for the early screening of infectious diseases, in which fast screening with high accuracy is necessary. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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13 pages, 4186 KiB

Open AccessArticle

Arteriovenous Fistula Flow Dysfunction Surveillance: Early Detection Using Pulse Radar Sensor and Machine Learning Classification

by Cheng-Hsu Chen, Teh-Ho Tao, Yi-Hua Chou, Ya-Wen Chuang and Tai-Been Chen

Biosensors 2021, 11(9), 297; https://doi.org/10.3390/bios11090297 - 26 Aug 2021

Cited by 9 | Viewed by 3844

Abstract

Vascular Access (VA) is often referred to as the “Achilles heel” for a Hemodialysis (HD)-dependent patient. Both the patent and sufficient VA provide adequacy for performing dialysis and reducing dialysis-related complications, while on the contrary, insufficient VA is the main reason for recurrent [...] Read more.

Vascular Access (VA) is often referred to as the “Achilles heel” for a Hemodialysis (HD)-dependent patient. Both the patent and sufficient VA provide adequacy for performing dialysis and reducing dialysis-related complications, while on the contrary, insufficient VA is the main reason for recurrent hospitalizations, high morbidity, and high mortality in HD patients. A non-invasive Vascular Wall Motion (VWM) monitoring system, made up of a pulse radar sensor and Support Vector Machine (SVM) classification algorithm, has been developed to detect access flow dysfunction in Arteriovenous Fistula (AVF). The harmonic ratios derived from the Fast Fourier Transform (FFT) spectrum-based signal processing technique were employed as the input features for the SVM classifier. The result of a pilot clinical trial showed that a more accurate prediction of AVF flow dysfunction could be achieved by the VWM monitor as compared with the Ultrasound Dilution (UD) flow monitor. Receiver Operating Characteristic (ROC) curve analysis showed that the SVM classification algorithm achieved a detection specificity of 100% at detection thresholds in the range from 500 to 750 mL/min and a maximum sensitivity of 95.2% at a detection threshold of 750 mL/min. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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Review

Jump to: Editorial, Research

17 pages, 1744 KiB

Open AccessEditor’s ChoiceReview

Salivary Diagnostics in Pediatrics and the Status of Saliva-Based Biosensors

by Hayeon Min, Sophie Zhu, Lydia Safi, Munzer Alkourdi, Bich Hong Nguyen, Akshaya Upadhyay and Simon D. Tran

Biosensors 2023, 13(2), 206; https://doi.org/10.3390/bios13020206 - 30 Jan 2023

Cited by 10 | Viewed by 4295

Abstract

Salivary biomarkers are increasingly being used as an alternative to diagnose and monitor the progression of various diseases due to their ease of use, on site application, non-invasiveness, and most likely improved patient compliance. Here, we highlight the role of salivary biosensors in [...] Read more.

Salivary biomarkers are increasingly being used as an alternative to diagnose and monitor the progression of various diseases due to their ease of use, on site application, non-invasiveness, and most likely improved patient compliance. Here, we highlight the role of salivary biosensors in the general population, followed by the application of saliva as a diagnostic tool in the pediatric population. We searched the literature for pediatric applications of salivary biomarkers, more specifically, in children from 0 to 18 years old. The use of those biomarkers spans autoimmune, developmental disorders, oncology, neuropsychiatry, respiratory illnesses, gastrointestinal disorders, and oral diseases. Four major applications of salivary proteins as biomarkers are: (1) dental health (caries, stress from orthodontic appliances, and gingivitis); (2) gastrointestinal conditions (eosinophilic esophagitis, acid reflux, appendicitis); (3) metabolic conditions (obesity, diabetes); and (4) respiratory conditions (asthma, allergic rhinitis, small airway inflammation, pneumonia). Genomics, metabolomics, microbiomics, proteomics, and transcriptomics, are various other classifications for biosensing based on the type of biomarkers used and reviewed here. Lastly, we describe the recent advances in pediatric biosensing applications using saliva. This work guides scientists in fabricating saliva-based biosensors by comprehensively overviewing the potential markers and techniques that can be employed. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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20 pages, 2027 KiB

Open AccessReview

A Concise and Systematic Review on Non-Invasive Glucose Monitoring for Potential Diabetes Management

by Soumyasanta Laha, Aditi Rajput, Suvra S. Laha and Rohan Jadhav

Biosensors 2022, 12(11), 965; https://doi.org/10.3390/bios12110965 - 3 Nov 2022

Cited by 27 | Viewed by 9320

Abstract

The current standard of diabetes management depends upon the invasive blood pricking techniques. In recent times, the availability of minimally invasive continuous glucose monitoring devices have made some improvements in the life of diabetic patients however it has its own limitations which include [...] Read more.

The current standard of diabetes management depends upon the invasive blood pricking techniques. In recent times, the availability of minimally invasive continuous glucose monitoring devices have made some improvements in the life of diabetic patients however it has its own limitations which include painful insertion, excessive cost, discomfort and an active risk due to the presence of a foreign body under the skin. Due to all these factors, the non-invasive glucose monitoring has remain a subject of research for the last two decades and multiple techniques of non-invasive glucose monitoring have been proposed. These proposed techniques have the potential to be evolved into a wearable device for non-invasive diabetes management. This paper reviews research advances and major challenges of such techniques or methods in recent years and broadly classifies them into four types based on their detection principles. These four methods are: optical spectroscopy, photoacoustic spectroscopy, electromagnetic sensing and nanomaterial based sensing. The paper primarily focuses on the evolution of non-invasive technology from bench-top equipment to smart wearable devices for personalized non-invasive continuous glucose monitoring in these four methods. With the rapid evolve of wearable technology, all these four methods of non-invasive blood glucose monitoring independently or in combination of two or more have the potential to become a reality in the near future for efficient, affordable, accurate and pain-free diabetes management. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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22 pages, 2036 KiB

Open AccessReview

Medical Devices for Tremor Suppression: Current Status and Future Directions

by Jiancheng Mo and Ronny Priefer

Biosensors 2021, 11(4), 99; https://doi.org/10.3390/bios11040099 - 30 Mar 2021

Cited by 27 | Viewed by 12038

Abstract

Tremors are the most prevalent movement disorder that interferes with the patient’s daily living, and physical activities, ultimately leading to a reduced quality of life. Due to the pathophysiology of tremor, developing effective pharmacotherapies, which are only suboptimal in the management of tremor, [...] Read more.

Tremors are the most prevalent movement disorder that interferes with the patient’s daily living, and physical activities, ultimately leading to a reduced quality of life. Due to the pathophysiology of tremor, developing effective pharmacotherapies, which are only suboptimal in the management of tremor, has many challenges. Thus, a range of therapies are necessary in managing this progressive, aging-associated disorder. Surgical interventions such as deep brain stimulation are able to provide durable tremor control. However, due to high costs, patient and practitioner preference, and perceived high risks, their utilization is minimized. Medical devices are placed in a unique position to bridge this gap between lifestyle interventions, pharmacotherapies, and surgical treatments to provide safe and effective tremor suppression. Herein, we review the mechanisms of action, safety and efficacy profiles, and clinical applications of different medical devices that are currently available or have been previously investigated for tremor suppression. These devices are primarily noninvasive, which can be a beneficial addition to the patient’s existing pharmacotherapy and/or lifestyle intervention. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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16 pages, 554 KiB

Open AccessReview

The Ketogenic Diet: Breath Acetone Sensing Technology

by Omar Alkedeh and Ronny Priefer

Biosensors 2021, 11(1), 26; https://doi.org/10.3390/bios11010026 - 19 Jan 2021

Cited by 23 | Viewed by 6434

Abstract

The ketogenic diet, while originally thought to treat epilepsy in children, is now used for weight loss due to increasing evidence indicating that fat is burned more rapidly when there is a low carbohydrate intake. This low carbohydrate intake can lead to elevated [...] Read more.

The ketogenic diet, while originally thought to treat epilepsy in children, is now used for weight loss due to increasing evidence indicating that fat is burned more rapidly when there is a low carbohydrate intake. This low carbohydrate intake can lead to elevated ketone levels in the blood and breath. Breath and blood ketones can be measured to gauge the level of ketosis and allow for adjustment of the diet to meet the user’s needs. Blood ketone levels have been historically used, but now breath acetone sensors are becoming more common due to less invasiveness and convenience. New technologies are being researched in the area of acetone sensors to capitalize on the rising popularity of the diet. Current breath acetone sensors come in the form of handheld breathalyzer devices. Technologies in development mostly consist of semiconductor metal oxides in different physio-chemical formations. These current devices and future technologies are investigated here with regard to utility and efficacy. Technologies currently in development do not have extensive testing of the selectivity of the sensors including the many compounds present in human breath. While some sensors have undergone human testing, the sample sizes are very small, and the testing was not extensive. Data regarding current devices is lacking and more research needs to be done to effectively evaluate current devices if they are to have a place as medical devices. Future technologies are very promising but are still in early development stages. Full article

(This article belongs to the Special Issue Non-invasive Medical Devices for Detection and Monitoring within Healthcare)

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