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Special Issue "Non-Invasive Biomedical Sensors"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Chemical Sensors".

Deadline for manuscript submissions: 31 May 2019

Special Issue Editors

Guest Editor
Prof. Antonio Tricoli

Australian National University, Research School of Engineering, Canberra, Australia
Website | E-Mail
Phone: +61261251696
Interests: nanotechnology; self-assembly; sensors; nanomedicine; functional coatings; renewable energy production and chemical storage; aerosols; flame synthesis
Guest Editor
Prof. Dr. Giovanni Neri

Department of Engineering, University of Messina, 98166 Messina, Italy
Website | E-Mail
Interests: synthesis of novel sensing materials; nanostructured materials for chemical and electrochemical sensing; metal oxide semiconductor-based gas sensors; biosensors; fabrication of chemical sensors; environmental sensors; automotive gas sensors; biomedical sensors

Special Issue Information

Dear Colleagues,

We would like to cordially invite you to participate in a special issue on “Non-Invasive Biomedical Sensors”. This special issue is focused on the latest achievements in chemical and physical biomedical sensors for the non-invasive and personalized health monitoring. Today, a key factor to reduce costs and time of hospitalization while improving the quality of life and mobility of patients with chronic disorders is the development of non-invasive miniaturized sensor systems, which can be deployed in point of care, used at home or integrated in wearable devices. A key challenge is the engineering of low-cost miniaturized sensing systems which provide continuous, real time and long-term monitoring of key biomarkers.

Various biomedical sensors have been successfully implemented to measure some important physiological parameters like heart rate, blood pressure and breath hydrogen, etc., in a non-invasive way. Further, connecting these devices to a portable/wireless power supply and data transmission unit has the potential to support point-of-care treatment and diagnostics of many diseases, with a dramatic advances over current methods.

However, advancement in materials science, flexible electronics and biomedicine are required to achieve reliable non-invasive measurement of a comprehensive set of biomarkers required for the management of numerous diseases such as blood glucose level for type-1 diabetes. The successful development of platform technologies for non-invasive measurement of a sufficiently broad set of biomarkers could open up to doctors and patients new exciting avenues for personalized health-care monitoring applications in the near future.

Contributions to this Special Issue may include, but are not limited to:

  • Novel sensing techniques for non-invasive measurement of biomarkers;
  • New insights into non-invasive biomarkers which provide information on the physiological state of people;
  • Recent advances in sensor materials, properties and device concepts for non-invasive monitoring of chemical and physical body parameters;
  • Sensor fabrication and testing techniques; Wearable sensors, Wireless sensors, and application-oriented non-invasive sensor systems, as well as closely-related topics, are welcome.
Assoc. Prof. Dr. Antonio Tricoli
Prof. Dr. Giovanni Neri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • non-invasive biomedical sensors
  • wearable sensors
  • wireless sensing devices
  • body-sensor networks
  • breath analysis
  • sweat analysis
  • tear analysis
  • saliva analysis
  • biochemical sensors

Published Papers (13 papers)

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Research

Jump to: Review

Open AccessArticle Reliability and Validity of Non-invasive Blood Pressure Measurement System Using Three-Axis Tactile Force Sensor
Sensors 2019, 19(7), 1744; https://doi.org/10.3390/s19071744
Received: 6 February 2019 / Revised: 18 March 2019 / Accepted: 4 April 2019 / Published: 11 April 2019
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Abstract
Blood pressure (BP) is a physiological parameter reflecting hemodynamic factors and is crucial in evaluating cardiovascular disease and its prognosis. In the present study, the reliability of a non-invasive and continuous BP measurement using a three-axis tactile force sensor was verified. All the [...] Read more.
Blood pressure (BP) is a physiological parameter reflecting hemodynamic factors and is crucial in evaluating cardiovascular disease and its prognosis. In the present study, the reliability of a non-invasive and continuous BP measurement using a three-axis tactile force sensor was verified. All the data were collected every 2 min for the short-term experiment, and every 10 min for the long-term experiment. In addition, the effects on the BP measurement of external physical factors such as the tension to the radial artery on applying the device and wrist circumference were evaluated. A high correlation between the measured BP with the proposed system and with the cuff-based non-invasive blood pressure, and reproducibility, were demonstrated. All data satisfied the Association for the Advancement of Medical Instrumentation criteria. The external physical factors did not affect the measurement results. In addition to previous research indicating the high reliability of the arterial pulse waveforms, the present results have demonstrated the reliability of numerical BP values, and this implies that the three-axis force sensor can be used as a patient monitoring device. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle A Smart Wireless Ear-Worn Device for Cardiovascular and Sweat Parameter Monitoring During Physical Exercise: Design and Performance Results
Sensors 2019, 19(7), 1616; https://doi.org/10.3390/s19071616
Received: 31 January 2019 / Revised: 25 March 2019 / Accepted: 30 March 2019 / Published: 4 April 2019
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Abstract
Wearable biomedical technology has gained much support lately as devices have become more affordable to the general public and they can easily interact with mobile phones and other platforms. The feasibility and accuracy of the data generated by these devices so as to [...] Read more.
Wearable biomedical technology has gained much support lately as devices have become more affordable to the general public and they can easily interact with mobile phones and other platforms. The feasibility and accuracy of the data generated by these devices so as to replace the standard medical methods in use today is still under scrutiny. In this paper, we present an ear-worn device to measure cardiovascular and sweat parameters during physical exercise. ECG bipolar recordings capture the electric potential around both ears, whereas sweat rate is estimated by the impedance method over one segment of tissue closer to the left ear, complemented by the measurement of the lactate and pH levels using amperiometric and potentiometric sensors, respectively. Together with head acceleration, the acquired data is sent to a mobile phone via BLE, enabling extended periods of signal recording. Results obtained by the device have shown a SNR level of 18 dB for the ECG signal recorded around the ears, a THD value of −20.46 dB for the excitation signal involved in impedance measurements, sweat conductivity of 0.08 S/m at 1 kHz and sensitivities of 50 mV/pH and 0.8 μA/mM for the pH and lactate acquisition channels, respectively. Testing of the device was performed in human subjects during indoors cycling with characteristic level changes. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Hydrogel Heart Model with Temperature Memory Properties for Surgical Simulation
Sensors 2019, 19(5), 1102; https://doi.org/10.3390/s19051102
Received: 14 December 2018 / Revised: 15 February 2019 / Accepted: 23 February 2019 / Published: 4 March 2019
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Abstract
The continual development of surgical technology has led to a demand for surgical simulators for evaluating and improving the surgical technique of surgeons. To meet these needs, simulators must incorporate a sensing function into the organ model for evaluating the surgical techniques. However, [...] Read more.
The continual development of surgical technology has led to a demand for surgical simulators for evaluating and improving the surgical technique of surgeons. To meet these needs, simulators must incorporate a sensing function into the organ model for evaluating the surgical techniques. However, it is difficult to incorporate a temperature sensor into the conventional cardiac training model. In this study, we propose a heart model for surgical training of cardiac catheter ablation made from hydrogel, which has temperature memory properties. The heart model consists of a photo-crosslinkable hydrogel mixed with an irreversible temperature indicator that exhibits a color change from magenta to colorless at 55 °C. The Young’s modulus, electrical resistivity, thermal conductivity, and specific heat capacity of the hydrogel material were evaluated and compared with those of human heart. Furthermore, temperature calibration based on the color of the hydrogel material confirmed that the temperature measurement accuracy of the material is ±0.18 °C (at 56 °C). A heart model for catheter ablation was fabricated using the hydrogel material and a molding method, and the color change due to temperature change was evaluated. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Signature Inspired Home Environments Monitoring System Using IR-UWB Technology
Sensors 2019, 19(2), 385; https://doi.org/10.3390/s19020385
Received: 21 December 2018 / Revised: 14 January 2019 / Accepted: 15 January 2019 / Published: 18 January 2019
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Abstract
Home monitoring and remote care systems aim to ultimately provide independent living care scenarios through non-intrusive, privacy-protecting means. Their main aim is to provide care through appreciating normal habits, remotely recognizing changes and acting upon those changes either through informing the person themselves, [...] Read more.
Home monitoring and remote care systems aim to ultimately provide independent living care scenarios through non-intrusive, privacy-protecting means. Their main aim is to provide care through appreciating normal habits, remotely recognizing changes and acting upon those changes either through informing the person themselves, care providers, family members, medical practitioners, or emergency services, depending on need. Care giving can be required at any age, encompassing young to the globally growing aging population. A non-wearable and unobtrusive architecture has been developed and tested here to provide a fruitful health and wellbeing-monitoring framework without interfering in a user’s regular daily habits and maintaining privacy. This work focuses on tracking locations in an unobtrusive way, recognizing daily activities, which are part of maintaining a healthy/regular lifestyle. This study shows an intelligent and locally based edge care system (ECS) solution to identify the location of an occupant’s movement from daily activities using impulse radio-ultra wide band (IR-UWB) radar. A new method is proposed calculating the azimuth angle of a movement from the received pulse and employing radar principles to determine the range of that movement. Moreover, short-term fourier transform (STFT) has been performed to determine the frequency distribution of the occupant’s action. Therefore, STFT, azimuth angle, and range calculation together provide the information to understand how occupants engage with their environment. An experiment has been carried out for an occupant at different times of the day during daily household activities and recorded with time and room position. Subsequently, these time-frequency outcomes, along with the range and azimuth information, have been employed to train a support vector machine (SVM) learning algorithm for recognizing indoor locations when the person is moving around the house, where little or no movement indicates the occurrence of abnormalities. The implemented framework is connected with a cloud server architecture, which enables to act against any abnormality remotely. The proposed methodology shows very promising results through statistical validation and achieved over 90% testing accuracy in a real-time scenario. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Non-Contact, Simple Neonatal Monitoring by Photoplethysmography
Sensors 2018, 18(12), 4362; https://doi.org/10.3390/s18124362
Received: 15 October 2018 / Revised: 29 November 2018 / Accepted: 3 December 2018 / Published: 10 December 2018
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Abstract
This paper presents non-contact vital sign monitoring in neonates, based on image processing, where a standard color camera captures the plethysmographic signal and the heart and breathing rates are processed and estimated online. It is important that the measurements are taken in a [...] Read more.
This paper presents non-contact vital sign monitoring in neonates, based on image processing, where a standard color camera captures the plethysmographic signal and the heart and breathing rates are processed and estimated online. It is important that the measurements are taken in a non-invasive manner, which is imperceptible to the patient. Currently, many methods have been proposed for non-contact measurement. However, to the best of the authors’ knowledge, it has not been possible to identify methods with low computational costs and a high tolerance to artifacts. With the aim of improving contactless measurement results, the proposed method based on the computer vision technique is enhanced to overcome the mentioned drawbacks. The camera is attached to an incubator in the Neonatal Intensive Care Unit and a single area in the neonate’s diaphragm is monitored. Several factors are considered in the stages of image acquisition, as well as in the plethysmographic signal formation, pre-filtering and filtering. The pre-filter step uses numerical analysis techniques to reduce the signal offset. The proposed method decouples the breath rate from the frequency of sinus arrhythmia. This separation makes it possible to analyze independently any cardiac and respiratory dysrhythmias. Nine newborns were monitored with our proposed method. A Bland-Altman analysis of the data shows a close correlation of the heart rates measured with the two approaches (correlation coefficient of 0.94 for heart rate (HR) and 0.86 for breath rate (BR)) with an uncertainty of 4.2 bpm for HR and 4.9 for BR (k = 1). The comparison of our method and another non-contact method considered as a standard independent component analysis (ICA) showed lower central processing unit (CPU) usage for our method (75% less CPU usage). Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Research on the Temperature Characteristics of the Photoacoustic Sensor of Glucose Solution
Sensors 2018, 18(12), 4323; https://doi.org/10.3390/s18124323
Received: 11 October 2018 / Revised: 5 December 2018 / Accepted: 6 December 2018 / Published: 7 December 2018
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Abstract
In order to weaken the influence of temperature on photoacoustic (PA) measurements and compensate PA signals with a proposed theoretical model, the relationship of PA signal amplitude with temperature, under the condition of different glucose concentrations and different light intensities, was studied in [...] Read more.
In order to weaken the influence of temperature on photoacoustic (PA) measurements and compensate PA signals with a proposed theoretical model, the relationship of PA signal amplitude with temperature, under the condition of different glucose concentrations and different light intensities, was studied in this paper. First, the theoretical model was derived from the theory of the PA effect. Then, the temperature characteristics of the PA signals were investigated, based on the analyses of the temperature-dependent Grüneisen parameter in glucose solution. Next, the concept of a PA temperature coefficient was proposed in this paper. The result of the theoretical analysis shows that this coefficient is linear to light intensity and irrelevant to the concentration of glucose solution. Furthermore, a new concept of a PA temperature coefficient of unit light intensity was proposed in this paper. This coefficient is approximately constant, with different light intensities and solution concentrations, which is similar to the thermal expansion coefficient. After calculation, the PA temperature coefficient by the unit light intensity of glucose solution is about 0.936 bar/K. Finally, relevant experiments were carried out to verify the theoretical analysis, and the PA temperature coefficient of the unit light intensity of glucose solution is about 0.04/°C. This method can also be used in sensors measuring concentrations in other aqueous solutions. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Cuffless Blood Pressure Estimation Using Pressure Pulse Wave Signals
Sensors 2018, 18(12), 4227; https://doi.org/10.3390/s18124227
Received: 14 November 2018 / Revised: 27 November 2018 / Accepted: 29 November 2018 / Published: 2 December 2018
Cited by 1 | PDF Full-text (2416 KB) | HTML Full-text | XML Full-text
Abstract
Pulse transit time (PTT) has received considerable attention for noninvasive cuffless blood pressure measurement. However, this approach is inconvenient to deploy in wearable devices because two sensors are required for collecting two-channel physiological signals, such as electrocardiogram and pulse wave signals. In this [...] Read more.
Pulse transit time (PTT) has received considerable attention for noninvasive cuffless blood pressure measurement. However, this approach is inconvenient to deploy in wearable devices because two sensors are required for collecting two-channel physiological signals, such as electrocardiogram and pulse wave signals. In this study, we investigated the pressure pulse wave (PPW) signals collected from one piezoelectric-induced sensor located at a single site for cuffless blood pressure estimation. Twenty-one features were extracted from PPW that collected from the radial artery, and then a linear regression method was used to develop blood pressure estimation models by using the extracted PPW features. Sixty-five middle-aged and elderly participants were recruited to evaluate the performance of the constructed blood pressure estimation models, with oscillometric technique-based blood pressure as a reference. The experimental results indicated that the mean ± standard deviation errors for the estimated systolic blood pressure and diastolic blood pressure were 0.70 ± 7.78 mmHg and 0.83 ± 5.45 mmHg, which achieved a decrease of 1.33 ± 0.37 mmHg in systolic blood pressure and 1.14 ± 0.20 mmHg in diastolic blood pressure, compared with the conventional PTT-based method. The proposed model also demonstrated a high level of robustness in a maximum 60-day follow-up study. These results indicated that PPW obtained from the piezoelectric sensor has great feasibility for cuffless blood pressure estimation, and could serve as a promising method in home healthcare settings. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Highly Sensitive Room-Temperature Sensor Based on Nanostructured K2W7O22 for Application in the Non-Invasive Diagnosis of Diabetes
Sensors 2018, 18(11), 3703; https://doi.org/10.3390/s18113703
Received: 21 September 2018 / Revised: 26 October 2018 / Accepted: 29 October 2018 / Published: 31 October 2018
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Abstract
Diabetes is one of the most rapidly-growing chronic diseases in the world. Acetone, a volatile organic compound in exhaled breath, shows a positive correlation with blood glucose and has proven to be a biomarker for type-1 diabetes. Measuring the level of acetone in [...] Read more.
Diabetes is one of the most rapidly-growing chronic diseases in the world. Acetone, a volatile organic compound in exhaled breath, shows a positive correlation with blood glucose and has proven to be a biomarker for type-1 diabetes. Measuring the level of acetone in exhaled breath can provide a non-invasive, low risk of infection, low cost, and convenient way to monitor the health condition of diabetics. There has been continuous demand for the improvement of this non-invasive, sensitive sensor system to provide a fast and real-time electronic readout of blood glucose levels. A novel nanostructured K2W7O22 has been recently used to test acetone with concentration from 0 parts-per-million (ppm) to 50 ppm at room temperature. The results revealed that a K2W7O22 sensor shows a sensitive response to acetone, but the detection limit is not ideal due to the limitations of the detection system of the device. In this paper, we report a K2W7O22 sensor with an improved sensitivity and detection limit by using an optimized circuit to minimize the electronic noise and increase the signal to noise ratio for the purpose of weak signal detection while the concentration of acetone is very low. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle LTCC Packaged Ring Oscillator Based Sensor for Evaluation of Cell Proliferation
Sensors 2018, 18(10), 3346; https://doi.org/10.3390/s18103346
Received: 29 August 2018 / Revised: 27 September 2018 / Accepted: 2 October 2018 / Published: 7 October 2018
Cited by 1 | PDF Full-text (3971 KB) | HTML Full-text | XML Full-text
Abstract
A complementary metal-oxide-semiconductor (CMOS) chip biosensor was developed for cell viability monitoring based on an array of capacitance sensors utilizing a ring oscillator. The chip was packaged in a low temperature co-fired ceramic (LTCC) module with a flip chip bonding technique. A microcontroller [...] Read more.
A complementary metal-oxide-semiconductor (CMOS) chip biosensor was developed for cell viability monitoring based on an array of capacitance sensors utilizing a ring oscillator. The chip was packaged in a low temperature co-fired ceramic (LTCC) module with a flip chip bonding technique. A microcontroller operates the chip, while the whole measurement system was controlled by PC. The developed biosensor was applied for measurement of the proliferation stage of adherent cells where the sensor response depends on the ratio between healthy, viable and multiplying cells, which adhere onto the chip surface, and necrotic or apoptotic cells, which detach from the chip surface. This change in cellular adhesion caused a change in the effective permittivity in the vicinity of the sensor element, which was sensed as a change in oscillation frequency of the ring oscillator. The sensor was tested with human lung epithelial cells (BEAS-2B) during cell addition, proliferation and migration, and finally detachment induced by trypsin protease treatment. The difference in sensor response with and without cells was measured as a frequency shift in the scale of 1.1 MHz from the base frequency of 57.2 MHz. Moreover, the number of cells in the sensor vicinity was directly proportional to the frequency shift. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Non-Invasive Blood Pressure Estimation from ECG Using Machine Learning Techniques
Sensors 2018, 18(4), 1160; https://doi.org/10.3390/s18041160
Received: 24 January 2018 / Revised: 13 March 2018 / Accepted: 26 March 2018 / Published: 11 April 2018
Cited by 3 | PDF Full-text (1106 KB) | HTML Full-text | XML Full-text
Abstract
Background: Blood pressure (BP) measurements have been used widely in clinical and private environments. Recently, the use of ECG monitors has proliferated; however, they are not enabled with BP estimation. We have developed a method for BP estimation using only electrocardiogram (ECG) signals. [...] Read more.
Background: Blood pressure (BP) measurements have been used widely in clinical and private environments. Recently, the use of ECG monitors has proliferated; however, they are not enabled with BP estimation. We have developed a method for BP estimation using only electrocardiogram (ECG) signals. Methods: Raw ECG data are filtered and segmented, and, following this, a complexity analysis is performed for feature extraction. Then, a machine-learning method is applied, combining a stacking-based classification module and a regression module for building systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP) predictive models. In addition, the method allows a probability distribution-based calibration to adapt the models to a particular user. Results: Using ECG recordings from 51 different subjects, 3129 30-s ECG segments are constructed, and seven features are extracted. Using a train-validation-test evaluation, the method achieves a mean absolute error (MAE) of 8.64 mmHg for SBP, 18.20 mmHg for DBP, and 13.52 mmHg for the MAP prediction. When models are calibrated, the MAE decreases to 7.72 mmHg for SBP, 9.45 mmHg for DBP and 8.13 mmHg for MAP. Conclusion: The experimental results indicate that, when a probability distribution-based calibration is used, the proposed method can achieve results close to those of a certified medical device for BP estimation. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Split-Ring Resonator Sensor Penetration Depth Assessment Using In Vivo Microwave Reflectivity and Ultrasound Measurements for Lower Extremity Trauma Rehabilitation
Sensors 2018, 18(2), 636; https://doi.org/10.3390/s18020636
Received: 12 January 2018 / Revised: 14 February 2018 / Accepted: 19 February 2018 / Published: 21 February 2018
Cited by 1 | PDF Full-text (3437 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In recent research, microwave sensors have been used to follow up the recovery of lower extremity trauma patients. This is done mainly by monitoring the changes of dielectric properties of lower limb tissues such as skin, fat, muscle, and bone. As part of [...] Read more.
In recent research, microwave sensors have been used to follow up the recovery of lower extremity trauma patients. This is done mainly by monitoring the changes of dielectric properties of lower limb tissues such as skin, fat, muscle, and bone. As part of the characterization of the microwave sensor, it is crucial to assess the signal penetration in in vivo tissues. This work presents a new approach for investigating the penetration depth of planar microwave sensors based on the Split-Ring Resonator in the in vivo context of the femoral area. This approach is based on the optimization of a 3D simulation model using the platform of CST Microwave Studio and consisting of a sensor of the considered type and a multilayered material representing the femoral area. The geometry of the layered material is built based on information from ultrasound images and includes mainly the thicknesses of skin, fat, and muscle tissues. The optimization target is the measured S11 parameters at the sensor connector and the fitting parameters are the permittivity of each layer of the material. Four positions in the femoral area (two at distal and two at thigh) in four volunteers are considered for the in vivo study. The penetration depths are finally calculated with the help of the electric field distribution in simulations of the optimized model for each one of the 16 considered positions. The numerical results show that positions at the thigh contribute the highest penetration values of up to 17.5 mm. This finding has a high significance in planning in vitro penetration depth measurements and other tests that are going to be performed in the future. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle Three-Dimensional Blood Vessel Model with Temperature-Indicating Function for Evaluation of Thermal Damage during Surgery
Sensors 2018, 18(2), 345; https://doi.org/10.3390/s18020345
Received: 21 December 2017 / Revised: 20 January 2018 / Accepted: 23 January 2018 / Published: 25 January 2018
Cited by 1 | PDF Full-text (4386 KB) | HTML Full-text | XML Full-text
Abstract
Surgical simulators have recently attracted attention because they enable the evaluation of the surgical skills of medical doctors and the performance of medical devices. However, thermal damage to the human body during surgery is difficult to evaluate using conventional surgical simulators. In this [...] Read more.
Surgical simulators have recently attracted attention because they enable the evaluation of the surgical skills of medical doctors and the performance of medical devices. However, thermal damage to the human body during surgery is difficult to evaluate using conventional surgical simulators. In this study, we propose a functional surgical model with a temperature-indicating function for the evaluation of thermal damage during surgery. The simulator is made of a composite material of polydimethylsiloxane and a thermochromic dye, which produces an irreversible color change as the temperature increases. Using this material, we fabricated a three-dimensional blood vessel model using the lost-wax process. We succeeded in fabricating a renal vessel model for simulation of catheter ablation. Increases in the temperature of the materials can be measured by image analysis of their color change. The maximum measurement error of the temperature was approximately −1.6 °C/+2.4 °C within the range of 60 °C to 100 °C. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Review

Jump to: Research

Open AccessFeature PaperReview Miniaturized Bio-and Chemical-Sensors for Point-of-Care Monitoring of Chronic Kidney Diseases
Sensors 2018, 18(4), 942; https://doi.org/10.3390/s18040942
Received: 9 February 2018 / Revised: 15 March 2018 / Accepted: 20 March 2018 / Published: 22 March 2018
Cited by 4 | PDF Full-text (4453 KB) | HTML Full-text | XML Full-text
Abstract
This review reports the latest achievements in point-of-care (POC) sensor technologies for the monitoring of ammonia, creatinine and urea in patients suffering of chronic kidney diseases (CKDs). Abnormal levels of these nitrogen biomarkers are found in the physiological fluids, such as blood, urine [...] Read more.
This review reports the latest achievements in point-of-care (POC) sensor technologies for the monitoring of ammonia, creatinine and urea in patients suffering of chronic kidney diseases (CKDs). Abnormal levels of these nitrogen biomarkers are found in the physiological fluids, such as blood, urine and sweat, of CKD patients. Delocalized at-home monitoring of CKD biomarkers via integration of miniaturized, portable, and low cost chemical- and bio-sensors in POC devices, is an emerging approach to improve patients’ health monitoring and life quality. The successful monitoring of CKD biomarkers, performed on the different body fluids by means of sensors having strict requirements in term of size, cost, large-scale production capacity, response time and simple operation procedures for use in POC devices, is reported and discussed. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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