Journal articles: 'Biomedical signal sensor'

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Aach, T., H. Witte, and T. M. Lehmann. "Sensor, Signal and Image Informatics." Yearbook of Medical Informatics 15, no. 01 (August 2006): 57–67. http://dx.doi.org/10.1055/s-0038-1638479.

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SummaryThe number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments.Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CTbased diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ.The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered.Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

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HAIDER, MOHAMMAD RAFIQUL, JEREMY HOLLEMAN, SALWA MOSTAFA, and SYED KAMRUL ISLAM. "LOW-POWER BIOMEDICAL SIGNAL MONITORING SYSTEM FOR IMPLANTABLE SENSOR APPLICATIONS." International Journal of High Speed Electronics and Systems 20, no. 01 (March 2011): 115–28. http://dx.doi.org/10.1142/s0129156411006453.

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Implantable biomedical sensors and continuous real time in vivo monitoring of various physiological parameters requires low-power sensor electronics and wireless telemetry for transmission of sensor data. In this article, generic blocks required for such systems have been demonstrated with design examples. Ideally neural or electro-chemical sensor signal monitoring units comprise of low noise amplifiers, current or voltage mode analog to digital domain data conversion circuits and wireless telemetry circuits. The low-noise amplifier described here has a novel open loop amplifier scheme used for neural signal recording systems. The design has been implemented using 0.5-μm SOI-BiCMOS process. The fabricated chip can work with 1 V supply and consumes 805 nA. The current mode analog to digital conversion signal processing circuitry takes the current signal as an input and generates a pulse-width modulated data signal. The data signal is then modulated with a high frequency carrier signal to generate FSK data for wireless transmission. The design is fabricated in 0.5-μm standard CMOS process and consumes 1.1 mW of power with 3.5 V supply.

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Soykan, Orhan, Michael R. Neuman, and Howard J. Chizeck. "Signal processing for sensor arrays." Annals of Biomedical Engineering 19, no. 2 (March 1991): 225–26. http://dx.doi.org/10.1007/bf02368474.

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Sosa, J., Juan A. Montiel-Nelson, R. Pulido, and Jose C. Garcia-Montesdeoca. "Design and Optimization of a Low Power Pressure Sensor for Wireless Biomedical Applications." Journal of Sensors 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/352036.

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A blood pressure sensor suitable for wireless biomedical applications is designed and optimized. State-of-the-art blood pressure sensors based on piezoresistive transducers in a full Wheatstone bridge configuration use low ohmic values because of relatively high sensitivity and low noise approach resulting in high power consumption. In this paper, the piezoresistance values are increased in order to reduce by one order of magnitude the power consumption in comparison with literature approaches. The microelectromechanical system (MEMS) pressure sensor, the mixed signal circuits signal conditioning circuitry, and the successive approximation register (SAR) analog-to-digital converter (ADC) are designed, optimized, and integrated in the same substrate using a commercial 1 μm CMOS technology. As result of the optimization, we obtained a digital sensor with high sensitivity, low noise (0.002 μV/Hz), and low power consumption (358 μW). Finally, the piezoresistance noise does not affect the pressure sensor application since its value is lower than half least significant bit (LSB) of the ADC.

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Kledrowetz, Vilem, Roman Prokop, Lukas Fujcik, Michal Pavlik, and Jiří Háze. "Low-power ASIC suitable for miniaturized wireless EMG systems." Journal of Electrical Engineering 70, no. 5 (September 1, 2019): 393–99. http://dx.doi.org/10.2478/jee-2019-0071.

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Abstract Nowadays, the technology advancements of signal processing, low-voltage low-power circuits and miniaturized circuits have enabled the design of compact, battery-powered, high performance solutions for a wide range of, particularly, biomedical applications. Novel sensors for human biomedical signals are creating new opportunities for low weight wearable devices which allow continuous monitoring together with freedom of movement of the users. This paper presents the design and implementation of a novel miniaturized low-power sensor in integrated circuit (IC) form suitable for wireless electromyogram (EMG) systems. Signal inputs (electrodes) are connected to this application-specific integrated circuit (ASIC). The ASIC consists of several consecutive parts. Signals from electrodes are fed to an instrumentation amplifier (INA) with fixed gain of 50 and filtered by two filters (a low-pass and high-pass filter), which remove useless signals and noise with frequencies below 20 Hz and above 500 Hz. Then signal is amplified by a variable gain amplifier. The INA together with the reconfigurable amplifier provide overall gain of 50, 200, 500 or 1250. The amplified signal is then converted to pulse density modulated (PDM) signal using a 12-bit delta-sigma modulator. The ASIC is fabricated in TSMC0.18 mixed-signal CMOS technology.

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He, Le. "Application of Biomedical Signal Acquisition Equipment in Human Sport Heart Rate Monitoring." Journal of Medical Imaging and Health Informatics 10, no. 4 (April 1, 2020): 877–83. http://dx.doi.org/10.1166/jmihi.2020.2948.

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Aiming at exploring biomedical signal acquisition equipment used in human motion heart rate monitoring, the research on the related hardware design and signal processing method was carried out. A biomedical signal acquisition device based on photoplethysmography (PPG) is designed, and the equipment was applied to acquire PPG signals and acceleration sensor signals under different motion states. The analysis of the experimental data showed that, the fusion method of the acceleration sensing information in the motion artifact removal method is perfected. The effectiveness of the baseline drift removal algorithm, motion artifact removal algorithm and dynamic heart rate monitoring algorithm was verified by reconstructing the signal quality evaluation index. To sum up, taking MINDRAY VS-800 as a reference device, it is compared with the adaptive filtering technology in terms of signal quality, BPM detection results and algorithm complexity, and better results are finally obtained.

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Li, Weiwei, Ting Jiang, and Ning Wang. "Compressed Sensing Based on the Characteristic Correlation of ECG in Hybrid Wireless Sensor Network." International Journal of Distributed Sensor Networks 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/325103.

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Hybrid wireless sensor network made up of wireless body area networks (WBANs) and cellular network provides support for telemedicine. In order to facilitate early diagnosis and treatment, WBANs collect and transmit crucial biomedical data to provide a continuous health monitoring by using various biomedical wireless sensors attached on or implanted in the human body. And then, collected signals are sent to a remote data center via cellular network. One of the features of WBAN is that its power consumption and sampling rate should be restricted to a minimum. Compressed sensing (CS) is an emerging signal acquisition/compression methodology which offers a prominent alternative to traditional signal acquisition. It has been proved that the successful recovery rate of multiple measurement vectors (MMV) model is higher than the single measurement vector (SMV) case. In this paper, we propose a simple algorithm of transforming the SMV model into MMV model based on the correlation of electrocardiogram (ECG), such that the MMV model can be used for general ECG signals rather than only several special signals. Experimental results show that its recovery quality is better than some existing CS-based ECG compression algorithms and sufficient for practical use.

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Sun, Ying, Rui Cao, Zhan Lu, Xin Nie, Zhaokai Li, Yonghua Yu, Hongping Tian, Xiangqun Qian, and Jianping Wang. "Design and Testing of an Impact Sensor Using Two Crossed Polyvinylidene Fluoride (PVDF) Films." Transactions of the ASABE 62, no. 5 (2019): 1195–205. http://dx.doi.org/10.13031/trans.13440.

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Abstract. Impact sensors are widely used to detect grain losses in harvesters. Using polyvinylidene fluoride (PVDF) films as sensing elements is a promising way to improve sensor performance due to their high sensitivity, stability, and flexibility. However, the overlap of collision signals significantly reduces the accuracy of a sensor. To solve this problem, a novel impact sensor with two crossed PVDF films was designed and investigated. This sensor has two orthogonal layers of sensing elements that both respond to impacts, which creates positioning information for the impacts. Because of the sensor’s structure, a signal processing method was designed based on multisensor fusion theory. Tests were performed to verify the performance of the proposed impact sensor. The average signal-to-noise ratios (SNRs) for impacted PVDF films were 34.79 and 20.23 dB, respectively, for the upper and lower layers, while the average signal-to-clutter ratios (SCRs) for nonimpacted films were 21.90 and 10.05 dB, respectively. The sensor also has an extremely high detection efficiency of at least 1528 collisions per second and can identify particles that impact at the same time. Keywords: Grain loss detection, Impact sensors, Multisensor fusion, Particle impact tests, PVDF films.

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Sezen, A. S., S. Sivaramakrishnan, S. Hur, R. Rajamani, W. Robbins, and B. J. Nelson. "Passive Wireless MEMS Microphones for Biomedical Applications." Journal of Biomechanical Engineering 127, no. 6 (July 8, 2005): 1030–34. http://dx.doi.org/10.1115/1.2049330.

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This paper introduces passive wireless telemetry based operation for high frequency acoustic sensors. The focus is on the development, fabrication, and evaluation of wireless, batteryless SAW-IDT MEMS microphones for biomedical applications. Due to the absence of batteries, the developed sensors are small and as a result of the batch manufacturing strategy are inexpensive which enables their utilization as disposable sensors. A pulse modulated surface acoustic wave interdigital transducer (SAW-IDT) based sensing strategy has been formulated. The sensing strategy relies on detecting the ac component of the acoustic pressure signal only and does not require calibration. The proposed sensing strategy has been successfully implemented on an in-house fabricated SAW-IDT sensor and a variable capacitor which mimics the impedance change of a capacitive microphone. Wireless telemetry distances of up to 5 centimeters have been achieved. A silicon MEMS microphone which will be used with the SAW-IDT device is being microfabricated and tested. The complete passive wireless sensor package will include the MEMS microphone wire-bonded on the SAW substrate and interrogated through an on-board antenna. This work on acoustic sensors breaks new ground by introducing high frequency (i.e., audio frequencies) sensor measurement utilizing SAW-IDT sensors. The developed sensors can be used for wireless monitoring of body sounds in a number of different applications, including monitoring breathing sounds in apnea patients, monitoring chest sounds after cardiac surgery, and for feedback sensing in compression (HFCC) vests used for respiratory ventilation. Another promising application is monitoring chest sounds in neonatal care units where the miniature sensors will minimize discomfort for the newborns.

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Anderson, William D., Sydney L. M. Wilson, and David W. Holdsworth. "Development of a Wireless Telemetry Sensor Device to Measure Load and Deformation in Orthopaedic Applications." Sensors 20, no. 23 (November 27, 2020): 6772. http://dx.doi.org/10.3390/s20236772.

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Due to sensor size and supporting circuitry, in-vivo load and deformation measurements are currently restricted to applications within larger orthopaedic implants. The objective of this study is to repurpose a commercially available low-power, miniature, wireless, telemetric, tire-pressure sensor (FXTH87) to measure load and deformation for future use in orthopaedic and biomedical applications. The capacitive transducer membrane was modified, and compressive deformation was applied to the transducer to determine the sensor signal value and the internal resistive force. The sensor package was embedded within a deformable enclosure to illustrate potential applications of the sensor for monitoring load. To reach the maximum output signal value, sensors required compressive deformation of 350 ± 24 µm. The output signal value of the sensor was an effective predictor of the applied load on a calibrated plastic strain member, over a range of 35 N. The FXTH87 sensor can effectively sense and transmit load-induced deformations. The sensor does not have a limit on loads it can measure, as long as deformation resulting from the applied load does not exceed 350 µm. The proposed device presents a sensitive and precise means to monitor deformation and load within small-scale, deformable enclosures.

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Iakovidis, Dimitris K. "Sensors, Signal and Image Processing in Biomedicine and Assisted Living." Sensors 20, no. 18 (September 7, 2020): 5071. http://dx.doi.org/10.3390/s20185071.

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Nag, Meetu, Ajay Kumar, and Bhanu Pratap. "A novel graphene pressure sensor with zig–zag shaped piezoresistors for maximum strain coverage for enhancing the sensitivity of the pressure sensor." International Journal for Simulation and Multidisciplinary Design Optimization 12 (2021): 14. http://dx.doi.org/10.1051/smdo/2021013.

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The demand for flexible and wearable sensors is increasing day by day due to varied applications in the biomedical field. Especially highly sensitive sensors are required for the detection of the low signal from the body. It is important to develop a pressure sensor that can convert the maximum input signal into the electrical output. In this paper, the design and performance of graphene piezoresistive pressure sensors have been investigated by zig–zag piezoresistors on the square diaphragm. On the applied pressure, deformation is sensed by the piezoresistors above the diaphragm. Finite element analysis is carried out to investigate the effect of zig–zag piezoresistors on the square diaphragm. Simulated results for the optimized design are obtained for an operating range of 0–100 psi for pressure sensitivity.

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Renna, Marco, Adriano Peruch, John Sunwoo, Zachary Starkweather, Alyssa Martin, and Maria Angela Franceschini. "A Contact-Sensitive Probe for Biomedical Optics." Sensors 22, no. 6 (March 18, 2022): 2361. http://dx.doi.org/10.3390/s22062361.

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Capacitive proximity sensing is widespread in our everyday life, but no sensor for biomedical optics takes advantage of this technology to monitor the probe attachment to the subject’s skin. In particular, when using optical monitoring devices, the capability to quantitatively measure the probe contact can significantly improve data quality and ensure the subject’s safety. We present a custom novel optical probe based on a flexible printed circuit board which integrates a capacitive contact sensor, 3D-printed optic fiber holders and an accelerometer sensor. The device can be effectively adopted during continuous monitoring optical measurements to detect contact quality, motion artifacts, probe detachment and ensure optimal signal quality.

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Giuffrida, Simone Giuseppe, Weronika Forysiak, Pawel Cwynar, and Roza Szweda. "Shaping Macromolecules for Sensing Applications—From Polymer Hydrogels to Foldamers." Polymers 14, no. 3 (January 31, 2022): 580. http://dx.doi.org/10.3390/polym14030580.

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Sensors are tools for detecting, recognizing, and recording signals from the surrounding environment. They provide measurable information on chemical or physical changes, and thus are widely used in diagnosis, environment monitoring, food quality checks, or process control. Polymers are versatile materials that find a broad range of applications in sensory devices for the biomedical sector and beyond. Sensory materials are expected to exhibit a measurable change of properties in the presence of an analyte or a stimulus, characterized by high sensitivity and selectivity of the signal. Signal parameters can be tuned by material features connected with the restriction of macromolecule shape by crosslinking or folding. Gels are crosslinked, three-dimensional networks that can form cavities of different sizes and forms, which can be adapted to trap particular analytes. A higher level of structural control can be achieved by foldamers, which are macromolecules that can attain well-defined conformation in solution. By increasing control over the three-dimensional structure, we can improve the selectivity of polymer materials, which is one of the crucial requirements for sensors. Here, we discuss various examples of polymer gels and foldamer-based sensor systems. We have classified and described applied polymer materials and used sensing techniques. Finally, we deliberated the necessity and potential of further exploration of the field towards the increased selectivity of sensory devices.

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Al Hamadi, Hussam, Amjad Gawanmeh, and Mahmoud Al-Qutayri. "Guided Test Case Generation for Enhanced ECG Bio-Sensors Functional Verification." International Journal of E-Health and Medical Communications 8, no. 4 (October 2017): 1–20. http://dx.doi.org/10.4018/ijehmc.2017100101.

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Testing and verifying the operation of bio-sensor nodes is essential due to the sensitivity and safety-critical aspects of their applications. Simulation technique is frequently used for this task; however, a proper set of test cases is required in order to carry out the simulation process. This paper focuses on enhancing the verification operations of an ElectroCardioGram (ECG) biomedical sensor node through simulation. It presents a new methodology for guided Test Cases Generation (TCG) of ECG signals from formal design specifications. Event-B invariants are used to specify ECG requirements, and then a new algorithm is used to translate these specifications into proper ECG signal parameters. These parameters are subsequently used to control the required shape of the ECG in order to have a wide range of scenarios. The primary objective of this work is to provide ECG test cases to detect design errors in biomedical algorithms. In addition, it can complement the usage of the limited ECG databases currently available to verify the correct operation of ECG bio-sensors.

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Wall, C., D. M. Merfeld, S. D. Rauch, and F. O. Black. "Vestibular prostheses: The engineering and biomedical issues." Journal of Vestibular Research 12, no. 2-3 (June 27, 2003): 95–113. http://dx.doi.org/10.3233/ves-2003-122-305.

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Currently available data demonstrate the need for balance prostheses. Recent technological and biomedical advances now make it feasible to produce miniaturized sensors, signal processors, electric stimulators, and stimulating electrodes that are roughly analogous to a cochlear implant but which provide information about self motion, instead of sound. Many areas require work before balance prostheses become a reality. Some of these include: the development of a motion sensor array, the conversion of the sensed motion into physiologically meaningful information, the delivery of the transformed information to the CNS, the training of vestibular deficient individuals to use the prosthesis, and developing methods to evaluate the efficacy of the device. In this “white paper”, we consider these issues in the context of prototype baseline prosthetic devices.

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Martins, Gustavo Campos, and Fernando Rangel de Sousa. "An RF-Powered Temperature Sensor Designed for Biomedical Applications." Journal of Integrated Circuits and Systems 9, no. 1 (December 28, 2014): 7–15. http://dx.doi.org/10.29292/jics.v9i1.384.

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Continuous patient monitoring enables early detection and treatment of diseases. Small and wireless devices are more comfortable to the patient and simplify the implantation procedure. This paper presents the design and partial testing of an integrated RF-powered temperature sensor suitable for the human body temperature range, from 35 to 42oC. The device was designed using a 130-nm standard CMOS technology and it receives energy from a 900-MHz signal that has power as low as −10 dBm. A calibration method was designed to obtain conversion errors smaller than 0.2oC.

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Randall, Terence C., Ifana Mahbub, Ashraf B. Islam, Mohammad R. Haider, and Syed K. Islam. "Low-power sensor signal monitoring and impulse radio architecture for biomedical applications." Analog Integrated Circuits and Signal Processing 78, no. 1 (September 25, 2013): 209–16. http://dx.doi.org/10.1007/s10470-013-0152-5.

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Wang, Lei, Guang-Zhong Yang, Jin Huang, Jinyong Zhang, Li Yu, Zedong Nie, and David Robert Sime Cumming. "A Wireless Biomedical Signal Interface System-on-Chip for Body Sensor Networks." IEEE Transactions on Biomedical Circuits and Systems 4, no. 2 (April 2010): 112–17. http://dx.doi.org/10.1109/tbcas.2009.2038228.

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Bachmann, Christian, Maryam Ashouei, Valer Pop, Maja Vidojkovic, Harmke Groot, and Bert Gyselinckx. "Low-power wireless sensor nodes for ubiquitous long-term biomedical signal monitoring." IEEE Communications Magazine 50, no. 1 (January 2012): 20–27. http://dx.doi.org/10.1109/mcom.2012.6122528.

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Širaiy, Boris, Roman Trobec, and Vladimir Ilić. "Quality of One-channel Telemetric ECG Sensor Signal in Maximum Exercise Stress Tests." Measurement Science Review 19, no. 3 (June 1, 2019): 79–85. http://dx.doi.org/10.2478/msr-2019-0013.

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Abstract The aim of this study was to evaluate the quality of the ECG signal, obtained from a telemetric body-sensor device during a maximum stress test on an ergometer. Twenty-three subjects, 13 males, were included in the study (20.56±1.19 years). Two different sensor positions were verified on each subject by the concurrent use of two ECG sensors. Each subject participated in four exercise stress tests: two on a treadmill and two on a cycle ergometer. In the first test, both sensors were attached to self-adhesive skin electrodes on the body, while in the second test the sensors were additionally fixed with self-adhesive tapes. The measurements were compared on both ergometers, in terms of the ECG sensors’ positions and the methods used for the sensors’ fixation. The results showed a significant difference in the running speed that provides an assessable ECG signal between the non-fixed and the fixed sensors at position left inferior (p = 0.000), as well as between the positions left inferior and left superior in the first (p = 0.019), and in the second test (p = 0.000) on the treadmill. On the cycle ergometer the differences were significant between the positions left inferior and left superior in the first (p = 0.000), and the second test (p = 0.003), and between the tests with fixed and non-fixed sensors in the position left superior (p = 0.011). The study confirms that ECG sensors could be used for maximal exercise stress tests in laboratories, especially on a cycle ergometer, and that they present a great potential for future use of ECG sensors during physical activity.

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Han, Jae-Joon, Peter C. Doerschuk, Saul B. Gelfand, and Sean J. O'Connor. "Models and Signal Processing for an Implanted Ethanol Bio-Sensor." IEEE Transactions on Biomedical Engineering 55, no. 2 (February 2008): 603–13. http://dx.doi.org/10.1109/tbme.2007.912652.

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Jegan R. and Nimi W.S. "Sensor Based Smart Real Time Monitoring of Patients Conditions Using Wireless Protocol." International Journal of E-Health and Medical Communications 9, no. 3 (July 2018): 79–99. http://dx.doi.org/10.4018/ijehmc.2018070105.

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This article describes how physiological signal monitoring plays an important role in identifying the health condition of heart. In recent years, online monitoring and processing of biomedical signals play a major role in accurate clinical diagnosis. Therefore, there is a requirement for the developing of online monitoring systems that will be helpful for physicians to avoid mistakes. This article focuses on the method for real time acquisition of an ECG and PPG signal and it's processing and monitoring for tele-health applications. This article also presents the real time peak detection of ECG and PPG for vital parameters measurement. The implementation and design of the proposed wireless monitoring system can be done using a graphical programming environment that utilizes less power and a minimized area with reasonable speed. The advantages of the proposed work are very simple, low cost, easy integration with programming environment and continuous monitoring of physiological signals.

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Sander, Tilmann H., Urban Marhl, and Vojko Jazbinšek. "Avoiding non-linearity of optically pumped magnetometer MEG within an actively shielded two-layer mu-metal room." Current Directions in Biomedical Engineering 7, no. 2 (October 1, 2021): 543–46. http://dx.doi.org/10.1515/cdbme-2021-2138.

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Abstract Some optically pumped magnetometer (OPM) sensors available for biomagnetic investigations have a linear range limited to +- 1 nT due to the specific properties of their open loop operation. In a two-layer magnetically shielded room of type Ak3b/Vacoshield Advanced with an external active compensation we studied how much sensor movement is allowed until amplitudes exceed the linearity range. Intentional movements were performed by a subject wearing an OPM-MEG sensor array. It was found that movements of 8 cm did yield non-linear amplitudes, but a reduction of the movement in half already preserves linearity. Despite movements, the heartbeat was found to generate a periodic signal, although the generating mechanism could not be identified so far.

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Schaufler, Anna, Alfredo Illanes, Ivan Maldonado, Axel Boese, Roland Croner, and Michael Friebe. "Surgical Audio Guidance: Feasibility Check for Robotic Surgery Procedures." Current Directions in Biomedical Engineering 6, no. 3 (September 1, 2020): 571–74. http://dx.doi.org/10.1515/cdbme-2020-3146.

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AbstractIn robot-assisted procedures, the surgeon controls the surgical instruments from a remote console, while visually monitoring the procedure through the endoscope. There is no haptic feedback available to the surgeon, which impedes the assessment of diseased tissue and the detection of hidden structures beneath the tissue, such as vessels. Only visual clues are available to the surgeon to control the force applied to the tissue by the instruments, which poses a risk for iatrogenic injuries. Additional information on haptic interactions of the employed instruments and the treated tissue that is provided to the surgeon during robotic surgery could compensate for this deficit. Acoustic emissions (AE) from the instrument/tissue interactions, transmitted by the instrument are a potential source of this information. AE can be recorded by audio sensors that do not have to be integrated into the instruments, but that can be modularly attached to the outside of the instruments shaft or enclosure. The location of the sensor on a robotic system is essential for the applicability of the concept in real situations. While the signal strength of the acoustic emissions decreases with distance from the point of interaction, an installation close to the patient would require sterilization measures. The aim of this work is to investigate whether it is feasible to install the audio sensor in non-sterile areas far away from the patient and still be able to receive useful AE signals. To determine whether signals can be recorded at different potential mounting locations, instrument/tissue interactions with different textures were simulated in an experimental setup. The results showed that meaningful and valuable AE can be recorded in the non-sterile area of a robotic surgical system despite the expected signal losses.

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WANG, LIHUA, YANYAN WANG, JIE ZOU, BIN LIU, and CHUNHAI FAN. "AMPLIFIED BIOSENSING STRATEGIES FOR THE DETECTION OF BIOLOGICALLY RELATED MOLECULES WITH SILICA NANOPARTICLES AND CONJUGATED POLYELECTROLYTES." COSMOS 06, no. 02 (December 2010): 207–19. http://dx.doi.org/10.1142/s0219607710000565.

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Development of rapid, field-portable and cost-effective sensors with high sensitivity and selectivity is of great importance for biomedical diagnostics, food safety and environmental monitoring. Silica nanoparticles (SiNPs) have great potential in sensor application due to their biocompatibility, controllable surface modification, excellent chemical stability and high specific surface area. On the other hand, conjugated polyelectrolytes (CPEs) have been widely used in sensor design due to their efficient Förster resonance energy transfer (FRET) to dyes and unique interaction with biomolecules. In this contribution, we briefly summarize the recent development of silica-related NP-based assays that incorporate CPEs as the signal amplifier or reporter. The silica-related NPs are used for probe immobilization, target recognition and separation, while CPEs provide amplified fluorescence signals and high sensitivity. These assays have been proven efficient for the detection of DNA, proteins, and small molecules through specific biorecognition events, such as DNA hybridization, antibody–antigen recognition and target–aptamer binding.

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Zaheer, Farah, Serge H. Roy, and Carlo J. De Luca. "Preferred sensor sites for surface EMG signal decomposition." Physiological Measurement 33, no. 2 (January 20, 2012): 195–206. http://dx.doi.org/10.1088/0967-3334/33/2/195.

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Wenyao Xu, Mi Zhang, A. A. Sawchuk, and M. Sarrafzadeh. "Robust Human Activity and Sensor Location Corecognition via Sparse Signal Representation." IEEE Transactions on Biomedical Engineering 59, no. 11 (November 2012): 3169–76. http://dx.doi.org/10.1109/tbme.2012.2211355.

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Worster, Susannah Bourne, and P. J. Hore. "Proposal to use superparamagnetic nanoparticles to test the role of cryptochrome in magnetoreception." Journal of The Royal Society Interface 15, no. 147 (October 2018): 20180587. http://dx.doi.org/10.1098/rsif.2018.0587.

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Evidence is accumulating to support the hypothesis that some animals use light-induced radical pairs to detect the direction of the Earth's magnetic field. Cryptochrome proteins seem to be involved in the sensory pathway but it is not yet clear if they are the magnetic sensors: they could, instead, play a non-magnetic role as signal transducers downstream of the primary sensor. Here we propose an experiment with the potential to distinguish these functions. The principle is to use superparamagnetic nanoparticles to disable any magnetic sensing role by enhancing the electron spin relaxation of the radicals so as to destroy their spin correlation. We use spin dynamics simulations to show that magnetoferritin, a synthetic, protein-based nanoparticle, has the required properties. If cryptochrome is the primary sensor, then it should be inactivated by a magnetoferritin particle placed 12–16 nm away. This would prevent a bird from using its magnetic compass in behavioural tests and abolish magnetically sensitive neuronal firing in the retina. The key advantage of such an experiment is that any signal transduction role should be completely unaffected by the tiny magnetic interactions (≪ k B T ) required to enhance the spin relaxation of the radical pair.

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Rathore, Pradeep Kumar, and Brishbhan Singh Panwar. "CMOS-MEMS Based Current Mirror MOSFET Embedded Pressure Sensor for Healthcare and Biomedical Applications." Advanced Materials Research 647 (January 2013): 315–20. http://dx.doi.org/10.4028/www.scientific.net/amr.647.315.

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This paper reports on the design and optimization of current mirror MOSFET embedded pressure sensor. A current mirror circuit with an output current of 1 mA integrated with a pressure sensing n-channel MOSFET has been designed using standard 5 µm CMOS technology. The channel region of the pressure sensing MOSFET forms the flexible diaphragm as well as the strain sensing element. The piezoresistive effect in MOSFET has been exploited for the calculation of strain induced carrier mobility variation. The output transistor of the current mirror forms the active pressure sensing MOSFET which produces a change in its drain current as a result of altered channel mobility under externally applied pressure. COMSOL Multiphysics is utilized for the simulation of pressure sensing structure and Tspice is employed to evaluate the characteristics of the current mirror pressure sensing circuit. Simulation results show that the pressure sensor has a sensitivity of 10.01 mV/MPa. The sensing structure has been optimized through simulation for enhancing the sensor sensitivity to 276.65 mV/MPa. These CMOS-MEMS based pressure sensors integrated with signal processing circuitry on the same chip can be used for healthcare and biomedical applications.

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Yu, Jian-Ping, Wen Wang, Xin Li, and Zhao-Zhong Zhou. "A Novel Quadrature Signal Estimation Method for a Planar Capacitive Incremental Displacement Sensor." Measurement Science Review 16, no. 3 (June 1, 2016): 127–33. http://dx.doi.org/10.1515/msr-2016-0015.

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Abstract This paper presents a novel phase-shift arctangent (PSA) interpolation method to improve the measurement accuracy of a planar capacitive incremental displacement sensor. Signals of planar capacitive micro-sensors acquire waveform errors, including sensitivity differences and phase-shift errors, because of static errors and dynamic disturbances. In the proposed PSA scheme, such errors are removed completely by loading a particular arctangent function. Moreover, measuring efficiency of the proposed planar capacitive sensors is improved by combining coarse measurement and fine estimation. Experiments show unanimous results to model-based fitting. When electrode length is four times the gap distance, applying the PSA interpolation method decreases waveform errors from more than 4 % to 1.72 %.

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Kazanskiy, N. L., S. N. Khonina, M. A. Butt, A. Kaźmierczak, and R. Piramidowicz. "State-of-the-Art Optical Devices for Biomedical Sensing Applications—A Review." Electronics 10, no. 8 (April 19, 2021): 973. http://dx.doi.org/10.3390/electronics10080973.

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Optical sensors for biomedical applications have gained prominence in recent decades due to their compact size, high sensitivity, reliability, portability, and low cost. In this review, we summarized and discussed a few selected techniques and corresponding technological platforms enabling the manufacturing of optical biomedical sensors of different types. We discussed integrated optical biosensors, vertical grating couplers, plasmonic sensors, surface plasmon resonance optical fiber biosensors, and metasurface biosensors, Photonic crystal-based biosensors, thin metal films biosensors, and fiber Bragg grating biosensors as the most representative cases. All of these might enable the identification of symptoms of deadly illnesses in their early stages; thus, potentially saving a patient’s life. The aim of this paper was not to render a definitive judgment in favor of one sensor technology over another. We presented the pros and cons of all the major sensor systems enabling the readers to choose the solution tailored to their needs and demands.

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Pérez-Valero, Jesús, Antonio-Javier Garcia-Sanchez, Manuel Ruiz Marín, and Joan Garcia-Haro. "A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor." Sensors 20, no. 3 (February 7, 2020): 896. http://dx.doi.org/10.3390/s20030896.

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Cardiovascular diseases are the leading cause of death around the world. As a result, low-cost biomedical sensors have been gaining importance in business and research over the last few decades. Their main benefits include their small size, light weight, portability and low power consumption. Despite these advantages, they are not generally used for clinical monitoring mainly because of their low accuracy in data acquisition. In this emerging technological context, this paper contributes by discussing a methodology to help practitioners build a prototype framework based on a low-cost commercial sensor. The resulting application consists of four modules; namely, a digitalization module whose input is an electrocardiograph signal in portable document format (PDF) or joint photographic expert group format (JPEG), a module to further process and filter the digitalized signal, a selectable data calibration module and, finally, a module implementing a classification algorithm to distinguish between individuals with normal sinus rhythms and those with atrial fibrillation. This last module employs our recently published symbolic recurrence quantification analysis (SRQA) algorithm on a time series of RR intervals. Moreover, we show that the algorithm applies to any biomedical low-cost sensor, achieving good results without requiring any calibration of the raw data acquired. In addition, it has been validated with a well-accepted public electrocardiograph (ECG) data base, obtaining 87.65%, 91.84%, and 91.31% in terms of sensitivity, specificity and accuracy, respectively.

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Chmielewski, Mariusz, Damian Frąszczak, and Dawid Bugajewski. "Architectural concepts for managing biomedical sensor data utilised for medical diagnosis and patient remote care." MATEC Web of Conferences 210 (2018): 05016. http://dx.doi.org/10.1051/matecconf/201821005016.

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This paper discusses experiences and architectural concepts developed and tested aimed at acquisition and processing of biomedical data in large scale system for elderly (patients) monitoring. Major assumptions for the research included utilisation of wearable and mobile technologies, supporting maximum number of inertial and biomedical data to support decision algorithms. Although medical diagnostics and decision algorithms have not been the main aim of the research, this preliminary phase was crucial to test capabilities of existing off-the-shelf technologies and functional responsibilities of system’s logic components. Architecture variants contained several schemes for data processing moving the responsibility for signal feature extraction, data classification and pattern recognition from wearable to mobile up to server facilities. Analysis of transmission and processing delays provided architecture variants pros and cons but most of all knowledge about applicability in medical, military and fitness domains. To evaluate and construct architecture, a set of alternative technology stacks and quantitative measures has been defined. The major architecture characteristics (high availability, scalability, reliability) have been defined imposing asynchronous processing of sensor data, efficient data representation, iterative reporting, event-driven processing, restricting pulling operations. Sensor data processing persist the original data on handhelds but is mainly aimed at extracting chosen set of signal features calculated for specific time windows – varying for analysed signals and the sensor data acquisition rates. Long term monitoring of patients requires also development of mechanisms, which probe the patient and in case of detecting anomalies or drastic characteristic changes tune the data acquisition process. This paper describes experiences connected with design of scalable decision support tool and evaluation techniques for architectural concepts implemented within the mobile and server software.

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Chen, Ling. "Construction and Signal Feature Processing of Gold Nanobiosensors Based on the Internet of Things." Journal of Healthcare Engineering 2022 (January 10, 2022): 1–7. http://dx.doi.org/10.1155/2022/1432266.

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With the continuous development of signal amplification technology and nanotechnology, more and more electrochemical sensors combining nanotechnology and signal amplification technology are applied in the field of analysis. In this paper, combined with the Internet of Things technology, the construction of gold nanobiosensors and signal characteristic processing are carried out. In this paper, a T-rich DNA probe is used as the recognition element, modified on the electrode surface, combined with DNA-modified nanogold particle amplification technology, and the electroactive substance peg amine is used as the signal molecule to develop a highly sensitive electrochemical biosensor for the detection of melamine. The sensor has good specificity and sensitivity, and the detection limit is as low as 0.5 NM. In addition, by combining sensors with the Internet of Things technology, melamine monitoring and signal characteristic processing can be carried out in real time. This model can easily achieve the purpose of accurate and quantitative analysis of melamine toxins and can be effective for food safety.

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Omar, Nur, Yap Fen, Silvan Saleviter, Wan Daniyal, Nur Anas, Nur Ramdzan, and Mohammad Roshidi. "Development of a Graphene-Based Surface Plasmon Resonance Optical Sensor Chip for Potential Biomedical Application." Materials 12, no. 12 (June 14, 2019): 1928. http://dx.doi.org/10.3390/ma12121928.

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The emergence of unintentional poisoning and uncontrolled vector diseases have contributed to sensor technologies development, leading to the more effective detection of diseases. In this study, we present the combination of graphene-based material with surface plasmon resonance technique. Two different graphene-based material sensor chips were prepared for rapid and quantitative detection of dengue virus (DENV) and cobalt ion (Co2+) as an example of typical metal ions. As the fundamental concept of surface plasmon resonance (SPR) sensor that relies on the refractive index of the sensor chip surface, this research focused on the SPR signal when the DENV and Co2+ interact with the graphene-based material sensor chip. The results demonstrated that the proposed sensor-based graphene layer was able to detect DENV and Co2+ as low as 0.1 pM and 0.1 ppm respectively. Further details in the detection and quantification of analyte were also discussed in terms of sensitivity, affinity, and selectivity of the sensor.

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Böhm, Anna, Christoph Brüser, and Steffen Leonhardt Leonhardt. "A NOVEL BCG SENSOR-ARRAY FOR UNOBTRUSIVE CARDIAC MONITORING." Acta Polytechnica 53, no. 6 (December 31, 2013): 862–67. http://dx.doi.org/10.14311/ap.2013.53.0862.

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Unobtrusive heart rate monitoring is a popular research topic in biomedical engineering. The reason is that convential methods, e.g. the clinical gold standard electrocardiography, require conductive contact to the human body. Other methods such as ballistocardiography try to record these vital signs without electrodes that are attached to the body. So far, these systems cannot replace routine procedures. Most systems have some drawbacks that cannot be compensated, such as aging of the sensor materials or movement artifacts. In addition, the signal form differs greatly from an ECG, which is an electrical signal. The ballistocardiogram has a mechanical source, which makes it harder to evaluate. We have developed a new sensor array made of near-IR-LEDs to record BCGs. IR-sensors do not age in relevant time scales. Analog filtering was neccesary, because the signal amplitude was very small. The digitized data was then processed by various algorithms to extract beat-to-beat or breath-to-breath intervals. The redundancy of multiple BCG channels was used to provide a robust estimation of beat-to-beat intervals and heart rate. We installed the system beneath a mattress topper of a hospital bed, but any other bed would have been sufficient. The validation of this measurement system shows that it is well suited for BCG recordings. The use of multiple channels has proven to be superior to relying on a single BCG channel.

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Iwe, Idorenyin, and Zhigang Li. "An isothermal, non-enzymatic, and dual-amplified fluorescent sensor for highly sensitive DNA detection." Reviews in Analytical Chemistry 40, no. 1 (January 1, 2021): 312–22. http://dx.doi.org/10.1515/revac-2021-0140.

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Abstract Sensitive DNA assays are of importance in life science and biomedical engineering, but they are heavily dependent on thermal cycling programs or enzyme-assisted schemes, which require the utilization of bulky devices and costly reagents. To circumvent such requirements, we developed an isothermal enzyme-free DNA sensing method with dual-stage signal amplification ability based on the coupling use of catalytic hairpin assembly (CHA) and Mg2+-dependent deoxyribozyme (DNAzyme). In this study, the sensing system involves a set of hairpin DNA probes for CHA (ensuring the first stage of signal amplification) as well as ribonucleobase-modified molecular beacons that serve as activatable substrates for DNAzymes (warranting the second stage of signal amplification). An experimentally determined detection limit of about 0.5 pM is achieved with a good linear range from 0.5 to 10 pM. The results from spiked fetal bovine serum samples further confirm the reliability for practical applications. The non-thermal cycling, enzyme-free, and dual-amplified features make it a powerful sensing tool for effective nucleic acid assay in a variety of biomedical applications.

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Kim, SungJoon, Sri Ramulu Torati, Artem Talantsev, ChangYeop Jeon, SungBae Lee, and CheolGi Kim. "Performance Validation of a Planar Hall Resistance Biosensor through Beta-Amyloid Biomarker." Sensors 20, no. 2 (January 13, 2020): 434. http://dx.doi.org/10.3390/s20020434.

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Magnetic sensors have great potential for biomedical applications, particularly, detection of magnetically-labeled biomolecules and cells. On the basis of the advantage of the planar Hall effect sensor, which consists of improved thermal stability as compared with other magnetic sensors, we have designed a portable biosensor platform that can detect magnetic labels without applying any external magnetic field. The trilayer sensor, with a composition of Ta (5 nm)/NiFe (10 nm)/Cu (x = 0 nm~1.2 nm)/IrMn (10 nm)/Ta (5 nm), was deposited on a silicon wafer using photolithography and a sputtering system, where the optimized sensor sensitivity was 6 μV/(Oe∙mA). The detection of the magnetic label was done by comparing the signals obtained in first harmonic AC mode (1f mode) using an external magnetic field and in the second harmonic AC mode (2f mode) with a self-field generated by current passing through the sensor. In addition, a technique for the β-amyloid biomarker-based antibody-antigen sandwich model was demonstrated for the detection of a series of concentrations of magnetic labels using the self-field mode method, where the signal-to-noise ratio (SNR) was high. The generated self-field was enough to detect an immobilized magnetic tag without an additional external magnetic field. Hence, it could be possible to reduce the device size to use the point-of-care testing using a portable circuit system.

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Wu, Yu Tzu, Matheus K. Gomes, Willian HA da Silva, Pedro M. Lazari, and Eric Fujiwara. "Integrated Optical Fiber Force Myography Sensor as Pervasive Predictor of Hand Postures." Biomedical Engineering and Computational Biology 11 (January 2020): 117959722091282. http://dx.doi.org/10.1177/1179597220912825.

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Force myography (FMG) is an appealing alternative to traditional electromyography in biomedical applications, mainly due to its simpler signal pattern and immunity to electrical interference. Most FMG sensors, however, send data to a computer for further processing, which reduces the user mobility and, thus, the chances for practical application. In this sense, this work proposes to remodel a typical optical fiber FMG sensor with smaller portable components. Moreover, all data acquisition and processing routines were migrated to a Raspberry Pi 3 Model B microprocessor, ensuring the comfort of use and portability. The sensor was successfully demonstrated for 2 input channels and 9 postures classification with an average precision and accuracy of ~99.5% and ~99.8%, respectively, using a feedforward artificial neural network of 2 hidden layers and a competitive output layer.

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Frisk, Megan L., Erwin Berthier, William H. Tepp, Eric A. Johnson, and David J. Beebe. "Bead-based microfluidic toxin sensor integrating evaporative signal amplification." Lab on a Chip 8, no. 11 (2008): 1793. http://dx.doi.org/10.1039/b811075a.

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Zamora-Mejia, Gregorio, Jaime Martinez-Castillo, Alejandro Diaz-Sanchez, Jose M. Rocha-Perez, Agustín L. Herrera-May, Uriel G. Zapata-Rodriguez, and Victor H. Carbajal-Gomez. "A Self-Powered UHF Passive Tag for Biomedical Temperature Monitoring." Electronics 11, no. 7 (March 31, 2022): 1108. http://dx.doi.org/10.3390/electronics11071108.

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Self-powered RF passive sensors have potential application in temperature measurements of patients with health problems. Herein, this work presents the design and implementation of a self-powered UHF passive tag prototype for biomedical temperature monitoring. The proposed battery-free sensor is composed of three basic building blocks: a high-frequency section, a micro-power management stage, and a temperature sensor. This passive temperature sensor uses an 860 MHz to 960 MHz RF carrier and a 1 W Effective Isotropic Radiated Power (EIRP) to harvest energy for its operation, showing a read range of 9.5 m with a 13.75 µW power consumption, and an overall power consumption efficiency of 10.92% was achieved. The proposed device can measure temperature variations between 0 °C and 60 °C with a sensitivity of 823.29 Hz/°C and a standard error of 13.67 Hz/°C over linear regression. Circuit functionality was validated by means of post-layout simulations, characterization, and measurements of the manufactured prototype. The chip prototype was fabricated using a 0.18 µm CMOS standard technology with a silicon area consumption of 1065 µm × 560 µm. The overall size of the self-powered passive tag is 8 cm × 2 cm, including both chip and antenna. The self-powered tag prototype could be employed for human body temperature monitoring.

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Li, Shancang, Li Da Xu, and Xinheng Wang. "A Continuous Biomedical Signal Acquisition System Based on Compressed Sensing in Body Sensor Networks." IEEE Transactions on Industrial Informatics 9, no. 3 (August 2013): 1764–71. http://dx.doi.org/10.1109/tii.2013.2245334.

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Osmers, Jan, Michael Sorg, and Andreas Fischer. "Optical measurement of the corneal oscillation for the determination of the intraocular pressure." Biomedical Engineering / Biomedizinische Technik 64, no. 4 (August 27, 2019): 471–80. http://dx.doi.org/10.1515/bmt-2018-0093.

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Abstract Motivation Glaucoma is currently the most common irreversible cause of blindness worldwide. A significant risk factor is an individually increased intraocular pressure (IOP). A precise measurement method is needed to determine the IOP in order to support the diagnosis of the disease and to monitor the outcome of the IOP reduction as a medical intervention. A handheld device is under development with which the patient can perform self-measurements outside the clinical environment. Method For the measurement principle of the self-tonometer the eye is acoustically excited to oscillate, which is analyzed and attributed to the present IOP. In order to detect the corneal oscillation, an optical sensor is required which meets the demands of a compact, battery driven self-tonometer. A combination of an infrared diode and a phototransistor provides a high-resolution measurement of the corneal oscillation in the range of 10 μm–150 μm, which is compared to a reference sensor in the context of this study. By means of an angular arrangement of the emitter and the detector, the degree of reflected radiation of the cornea can be increased, allowing a measurement with a high signal-to-noise ratio. Results By adjusting the angle of incidence between the detector and the emitter, the signal-to-noise ratio was improved by 40 dB which now allows reasonable measurements of the corneal oscillation. For low amplitudes (10 μm) the signal-to-noise ratio is 10% higher than that of the commercial reference sensor. On the basis of amplitude variations at different IOP levels, the estimated standard uncertainty amounts to <0.5 mm Hg in the physiological pressure range with the proposed measuring approach. Conclusion With a compact and cost-effective approach, that suits the requirements for a handheld self-tonometer, the corneal oscillation can be detected with high temporal resolution. The cross-sensitivity of the sensor concept concerning a distance variation can be reduced by adding a distance sensor. Existing systematic influences of corneal biomechanics will be integrated in the sensor concept as a consecutive step.

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KARTHIKEYAN, P., M. MURUGAPPAN, and S. YAACOB. "DETECTION OF HUMAN STRESS USING SHORT-TERM ECG AND HRV SIGNALS." Journal of Mechanics in Medicine and Biology 13, no. 02 (April 2013): 1350038. http://dx.doi.org/10.1142/s0219519413500383.

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This paper introduces a method for resolving the problem of human stress detection through short-term (less than 5 min) electrocardiogram (ECG) and heart rate variability (HRV) signals. The explored methodology helps to improve the stress detection rate and reliability through multiple evidences originated in same sensor. In this work, stress-inducing protocol, data acquisition, preprocessing, feature extraction and classification are the major steps involved to detect the stress. In total, 60 subjects (30 males and 30 females) participated in the Stroop color word-based stress-inducing task and ECG signal was acquired simultaneously. The wavelet denoising algorithm was applied to remove high frequency, baseline wander and power line noises. Discrete wavelet transform (DWT)-based heart rate (HR) detection algorithm is used for deriving HRV signal from the preprocessed ECG signal. The ectopic beat removal method is employed to eliminate the ectopic beat and noise peaks in the HRV signal. In order to detect the stress, the issue of uneven sampling with the HRV signal has been successfully rectified using the Lomb-Scargle periodogram (LSP). The application of LSP in short-term HRV signals (32 s), uneven sampling issue, and power spectral information issue has been rectified and the trustworthiness of the short-term HRV signal has been proved by hypothesis as well as experimental results. Theoretical analysis suggested that a minimum 25 s of online or offline ECG data is required to analyze the autonomous nervous system (ANS) activity related to stress. In addition to the HRV signal, ECG-based stress assessment has been proposed to detect the stress through optimum features using fast Fourier transform (FFT). Various features extracted from the ECG and HRV signal have been classified into normal and stress using PNN and kNN classifiers with different smoothing factor and k values. The experimental results indicate that the proposed methodology for short-term ECG and HRV signal can achieve the overall average classification accuracy of 91.66% and 94.66% in the subject-independent mode.

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Tiboni, Monica, Azzurra Filippini, Cinzia Amici, and David Vetturi. "Test-Bench for the Characterization of Flexion Sensors Used in Biomechanics." Electronics 10, no. 23 (December 1, 2021): 2994. http://dx.doi.org/10.3390/electronics10232994.

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The design, prototyping and validation of an innovative test bench for the characterization and the hysteresis measurement of flexion sensors are presented in this paper. The device, especially designed to test sensors employed in the biomedical field, can be effectively used to characterize also sensors intended for other applications, such as wearable devices. Flexion sensors are widely adopted in devices for biomedical purposes and in this context are commonly used in two main ways: to measure movements (i) with fixed radius of curvature and (ii) with variable radius of curvature. The test bench has been conceived and designed with reference to both of these needs of use. The technological choices have been oriented towards simplicity of manufacture and assembly, configuration flexibility and low cost of realization. For this purpose, 3D printing technology was chosen for most of the structural components of the device. To verify the test bench performances, a test campaign was carried out on five commercial bending sensors. To characterize each sensor, the acquired measurements were analysed by assessing repeatability and linearity of the sensors and hysteresis of the system sensor/test bench. A statistical analysis was performed to study the positioning repeatability and the hysteresis of the device. The results demonstrate good repeatability and low hysteresis.

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Araujo Cespedes, Fabiola, Gokhan Mumcu, and Stephen E. Saddow. "SiC RF Sensor for Continuous Glucose Monitoring." MRS Advances 1, no. 55 (2016): 3691–96. http://dx.doi.org/10.1557/adv.2016.400.

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ABSTRACTIt has been shown that changes in blood glucose can be sensed with an RF antenna made from silicon carbide (SiC) operating at 10 GHz. Therefore a SiC antenna patch could operate as an active sensor or as a passive sensor at 5.8 GHz for a continuous glucose monitoring system. The properties of SiC make this material ideal for biomedical applications and devices as it is not only biocompatible but also has great sensing capability. The permittivity and conductivity of the blood is glucose dependent. Thus implanting the antenna in the fatty tissue facing the muscle and blood results should result in a shift of the resonant frequency of the antenna with glucose levels. In the active sensor approach, a power supply and internal in-vivo circuitry with protection would be required. In the passive sensor approach, external circuitry sends a signal to the implanted antenna and is received back again, detecting any signal variations. Simulations in HFSS™ show that that an implanted sensor placed 2 mm from the muscle in fatty tissue would experience an approximate shift in resonant frequency of 12.3 MHz for a blood glucose change of 500 mg/dl.

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Juárez-Aguirre, Raúl, Saúl Domínguez-Nicolás, Elías Manjarrez, Jesús Tapia, Eduard Figueras, Héctor Vázquez-Leal, Luz Aguilera-Cortés, and Agustín Herrera-May. "Digital Signal Processing by Virtual Instrumentation of a MEMS Magnetic Field Sensor for Biomedical Applications." Sensors 13, no. 11 (November 5, 2013): 15068–84. http://dx.doi.org/10.3390/s131115068.

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Huang, Shi-Ing, Long-Cheng Cheng, Show-Hwai Chou, Chii-Wann Lin, Chun Yu, and Tzu-Hsiu Tsai. "SOFT SENSORS FOR MONITORING RESPIRATORY AND HEART SOUND." Biomedical Engineering: Applications, Basis and Communications 21, no. 06 (December 2009): 453–56. http://dx.doi.org/10.4015/s1016237209001635.

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The soft sensors for monitoring respiratory and heart sound were composed of polyurethane and microphones. In this study, silica was blended with polyurethane to change the hardness of the chambers. The hardness would influence the frequency response of the sensors. The material composed of 60 phr silica was chosen to make the chamber of the sensor. It had higher hardness and resulted in the flatten frequency response across the range of 100–1200 Hz. By the filter band designed for heart sound and respiratory sound signal, the heart sound and respiratory sound can be collected. The measured sound was verified by the physician and showed no distortion.

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Pflugradt, Maik, Steffen Mann, Timo Tigges, Matthias Görnig, and Reinhold Orglmeister. "Multi-modal signal acquisition using a synchronized wireless body sensor network in geriatric patients." Biomedical Engineering / Biomedizinische Technik 61, no. 1 (February 1, 2016): 57–68. http://dx.doi.org/10.1515/bmt-2014-0178.

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AbstractWearable home-monitoring devices acquiring various biosignals such as the electrocardiogram, photoplethysmogram, electromyogram, respirational activity and movements have become popular in many fields of research, medical diagnostics and commercial applications. Especially ambulatory settings introduce still unsolved challenges to the development of sensor hardware and smart signal processing approaches. This work gives a detailed insight into a novel wireless body sensor network and addresses critical aspects such as signal quality, synchronicity among multiple devices as well as the system’s overall capabilities and limitations in cardiovascular monitoring. An early sign of typical cardiovascular diseases is often shown by disturbed autonomic regulations such as orthostatic intolerance. In that context, blood pressure measurements play an important role to observe abnormalities like hypo- or hypertensions. Non-invasive and unobtrusive blood pressure monitoring still poses a significant challenge, promoting alternative approaches including pulse wave velocity considerations. In the scope of this work, the presented hardware is applied to demonstrate the continuous extraction of multi modal parameters like pulse arrival time within a preliminary clinical study. A Schellong test to diagnose orthostatic hypotension which is typically based on blood pressure cuff measurements has been conducted, serving as an application that might significantly benefit from novel multi-modal measurement principles. It is further shown that the system’s synchronicity is as precise as 30 μs and that the integrated analog preprocessing circuits and additional accelerometer data provide significant advantages in ambulatory measurement environments.

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Journal articles on the topic 'Biomedical signal sensor'

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