Journal articles on the topic 'Biopotential detection'
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Mahdi, A. E., and L. Faggion. "Non-contact biopotential sensor for remote human detection." Journal of Physics: Conference Series 307 (August 17, 2011): 012056. http://dx.doi.org/10.1088/1742-6596/307/1/012056.
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Noguchi, Yuta, and Akira Kawai. "Surface Stability of SU-8 Film for Accurate Biopotential Detection." Journal of Photopolymer Science and Technology 25, no. 6 (2012): 719–22. http://dx.doi.org/10.2494/photopolymer.25.719.
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Ng, E. Y. K., W. K. Ng, L. S. J. Sim, and U. Rajendra Acharya. "Numerical modelling of biopotential field for detection of breast tumour." Computers in Biology and Medicine 37, no. 8 (August 2007): 1121–32. http://dx.doi.org/10.1016/j.compbiomed.2006.10.006.
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Kareem, Ghada. "DETECTION AND CLASSIFICATION OF ABNORMALITIES OF BIO-POTENTIAL ACTIVITY OF HEART." Journal of Southwest Jiaotong University 57, no. 1 (February 28, 2022): 673–82. http://dx.doi.org/10.35741/issn.0258-2724.57.1.60.
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An electrocardiograph (ECG) is one of the essential equipment used in cardiology department research. It is used for diagnostic patients suffering from heart biopotential activity disorders. The difficulty of ECG classification is solved; the signal of ECG has some noise, so pre-processing is done at first to denoising. The signal is transformed into a small set of features simplifying the classification of the signal and diagnosing the disease. Support vector machine (SVM), K nearest neighbor (KNN), discriminant analysis (DS), random forest (RF), and Naïve Bayes (NB) classifiers are used for the classification of the signals of ECG. The proposed technique is used to detect the abnormal ECG sample and classify it into three different classes: normal sinus rhythm (NSR), arrhythmia (ARR), and congestive heart failure (CHF); it is shown that the accuracy of the technique is 98%, so the classification after feature extraction is better than classification with raw data without feature extraction. The method includes several steps: ECG signal database loading, signal pre-processing, feature extracting using wavelet transform, and displaying the classification results. Our classification and denoising technique uses discrete wavelet transform to support the diagnosis of patients with heart rate disorders, biopotential activity, and myocardial ischemia. This helps early detect heart disorders in a patient suffering from COVID-19.
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Abd-Elbaki, Mohamed K. M., Hanan A. Matar, and Naglaa R. E. Ismaeel. "Preparation and Characterization of Silk Fibroin-PANI Nanocomposites and Their Application for Electrophysiological Signals Recording." American Journal of Agricultural Science, Engineering, and Technology 6, no. 3 (December 3, 2022): 142–49. http://dx.doi.org/10.54536/ajaset.v6i3.1009.
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Wearable dry electrodes are required for long-term biopotential recordings, but their availability is limited. The diagnosis of coronary heart disease is possible with ambulatory electrocardiography (ECG). For ambulatory ECG sensing, on-skin electrodes are used by conformably contacting the skin’s moving and arbitrary formed surface. However, the low skin-adhesion of electrodes restricts their use in ambulatory ECG sensing for an extended period of time. Here, it was possible to create extremely skin-adhesive and washable on-skin electrodes by developing a new composite of Poly aniline (PANI) and silk fibroin (SF). Self-adhesive property of silk fibroin - PANI electrodes was achieved by coating with silk/Ca2+ adhesive layers. These electrodes were applied to the skin to capture high-quality ECG readings for the detection of cardiac real status in order to show how they can be used to detect precise and dependable signals. Silk fibroin - PANI electrodes showed an excellent performance for ECG signals recording over different physiological states.
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Kataoka, Hiroshi, Tsunenori Takatani, and Kazuma Sugie. "Two-Channel Portable Biopotential Recording System Can Detect REM Sleep Behavioral Disorder: Validation Study with a Comparison of Polysomnography." Parkinson's Disease 2022 (February 24, 2022): 1–5. http://dx.doi.org/10.1155/2022/1888682.
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Background. Sleep disorders are frequent nonmotor symptoms of Parkinson’s disease (PD). Polysomnography (PSG) has been the gold standard for its assessment. However, it requires patients to stay overnight in a hospital or sleep center. The mobile two-channel electroencephalography (EEG)/electrooculography (EOG) recording system is a self-applicable and affordable method to objectively assess sleep at home. We aimed at evaluating patients with PD to confirm the difference in sleep parameters between the portable recording system and PSG. Methods. PSG and the portable recording system were simultaneously performed on a similar night in eight patients with PD. We compared the difference in sleep parameters between them using nonparametric tests. Results. All patients displayed a score of both PDSS −2 ≥ 15 and PSQI ≥ 5, respectively, which revealed poor sleep quality. There was no difference in the sleep parameters between the portable recording system and PSG, except for the percentage of sleep stage N3. Regarding the detection of REM sleep without atonia, we observed accordance between the portable recording system and PSG in six patients ( P = 0.686 ). Conclusions. The portable EEG/EOG recording system may gain an advantage from home-based evaluations for habitual sleep at home. Our study on device validation may contribute to measuring natural sleep, including rapid eye movement (REM) sleep behavioral disorder (RBD), in an outpatient care setting.
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Golparvar, Ata Jedari, and Murat Kaya Yapici. "Toward graphene textiles in wearable eye tracking systems for human–machine interaction." Beilstein Journal of Nanotechnology 12 (February 11, 2021): 180–89. http://dx.doi.org/10.3762/bjnano.12.14.
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The study of eye movements and the measurement of the resulting biopotential, referred to as electrooculography (EOG), may find increasing use in applications within the domain of activity recognition, context awareness, mobile human–computer and human–machine interaction (HCI/HMI), and personal medical devices; provided that, seamless sensing of eye activity and processing thereof is achieved by a truly wearable, low-cost, and accessible technology. The present study demonstrates an alternative to the bulky and expensive camera-based eye tracking systems and reports the development of a graphene textile-based personal assistive device for the first time. This self-contained wearable prototype comprises a headband with soft graphene textile electrodes that overcome the limitations of conventional “wet” electrodes, along with miniaturized, portable readout electronics with real-time signal processing capability that can stream data to a remote device over Bluetooth. The potential of graphene textiles in wearable eye tracking and eye-operated remote object interaction is demonstrated by controlling a mouse cursor on screen for typing with a virtual keyboard and enabling navigation of a four-wheeled robot in a maze, all utilizing five different eye motions initiated with a single channel EOG acquisition. Typing speeds of up to six characters per minute without prediction algorithms and guidance of the robot in a maze with four 180° turns were successfully achieved with perfect pattern detection accuracies of 100% and 98%, respectively.
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Donisi, Leandro, Giuseppe Cesarelli, Noemi Pisani, Alfonso Maria Ponsiglione, Carlo Ricciardi, and Edda Capodaglio. "Wearable Sensors and Artificial Intelligence for Physical Ergonomics: A Systematic Review of Literature." Diagnostics 12, no. 12 (December 5, 2022): 3048. http://dx.doi.org/10.3390/diagnostics12123048.
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Physical ergonomics has established itself as a valid strategy for monitoring potential disorders related, for example, to working activities. Recently, in the field of physical ergonomics, several studies have also shown potential for improvement in experimental methods of ergonomic analysis, through the combined use of artificial intelligence, and wearable sensors. In this regard, this review intends to provide a first account of the investigations carried out using these combined methods, considering the period up to 2021. The method that combines the information obtained on the worker through physical sensors (IMU, accelerometer, gyroscope, etc.) or biopotential sensors (EMG, EEG, EKG/ECG), with the analysis through artificial intelligence systems (machine learning or deep learning), offers interesting perspectives from both diagnostic, prognostic, and preventive points of view. In particular, the signals, obtained from wearable sensors for the recognition and categorization of the postural and biomechanical load of the worker, can be processed to formulate interesting algorithms for applications in the preventive field (especially with respect to musculoskeletal disorders), and with high statistical power. For Ergonomics, but also for Occupational Medicine, these applications improve the knowledge of the limits of the human organism, helping in the definition of sustainability thresholds, and in the ergonomic design of environments, tools, and work organization. The growth prospects for this research area are the refinement of the procedures for the detection and processing of signals; the expansion of the study to assisted working methods (assistive robots, exoskeletons), and to categories of workers suffering from pathologies or disabilities; as well as the development of risk assessment systems that exceed those currently used in ergonomics in precision and agility.
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Cao, Tianao, Dan Liu, Qisong Wang, Ou Bai, and Jinwei Sun. "Surface Electromyography-Based Action Recognition and Manipulator Control." Applied Sciences 10, no. 17 (August 22, 2020): 5823. http://dx.doi.org/10.3390/app10175823.
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To improve the quality of lives of disabled people, the application of intelligent prosthesis was presented and investigated. In particular, surface Electromyography (sEMG) signals succeeded in controlling the manipulator in human–machine interface, due to the fact that EMG activity belongs to one of the most widely utilized biosignals and can reflect the straightforward motion intention of humans. However, the accuracy of real-time action recognition is usually low and there is usually obvious delay in a controlling manipulator, as a result of which the task of tracking human movement precisely, cannot be guaranteed. Therefore, this study proposes a method of action recognition and manipulator control. We built a multifunctional sEMG detection and action recognition system that integrated all discrete components. A biopotential measurement analog-to-digital converter with a high signal–noise rate (SNR) was chosen to ensure the high quality of the acquired sEMG signals. The acquired data were divided into sliding windows for processing in a shorter time. Mean Absolute Value (MAV), Waveform Length (WL), and Root Mean Square (RMS) were finally extracted and we found that compared to the Genetic-Algorithm-based Support Vector Machine (GA–SVM), the back propagation (BP) neural network performed better in joint action classification. The results showed that the average accuracy of judging the 5 actions (fist clenching, hand opening, wrist flexion, wrist extension, and calling me) was up to 93.2% and the response time was within 200 ms, which achieved a simultaneous control of the manipulator. Our work took into account the action recognition accuracy and real-time performance, and realized the sEMG-based manipulator control eventually, which made it easier for people with arm disabilities to communicate better with the outside world.
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Vajravelu, Ashok, Muhammad Mahadi Bin Abdul Jamil, Mohd Helmy Bin Abd Wahab, Wan Suhaimizan Bin Wan Zaki, Vibin Mammen Vinod, Karthik Ramasamy Palanisamy, and Gousineyah Nageswara Rao. "Nanocomposite-Based Electrode Structures for EEG Signal Acquisition." Crystals 12, no. 11 (October 27, 2022): 1526. http://dx.doi.org/10.3390/cryst12111526.
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Objective: To fabricate a lightweight, breathable, comfortable, and able to contour to the curvilinear body shape, electrodes built on a flexible substrate are a significant growth in wearable health monitoring. This research aims to create a GNP/FE electrode-based EEG signal acquisition system that is both efficient and inexpensive. Methodology: Three distinct electrode concentrations were developed for EEG signal acquisition, three distinct electrode concentrations (1.5:1.5, 2:1, and 3:0). The high strength-to-weight ratio to form the tribofilm in the fabrication of the electrode will provide good efficiency. The EEG signal is first subjected to a wavelet transform, which serves as a preliminary analysis. The use of biopotential signals in wearable systems as biofeedback or control commands is expected to substantially impact point-of-care health monitoring systems, rehabilitation devices, human–computer/machine interfaces (HCI/HMI), and brain–computer interfaces (BCIs). The graphene oxide (GO), glycerol (GL), and polyvinyl alcohol (PVA) GO/GL/PVA plastic electrodes were measured and compared to that of a commercially available electrode using the biopic equipment. The GO/GL/PVA plastic electrode was able to detect EEG signals satisfactorily after being used for two months, demonstrating good conductivity and lower noise than the commercial electrode. The GO/GL/PVA nanocomposite mixture was put into the electrode mold as soon as it was ready and then rapidly chilled. Results: The quality of an acquired EEG signal could be measured in several ways including by its error percentage, correlation coefficient, and signal-to-noise ratio (SNR). The fabricated electrode yield detection ranged from 0.81 kPa−1 % to 34.90 kPa−1%. The performance was estimated up to the response of 54 ms. Linear heating at the rate of 40 °C per minute was implemented on the sample ranges from 0 °C to 240 °C. During the sample electrode testing in EEG signal analysis, it obtained low impedance with a good quality of signal acquisition when compared to a conventional wet type of electrode. Conclusions: A large database was frequently built from all of the simulated signals in MATLAB code. Through the experiment, all of the required data were collected, checked against all other signals, and proven that they were accurate representations of the intended database. Evidence suggests that graphene nanoplatelets (GNP) hematite (FE2O3) polyvinylidene fluoride (PVDF) GNP/FE2O3@PVDF electrodes with a 3:0 concentration yielded the best outcomes.
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Varela-Benítez, J. L., J. O. Rivera-Delgado, J. H. Espina-Hernández, and J. M. de la Rosa-Vázquez. "Capacitive electrode with high sensitivity for detection of electrical biopotentials." Revista Mexicana de Ingeniería Biomédica 36, no. 2 (May 2015): 131–42. http://dx.doi.org/10.17488/rmib.36.2.1.
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Varela, JL, JO Rivera, JH Espina, and JM de la Rosa. "Capacitive electrode with high sensitivity for detection of electrical biopotentials." Revista Mexicana de Ingeniería Biomédica 36, no. 2 (May 29, 2015): 131–42. http://dx.doi.org/10.17488/rmib.36.2.1pdf.
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Takano, Akira, Hiroshi Ishigami, and Akinori Ueno. "Non-Contact Measurements of Electrocardiogram and Cough-Associated Electromyogram from the Neck Using In-Pillow Common Cloth Electrodes: A Proof-of-Concept Study." Sensors 21, no. 3 (January 26, 2021): 812. http://dx.doi.org/10.3390/s21030812.
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Asthma and chronic obstructive pulmonary disease are associated with nocturnal cough and changes in heart rate. In this work, the authors propose a proof-of-concept non-contact system for performing capacitive electrocardiogram (cECG) and cough-associated capacitive electromyogram (cEMG) measurements using cloth electrodes under a pillowcase. Two electrodes were located along with the approximate vector of lead II ECG and were used for both cECG and cEMG measurements. A signature voltage follower was introduced after each electrode to detect biopotentials with amplitudes of approximately 100 µV. A bootstrapping technique and nonlinear electrical component were combined and implemented in the voltage follower to attain a high input impedance and rapid static discharge. The measurement system was evaluated in a laboratory experiment for seven adult males and one female (average age: 22.5 ± 1.3 yr). The accuracy of R-wave detection for 2-min resting periods was 100% in six subjects, with an overall average of 87.5% ± 30.0%. Clearly visible cEMGs were obtained for each cough motion for all subjects, synchronized with reference EMGs from submental muscle. Although there remains room for improvement in practical use, the proposed system is promising for unobtrusive detection of heart rate and cough over a prolonged period of time.
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Krivonogova, Olga Vyacheslavovna, Elena Vyacheslavovna Krivonogova, and Liliya Vladimirovna Poskotinova. "THE CORRELATION BETWEEN INDIVIDUAL MINUTE DATA AND THE Р300 AUDITORY EVOKED POTENTIAL IN YOUNG PEOPLE WITH DIFFERENT LEVELS OF INTERNET ADDICTION BEHAVIOR." Психология. Психофизиология 13, no. 3 (October 21, 2020): 93–101. http://dx.doi.org/10.14529/jpps200310.
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Background. The nature of changes in cerebral biopotentials as a neurobiological foundation of individual time in persons with different levels of internet addiction behavior remains insufficiently studied. However, these biopotentials reflect decision making speed and the quality of significant stimulus detection by brain structures. The paper aims to establish the correlation between the P300 cognitive evoked potential and individual minute (IM) test in young people with different levels of Internet addiction (IA) risk. Materials and methods. Healthy young people aged 16-17 years (n = 51) participated in the study. The survey was conducted according to the Chen scale (CIAS – Chen Internet Addiction Scale) modified by V. Malygin. This modification implies the calculation of the CIAS total score and the subjective assessment of time intervals by the IM test. The amplitude and latency of the P 300 auditory evoked potential were determined using the Neuron-Spectrum - 4 /VMP electroencephalograph (Neurosoft, Russia) in the frontal (F3, F4), temporal (F7, F8, T3, T4), central (C3, C4) and parietal (P3, P4) leads of the electroencephalogram. Results. No significant correlations were found between the IM time, P 300 data and the severity of IA signs in young people with a minimal risk of IA (less than 43 scores by CIAS). There was a decrease in the IM time and an increase in P300 amplitude (mainly in the frontal and anterior temporal areas) in persons with a risk of IA (43–65 scores by CIAS). In persons with a stable IA pattern (more than 65 scores by CIAS), the minimum P 300 amplitude in the F7, F8 brain areas was found against a relative increase in the IM time and the number of errors in decision making. Conclusion. An increased risk of Internet addiction behavior in young people is accompanied by phase changes in the ratios of P 300 amplitude (mainly in the anterior temporal areas), the quality of information processing and individual time perception.
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Angelucci, Alessandra, Matteo Cavicchioli, Ilaria A. Cintorrino, Giuseppe Lauricella, Chiara Rossi, Sara Strati, and Andrea Aliverti. "Smart Textiles and Sensorized Garments for Physiological Monitoring: A Review of Available Solutions and Techniques." Sensors 21, no. 3 (January 26, 2021): 814. http://dx.doi.org/10.3390/s21030814.
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Several wearable devices for physiological and activity monitoring are found on the market, but most of them only allow spot measurements. However, the continuous detection of physiological parameters without any constriction in time or space would be useful in several fields such as healthcare, fitness, and work. This can be achieved with the application of textile technologies for sensorized garments, where the sensors are completely embedded in the fabric. The complete integration of sensors in the fabric leads to several manufacturing techniques that allow dealing with both the technological challenges entailed by the physiological parameters under investigation, and the basic requirements of a garment such as perspiration, washability, and comfort. This review is intended to provide a detailed description of the textile technologies in terms of materials and manufacturing processes employed in the production of sensorized fabrics. The focus is pointed at the technical challenges and the advanced solutions introduced with respect to conventional sensors for recording different physiological parameters, and some interesting textile implementations for the acquisition of biopotentials, respiratory parameters, temperature and sweat are proposed. In the last section, an overview of the main garments on the market is depicted, also exploring some relevant projects under development.
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Mustafa, Yasser Fakri, Moath Kahtan Bashir, Mahmood Khudhayer Oglah, Raghad Riyadh Khalil, and Eman Tareq Mohammed. "Bioactivity of Some Natural and Semisynthetic Coumarin Derived Compounds." NeuroQuantology 19, no. 6 (July 14, 2021): 129–38. http://dx.doi.org/10.14704/nq.2021.19.6.nq21078.
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A couple of natural coumarins was identified in the seeds of two apples’ cultivars commonly known as Granny Smith and Red Delicious. The effect of the phenolic hydroxyl moieties found in these products was evaluated on the bioactivity. This evaluation included the structural alteration of these moieties into less hydrophilic ones to explore the significance of the parent moieties on the biological activity. The investigated biopotentials were antioxidant, antiproliferative, antibacterial, and antifungal effects. The antioxidant potential was investigated by detecting the ability of the natural and semisynthetic coumarins to trap the free hydroxyl and DPPH radicals. The antiproliferative potential was assessed via an MTT-depended assay versus eight cancerous-cell lines, included HeLa, SK-OV-3, AR42J, MCF-7, AB12, KYSE-30, LC540, and AMN3. The antibacterial potential was tested versus six common pathogenic bacterial strains via a well-defined disc diffusion assay. These pathogens were Escherichia coli, Salmonella typhi, Klebsiella pneumonia, Haemophilus influenzae, Shigella dysenteriae, and Pseudomonas aeruginosa. The antifungal potential was also screened by utilizing a similar microbiological technique versus three pathogenic fungi, involved Candida albicans, Aspergillus flavus, and Aspergillus niger. It is concluded that the investigated chemical moiety has a positive influence on the antioxidant and antiproliferative potentials of the natural derivatives, and a negative one on their antibacterial and antifungal potentials.
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Homayounfar, S. Zohreh, Ali Kiaghadi, Deepak Ganesan, and Trisha L. Andrew. "(Digital Presentation) Harnessing Wide-Range, Highly Stable Pressure Sensitivity Via PEDOT-Cl Vapor Printed Textiles for Health Monitoring." ECS Meeting Abstracts MA2022-02, no. 62 (October 9, 2022): 2286. http://dx.doi.org/10.1149/ma2022-02622286mtgabs.
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The advancement of wearable electromechanical sensors to detect biopotentials and body locomotion is critically important in evaluating human performance and improving off-site care applications. Electromechanical pressure sensors are defined as transducers that transform the mechanical deformations caused by applied pressure to a detectable electrical output. Depending on the transduction mechanism, pressure sensors fall within different categories including triboelectric, transistive, capacitive, piezoelectric, and piezoresistive sensors. Piezoresistive pressure sensors, in which the ultimate electrical output is resistance variations, are the most-widely used class due to the simplicity of read-out system in signal acquisition, simple working mechanism that allows a wide variety of materials to be used along with cost-effective fabrication process. However, their practicality is highly restricted by narrow range of detection (RoD), failure to sense both static and dynamic pressures simultaneously, and low stability against aging phenomena such as cycling abrasions, exposure to perspiration and washing. By taking advantage of vapor deposition of a p-doped conjugated polymer, poly(3,4-ethylenedioxythiophene):chloride (PEDOT-Cl), we introduce an ultra-stable pressure sensor that reveals high sensitivity in detecting real-time signals in such a wide range of pressures that has not been reported before (from heart beats to more than body weight). This one-step technique allowed us to tune the conductivity and subsequently sensitivity of the sensor accordingly. We observed that the sensor enjoys a multiscale working mechanism, in which we have the putative decrease in the thickness and therefore reduction in the air trapped in the free volume of the active layer in mili-centmeter scale, the percolation pathways in micro-milimeter scale, and piezoionic effect in nanometer scale which means that the redistribution of ions under the applied mechanical stress leads to the change in resistance. This multiscale sensitivity is the key to its broad RoD along with its ability to simultaneously detect subtle dynamic and static pressure in the presence of a base pressure. We developed two sensors: one with PEDOT-Cl coated cotton fabric and one with PEDOT-Cl coated cotton ball as the active layer. In fact, the ordered structure of fabric and the disordered structure of cotton ball play the role of a lattice for percolation; providing the structure with points of connectivity for charge carriers. As expected, the disordered nature of the cotton ball leads to a higher number of points of connectivity and therefore, lower range of variation and higher precision in data acquisition. While taking advantage of the presence of ions in our sensor, we protected the sensor against all the humidity-induced degradations entangled with ions and other aging processes via vapor deposition of Fluorinated hydrophobic moieties on all the sensor layers. With this protective coating, the sensor shows less than no change in resistance and sensitivity after staying in ~100% humidity for more than a week, and can stand more than 20 laundry cycles without any drop in signal quality. Also, it displays ultrastability with 99.21% over 70,000 bending cycles in ambient conditions, exceeding the durability cycles of sensors reported previously. The broad ability of this sensor was further confirmed by acquiring physiological signals and body motions such as heartbeats, respiration, Joint movements and step. All these properties, along with the low-cost and robust fabrication process, bears the testimony that this sensor will be uniquely placed in wearable health monitoring electronics for both diagnostic and treatment applications. *Figure Caption: a) Schematic illustration of the sensor including the SEM image of the PEDOT-Cl coated layer, b) Physiological and body movements signals acquired via sensor, c) Sensitivity of the sensor over a wide range of pressures Figure 1
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Tiwari, Rudraksh, and Vinod Kuumar Kushwah. "STUDY THE BIOPOTENTIAL PARAMETER FOR DETECTION OF SEISMIC AND ENVIORNMENTAL CHANGES IN INDIAN REGION." Journal of Geography and Cartography 4, no. 2 (September 30, 2021). http://dx.doi.org/10.24294/jgc.v1i3.765.
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The changes in the magnetic flux generated (electric, magnetic and electromagnetic waves) on the surface of earth due to sudden changes is a matter of discussion. These emissions occur along the fault line generated due to geological and tectonic processes. When sudden changes occur in the environment due to seismic and atmospheric variations, these sensing was observed by creatures and human bodies because the animals and trees adopt the abnormal signals and change the behavior. We have analyzed the changing behavior of recorded signal by live sensors (i.e. banyan tree). So we use the deep rooted and long age’s banyan tree. Banyan tree (long ages) in which root has been working as a live sensor and record the geological and environmental changes. We record the low frequency signals which propagated through solar-terrestrial environment affect directly the root system of the banyan tree and changes has been observed by live sensors. Then, VLF signal ma(y propagate to the earth-ionosphere waveguide. We have also analyzed the different parameters of live cells which is inbuilt in latex of the tree, so we record the dielectric parameters of green stem latex and found some parameters i.e., dielectric constant (ε) and dielectric loss (ε’) of various trees to verify these natural hazards and found good correlation. Therefore, we can say by regularly monitoring the bio-potential signal and dielectric properties of banyan tree we can able to find the precursory signature of seismic hazards and environmental changes.
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Schumayer, Sven, Nicolai Simon, Benjamin Sittkus, Sandra Wagner, Volker Bucher, and Torsten Strasser. "Novel Three-Dimensional and Biocompatible Lift-Off Method for Selective Metallization of a Scleral Contact Lens Electrode for Biopotential Detection." Frontiers in Medical Technology 4 (June 10, 2022). http://dx.doi.org/10.3389/fmedt.2022.920384.
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Presbyopia describes the eye's physiological loss of the ability to see close objects clearly. The adaptation to different viewing distances, termed accommodation, is achieved by a change in the curvature of the eye lens induced by the ciliary muscle. A possible approach to correct presbyopia could be to detect the ciliary muscle's neuromuscular signals during accommodation and transfer these signals electronically to a biomimetic, micro-optical system to provide the necessary refractive power. As a preliminary step toward such a described system, a novel three-dimensional and biocompatible lift-off method was developed. In addition, the influence of the distance between the electrically conducting surfaces of the lens on the accommodated signal amplitudes was investigated. Compared to the conventional masking methods, this process has the advantage that three-dimensional surfaces can be masked with biocompatible gelling sugar by utilizing a direct writing process with a dispensing robot. Since gelling sugar can be used at room temperature and is water-soluble, the process presented is suitable for materials that should not be exposed to organic solvents or excessively high temperatures. Apart from investigating the shrinkage behavior of the gelling sugar during the physical vapor deposition (PVD) coating process, this paper also describes the approaches used to partially coat a commercial scleral contact lens with an electrically conductive material. It was shown that gelling sugar withstands the conditions during the PVD processes and a successful lift-off was performed. To investigate the influence of the spacing between the electrically conductive regions of the contact lens on the measured signals, three simplified electrode configurations with different distances were fabricated using a 3D printer. By testing these in an experimental setup, it could be demonstrated that the distance between the conductive surfaces has a significant influence on the amplitude. Regarding the described lift-off process using gelling sugar, it was found that the dispensing flow rate has a direct influence on the line uniformity. Future work should address the influence of the viscosity of the gelling sugar as well as the diameter of the cannula. It is assumed that they are the prevailing limitations for the lateral resolution.
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Baldazzi, Giulia, Eleonora Sulas, Rik Vullings, Monica Urru, Roberto Tumbarello, Luigi Raffo, and Danilo Pani. "Automatic signal quality assessment of raw trans-abdominal biopotential recordings for non-invasive fetal electrocardiography." Frontiers in Bioengineering and Biotechnology 11 (February 27, 2023). http://dx.doi.org/10.3389/fbioe.2023.1059119.
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Introduction: Wearable monitoring systems for non-invasive multi-channel fetal electrocardiography (fECG) can support fetal surveillance and diagnosis during pregnancy, thus enabling prompt treatment. In these embedded systems, power saving is the key to long-term monitoring. In this regard, the computational burden of signal processing methods implemented for the fECG extraction from the multi-channel trans-abdominal recordings plays a non-negligible role. In this work, a supervised machine-learning approach for the automatic selection of the most informative raw abdominal recordings in terms of fECG content, i.e., those potentially leading to good-quality, non-invasive fECG signals from a low number of channels, is presented and evaluated.Methods: For this purpose, several signal quality indexes from the scientific literature were adopted as features to train an ensemble tree classifier, which was asked to perform a binary classification between informative and non-informative abdominal channels. To reduce the dimensionality of the classification problem, and to improve the performance, a feature selection approach was also implemented for the identification of a subset of optimal features. 10336 5-s long signal segments derived from a real dataset of multi-channel trans-abdominal recordings acquired from 55 voluntary pregnant women between the 21st and the 27th week of gestation, with healthy fetuses, were adopted to train and test the classification approach in a stratified 10-time 10-fold cross-validation scheme. Abdominal recordings were firstly pre-processed and then labeled as informative or non-informative, according to the signal-to-noise ratio exhibited by the extracted fECG, thus producing a balanced dataset of bad and good quality abdominal channels.Results and Discussion: Classification performance revealed an accuracy above 86%, and more than 88% of those channels labeled as informative were correctly identified. Furthermore, by applying the proposed method to 50 annotated 24-channel recordings from the NInFEA dataset, a significant improvement was observed in fetal QRS detection when only the channels selected by the proposed approach were considered, compared with the use of all the available channels. As such, our findings support the hypothesis that performing a channel selection by looking directly at the raw abdominal signals, regardless of the fetal presentation, can produce a reliable measurement of fetal heart rate with a lower computational burden.
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Ahmad, Zulkifli, Mohd Najeb Jamaludin, and Abdul Hafidz Omar. "Development of wearable electromyogram for the physical fatigue detection during aerobic activity." MoHE 7, no. 1 (January 29, 2018). http://dx.doi.org/10.15282/mohe.v7i1.225.
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Physical fatigue or muscle fatigue is a common problem that affects people who are vigorously involved in activities that require endurance movements. It becomes more complicated to measure the fatigue level when the dynamic motion of the activity is included. Therefore, this paper aims to develop a wearable device that can be used for monitoring physical fatigue condition during aerobic exercise. A 10-bit analog to digital converter (ADC) micro-controller board was used to process the data sensed by Ag/AgCl electrodes and real-time transmitted to the computer through Bluetooth's technology. The wearable was attached to the knee and connected to the biopotential electrodes for sensing the muscle movement and convert it into the electrical signal. The signal then processed by using the fourth-order Butterworth filter to filter the low-pass filter frequency and eliminate the noise signal. The results reveal that the fatigue level increased gradually based on the rating of perceived exertion (RPE), using 10-point Borg's scale, which is rated by the subject’s feeling. Both muscle's activities in lower limb rise as speed is increased, and it was also observed that the rectus femoris is functioning more than gastrocnemius due to the size of muscle fiber. Furthermore, it was established that the maximum volumetric contraction (MVC) could be used as a reference and indicator for measuring the percentage of contraction in pre-fatigue but not to fatigue induced experiment. However, this wearable device for EMG is promising to measure the muscle signal in the dynamic motion of movement. Consequently, this device is beneficial for a coach to monitor their athlete's level of exhaustion to be not over-exercise, which also can prevent severe injury.
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YAPICI, Murat Kaya. "Multilayer Flexible SU8-Gold Microelectrode Arrays for Wearable Bioelectronics." Sakarya University Journal of Science, November 21, 2022. http://dx.doi.org/10.16984/saufenbilder.1108035.
Full textAbstract:
Wearable health trackers for vital signs monitoring are becoming ever more important especially due to the global coronavirus pandemic (COVID-19) caused by the SARS‑CoV‑2 virus which severely affect the respiratory system and can cause cardiac manifestations. Particularly, wearable solutions which can seamlessly monitor heart activity are critical to facilitate personal preventive and remote healthcare, as well as to allow early diagnosis of cardiac dysfunctions. A fundamental enabler of wearable bioelectronics is the sensing bioelectrode which is used to record surface biopotentials. While a plethora of attempts have been reported to realize skin-conformal dry electrodes and electronic skin patches, oftentimes a very critical aspect of the electrode i.e., the actual electrical interfacing of the wearable electrode to readout circuits without disturbing the skin-electrode contact, is overlooked. To address this issue, this paper reports a unique tri-layer, polymer-metal-polymer skin-conformal microelectrode design with sidewall metal coating to achieve vertical interconnect accesses (VIAs) and realize contact pads for external interfacing. The novel and optimized process flow reported herein allows repeatable fabrication of flexible electrodes in arrayed format with yields exceeding 90%. Functionality of the microfabricated electrodes were demonstrated by successful acquisition of the electrocardiogram in lead-I configuration with clear detection of the P-QRS-T complex.