Search Results (77)

Silicon carbide (SiC) has been widely adopted in the semiconductor industry, particularly in power electronics, because of its high temperature stability, high breakdown field, and fast switching speeds. Its wide bandgap makes it an interesting candidate for radiation-hard particle detectors in high-energy physics and medical applications. Furthermore, the high electron and hole drift velocities in 4H-SiC enable devices suitable for ultra-fast particle detection and timing applications. However, currently, the front-end readout electronics used for 4H-SiC detectors constitute a bottleneck in investigations of the charge carrier drift. To address these limitations, a high-frequency readout board with an intrinsic bandwidth of 10 GHz was developed. With this readout, the transient current signals of a 4H-SiC diode with a diameter of 141 μm and a thickness of 50 μm upon UV laser, alpha particle, and high-energy proton beam excitation were recorded. In all three cases, the electron and hole drift can clearly be separated, which enables the extraction of the charge carrier drift velocities as a function of the electric field. These velocities, directly measured for the first time, provide a valuable comparison to Monte Carlo-simulated literature values and constitute an essential input for TCAD simulations. Finally, a complete simulation environment combining TCAD, the Allpix² framework, and SPICE simulations is presented, which is in good agreement with the measured data. Full article

Electromagnetic compatibility is the capability of electrical and electronic equipment to function properly around devices radiating electromagnetic energy, without mutual disturbance. Hospital environments contain numerous devices operating simultaneously and sharing resources. Undetected electromagnetic interference can cause medical devices’ malfunctions, exposing patients and staff. Traditional monitoring is time-consuming and relies on expert interpretation. An Internet of Things-enabled embedded system architecture for remote and real-time monitoring of electromagnetic fields from medical devices is proposed. It integrates frequency probes, a Raspberry Pi 4, and a communication module. A three-month study conducted at Muhima District Hospital, Kigali, Rwanda, demonstrated the system’s effectiveness in monitoring electromagnetic field levels and cloud transmission. The signals were benchmarked against International Electrotechnical Commission and Rwanda Standards Board standards. Alerts are triggered when thresholds are exceeded, with results plotted on website and mobile interfaces. Emissions were highest at noon when the equipment was most active and lower after 1:30 PM, indicating reduced activity. The sample recorded statistics of electric fields include mean (1.0028), minimum (0.7228), and maximum (1.3515). Among the five filters evaluated, the Savitzky–Golay performed better, with MSE (0.235) and SNR (9.308). A 412 ms average latency and 24 h operation was achieved, offering a portable solution for hospital safety and equipment optimization. Full article

EMFIT, also referred to as EMFi, is a ferroelectret film related to polyvinylidene fluoride (PVDF) sensors. It is an electroactive polymer (EAP) based on a polyolefin structure and consists of three layers of polyester film. Its application in geophysical monitoring has not been reported in the literature. At present, EMFIT is mainly employed in ballistocardiography and medical sleep monitoring, as developed by the manufacturer Emfit Ltd. (Vaajakoski, Finland). Within the multidisciplinary monitoring network of the National Institute for Earth Physics (NIEP), EMFIT is used as a pressure sensor in combination with infrasound transducers and microphones deployed in seismic areas. The primary aim of this study is to evaluate its suitability for detecting seismic noise that precedes earthquakes, generated by rock fracturing associated with crustal deformation. Although similar studies have been reported, they have not involved the use of EMFIT sensors. The novelty of this approach lies in the large surface area and mechanical flexibility of the material. Beyond seismic forecasting, the research also examines whether this type of sensor can contribute to seismic monitoring as a complement to conventional instruments such as accelerometers, seismometers, and microbarometers. Data analysis relies primarily on spectral time-series methods and incorporates measurements from other acoustic sensors (microphones and microbarometers) as well as a weather station. The working hypothesis is the potential correlation between the recorded data and the presence of enhanced noise prior to the detection of seismic waves by standard seismic sensors. The target area for this investigation is Vrancea, specifically the Vrâncioaia seismic station, where multidisciplinary monitoring includes infrasound, radon, thoron, soil temperature, and atmospheric electrical discharges. Preliminary tests suggest that the EMFIT sensor may function as a highly sensitive device, effectively serving as an “ear” for detecting ground noise. Full article

The electrocardiogram (ECG), which records variations in surface electrical potential over time, has been widely used in the diagnosis of cardiovascular diseases. In recent years, the artificial intelligence (AI) + ECG paradigm has attracted considerable interest, but the two intrinsic characteristics of the ECG, namely, inter-lead correlations and multi-label classification, are often overlooked. Given that this oversight may constrain the full potential of AI models to enhance diagnostic performance, this study focuses on investigating methods for fusing information from a 12-lead ECG. A series of comprehensive experiments was conducted to evaluate the performance of various lead configurations, that is, 1-, 3-, 6-, 9-, and 12-lead combinations, with different fusion strategies. Innovatively integrating medical theory, we propose a novel five-lead-grouping strategy and develop a neural network architecture named Lead-5-Group Net (L5G-Net). After ranking the 12 leads with the AUC, we found that the aVR, V5, and V6 leads are particularly informative for single-lead ECG diagnosis. Furthermore, in multi-lead ECG classification, adopting an orthogonal lead-selection strategy which is based on the hypothesis of spatial interdependence among ECG leads was shown to enhance performance by ensuring that the information provided by each lead is complementary. Finally, the proposed L5G-Net demonstrates outstanding performance, achieving a macro-AUC of 0.9357 on the PTB-XL multi-label dataset without the use of data augmentation, attention mechanisms, or other strategies. Furthermore, considerable performance gains were observed after the five-lead-grouping strategy was applied to DenseNet and ResNet. These results imply that the proposed strategy can be seamlessly integrated into various network architectures and considerably enhance performance. Full article

Background: Chronic thoracic pain is commonly caused by thoracic facet dysfunction, intercostal neuralgia, surgery, or thoracic pain secondary to cancer and is present in approximately 15% of the population. Conventional treatments, including pharmacotherapy and transcutaneous electrical nerve stimulation, are often ineffective and are often associated with poorly tolerated adverse effects. Cooled radiofrequency ablation (c-RFA) is a minimally invasive procedure that uses radiofrequency energy delivered through a probe to lesion the targeted nerve and provide significant and lasting relief. Methods: This study was a retrospective analysis of data extracted from UW-Health Electronic Medical Health records from October 2015 through June 2024. Patient data were collected, including diagnosis, pre-operative pain score, post-operative pain score, duration of relief, age, sex, and BMI. A two-tailed paired t-test was used to analyze the pre-operative and post-operative pain scores. A p-value < 0.05 was considered significant. Results: A total of 111 thoracic c-RFA procedures were reviewed; 43 were excluded due to absent pre-operative or post-operative pain scores in medical records. A total of 68 procedures were included in the analysis, comprising 55 patients: 25 females and 30 males with an average age of 51.31 ± 18.22 years and a BMI of 29.79 ± 6.48 kg/m². Improvement in pain scores was reported in 77.94% (n = 53), 16.18% (n = 11) reported no change, and 5.88% (n = 4) reported worsening pain. Patients reported an average pre-operative pain score of 5.98 (M = 5.98, SD = 1.91) and an average post-operative pain score of 3.06 (M = 3.06, SD = 2.52); this achieved significance (p < 0.0001). Of the 77.94% (n = 53) charts that noted improvement, there is an average of 62.83 ± 28.48% reduction from their pre-operative pain scores. The average duration of relief lasted 11.85 ± 13.42 months. Conclusions: This study supports the efficacy and safety of c-RFA as a minimally invasive therapy for chronic thoracic pain refractory to conservative measures. Full article

Background: High-voltage injuries associated with train surfing are a distinct subset of electrical injuries, yet detailed analyses remain limited. This study retrospectively reviewed train-surfing injuries admitted between 1994 and 2024, comparing their characteristics and outcomes to work-related high-voltage injuries. Methods: Medical records of 102 patients admitted for high-voltage injuries were analyzed, including 32 train-surfing and 70 work-related cases. Demographics, injury patterns, and clinical outcomes were assessed. Results: Train surfers were predominantly young males (median age 19 years), while work-related injuries involved slightly older males (median age 34 years). Train surfers sustained more severe burns (%TBSA: 47.6% vs. 25.4%, p < 0.0001) and higher ABSI scores (6.7 vs. 5.3, p < 0.01). Vertical electrical flow was predominant in train surfing (65.6%), reflecting contact with overhead lines, while work-related injuries showed varied flow patterns, with diagonal flow being most frequent (58.6%). Train surfers had longer ICU stays (38.7 vs. 17.9 days, p < 0.001) and underwent more surgeries per patient (5.3 vs. 2.8, p < 0.01). Fasciotomy rates were significantly higher among train surfers (84.4% vs. 55.7%, p < 0.01), as were amputations (53.1% vs. 25.7%, p < 0.001). Mortality rates were similar in both groups (25%). Conclusions: Train-surfing injuries represent a distinct and highly severe subgroup of high-voltage trauma, marked by greater burn extent, predominantly vertical electrical flow due to contact with overhead lines, and significantly higher surgical complexity—including increased rates of fasciotomies and amputations. Despite comparable mortality, the clinical burden for train-surfing victims is substantially higher, reflected in longer ICU stays and more operations per patient. These findings underscore the urgent need for targeted prevention strategies addressing youth engagement in train surfing. Public health campaigns, railway infrastructure modifications (e.g., deterrent systems or physical barriers), and early educational interventions could play a critical role in reducing these preventable injuries. Furthermore, trauma centers should be prepared for the specific reconstructive and critical care demands posed by this high-risk group, emphasizing the importance of specialized multidisciplinary management protocols. Full article

Background/Objections: The pharmacological management of Parkinson’s Disease (PD) is often supplemented by deep brain stimulation (DBS) to tackle problems of advanced disease such as motor fluctuation, dyskinesias or medication-resistant tremor. DBS uses high-frequency stimulation with spatially distributed electrodes to produce electrical fields that influence neuronal networks. The programming of such stimulation is complex and time-consuming. Recent technological advancements have enabled DBS systems to record local field potentials (LFPs). In conjunction with biomarker discovery, such as beta oscillations, this shows promise in streamlining the DBS programming process. This review aims to synthesize the current literature investigating LFP characteristics in PD in order to understand the place of LFPs in assisting with DBS programming. Methods: A comprehensive literature search was conducted using databases including OVID MEDLINE, Scopus, and Cochrane Library, resulting in 738 identified articles; 122 studies remained after screening and 87 studies were selected for detailed analysis. Results: Analyzing LFPs clearly has the potential to assist or streamline DBS programming in clinical practice, but there are knowledge gaps and challenges to overcome, especially in the utilization of intraoperative LFPs. Conclusions: More research is required to compare different algorithms that utilize LFPs in DBS programming to identify a simple, practical and time-saving algorithm incorporating reliable LFP biomarkers that will enhance the DBS programming experience for both patients and clinicians. Full article

Background/Objectives: Sudden cardiac arrest (SCA) is a severe medical condition involving the cessation of the heart’s mechanical activity. Following the chain of survival, which includes early recognition and calling for help, early initiation of cardiopulmonary resuscitation (CPR), early defibrillation, and post-resuscitation care, offers the greatest chances of saving a person who has experienced SCA. The aim of this study was to analyze cases of out-of-hospital cardiac arrest (OHCA) and assess the actions taken by bystanders. Methods: The input for analysis consisted of 49,649 dispatch records from the emergency medical team (EMT) at the Voivodeship Emergency Medical Station in Bialystok in 2018–2019. Results: Among the patients where bystanders performed CPR, the return of spontaneous circulation (ROSC) occurred in 30.53% of cases, whereas in the cases where the bystander did not perform CPR, ROSC occurred in 2.35% of cases. When cardiac arrest rhythm was ventricular fibrillation (VF) or pulseless ventricular tachycardia (pVT), ROSC occurred in 58.62% of cases, while there was asystole or pulseless electrical activity (PEA) present, ROSC occurred in 26.56% of cases. In patients who experienced OHCA in a VF/pVT rhythm and who underwent intubation, ROSC occurred in 58.73% of cases, whereas in patients who underwent alternative procedures for airway management, ROSC occurred in 83.33% of cases. Conclusions: The most significant factor influencing the occurrence of ROSC in patients is CPR initiation by bystanders. The presence of a rhythm that requires defibrillation increases the likelihood of achieving ROSC in the patient. Alternative methods for airway management appear to be more beneficial in VF/pVT rhythms. Full article

Background/Objectives—Parkinson’s disease (PD) is the second most common neurodegenerative disorder caused by the destruction of neurons in the substantia nigra of the brain. Clinical diagnosis of this disease, based on monitoring motor symptoms, often leads to a delayed start of PD therapy and control, where over 60% of dopaminergic nerve cells are damaged in the brain substantia nigra. The search for simple and stable characteristics of EEG recordings is a promising direction in the development of methods for diagnosing PD and methods for diagnosing the preclinical stage of PD development. Methods—42 subjects participated in work, of which 4 female/10 male patients were included in the group of patients with non-motor disorders, belonging to the risk group for developing PD (median age: 62 years, height: 164 cm, weight: 70 kg, pulse: 70, BPsys and BPdia: 143 and 80)/(median age: 68 years, height: 170 cm, weight: 73.9 kg, pulse: 75, BPsys and BPdia: 143 and 82). The first control group of healthy participants included 6 women (median age: 33 years, height: 161 cm, weight: 66 kg, pulse: 80, BPsys and BPdia: 110 and 80)/8 men (median age: 36.3 years, height: 175 cm, weight: 69 kg, pulse: 78, BPsys and BPdia: 120 and 85). The second control group of healthy participants included 8 women (median age: 74 years, height: 164 cm, weight: 70 kg, pulse: 70, BPsys and BPdia: 145 and 82)/6 men (median age: 51 years, height: 172 cm, weight: 72.5 kg, pulse: 74, BPsys and BPdia: 142 and 80). Wavelet oscillatory pattern estimation is performed on patients’ nocturnal sleep recordings without separating them into sleep stages. Results—Amplitude characteristics of oscillatory activity in patients without motor disorders and the prodromal PD stage are significantly reduced both in terms of changes in the number of patterns and in terms of their duration. This pattern is especially pronounced for high-frequency activity, in frequency ranges close to 40 Hz. Conclusions—The success of the analysis of the electrical activity of the brain, performed over the entire duration of the night recording, makes it promising to further use during daytime monitoring the concept of oscillatory wavelet patterns in patients with non-motor disorders, belonging to the risk group for developing PD. The daytime monitoring system can become the basis for developing screening tests to detect neurodegenerative diseases as part of routine medical examinations. Full article

Neural recording systems play a crucial role in comprehending the intricacies of the brain and advancing treatments for neurological disorders. Within these systems, the analog-to-digital converter (ADC) serves as a fundamental component, converting the electrical signals from the brain into digital data that can be further processed and analyzed by computing units. This research introduces a novel nonlinear ADC designed specifically for spike sorting in biomedical applications. Employing MOSFET varactors and voltage-controlled oscillators (VCOs), this ADC exploits the nonlinear capacitance properties of MOSFET varactors, achieving a parabolic quantization function that digitizes the noise with low resolution and the spikes with high resolution, effectively suppressing the background noise present in biomedical signals. This research aims to develop a reconfigurable, nonlinear voltage-controlled oscillator (VCO)-based ADC, specifically designed for implantable neural recording systems used in neuroprosthetics and brain–machine interfaces. The proposed design enhances the signal-to-noise ratio and reduces power consumption, making it more efficient for real-time neural data processing. By improving the performance and energy efficiency of these devices, the research contributes to the development of more reliable medical technologies for monitoring and treating neurological disorders. The quantization step of the ADC spans from 44.8 mV in the low-amplitude range to 1.4 mV in the high-amplitude range. The circuit was designed and simulated utilizing a 180 nm CMOS process; however, no physical prototype has been fabricated at this stage. Post-layout simulations confirm the expected performance. Occupying a silicon area is 0.09 mm². Operating at a sampling frequency of 16 kS/s and a supply voltage of 1 volt, this ADC consumes 62.4 µW. Full article

Here, we report an ultrasoft extra long-lasting, reusable hydrogel-based sensor that enables high-quality electrophysiological recording with low-motion artifacts. The developed sensor can be used and stored in an ambient environment for months before being reused. The developed sensor is made of a self-adhesive electrical-conductivity-enhanced ultrasoft hydrogel mounted in an Ecoflex-based frame. The hydrogel’s conductivity was enhanced by incorporating polypyrrole (PPy), resulting in a conductivity of 0.25 S m⁻¹. Young’s modulus of the sensor is only 12.9 kPa, and it is stretchable up to 190%. The sensor was successfully used for electrocardiography (ECG) and electromyography (EMG). Our results indicate that using the developed hydrogel-based sensor, the signal-to-noise ratio of recorded electrophysiological signals was improved in comparison to that when medical-grade silver/silver chloride (Ag/AgCl) wet gel electrodes were used (33.55 dB in comparison to 22.16 dB). Due to the ultra-softness, high stretchability, and self-adhesion of the developed sensor, it can conform to the skin and, therefore, shows low susceptibility to motion. In addition, the sensor shows no sign of irritation or allergic reaction, which usually occurs after long-term wearing of medical-grade Ag/AgCl wet gel electrodes on the skin. Further, the sensor is fabricated using a low-cost and scalable fabrication process. Full article

Background and Objectives: Chronic heart failure (CHF) caused by ischemic heart disease (IHD) is the leading cause of death worldwide and presents significant health challenges. Effective management of IHD requires prevention, early detection, and treatment to improve patient outcomes. This study aims to expand the diagnostic utility of various 24 h Holter ECG parameters, such as T-wave alternans (TWA), late ventricular potentials (LVPs), and heart rate variability (HRV) in patients with CHF caused by IHD. Additionally, we seek to explore the association between these parameters and other comorbid conditions affecting the prognosis of CHF patients. Materials and Methods: We conducted a prospective case–control study with 150 patients divided into two subgroups: 100 patients with CHF caused by IHD, and 50 patients in the control group. Data included medical history, physical examination, laboratory tests, echocardiography, and 24 h Holter monitoring. Results: Our comparative analysis demonstrated that both TWA and LVPs were significantly higher in patients with CHF compared to the control group (p < 0.01), indicating increased myocardial electrical vulnerability in CHF patients. Both time and frequency-domain HRV parameters were significantly lower in the CHF group. However, the ratio of NN50 to the total count of NN intervals (PNN50) showed a borderline significance (p = 0.06). While the low-frequency (LF) domain was significantly lower in CHF patients, the high-frequency (HF) domain did not differ significantly between groups. Acceleration and deceleration capacities were also significantly altered in CHF patients. Categorizing CHF patients by left ventricular ejection fraction (LVEF) revealed that the mean of the 5-min normal-to-normal intervals over the complete recording (SDNN Index) was significantly higher in patients with LVEF ≥ 50% compared to those with CHF with reduced EF and CHF with mildly reduced EF (p < 0.001), whereas the other HRV parameters showed no significant differences among the groups. Conclusions: Holter ECG parameters can become a reliable tool in the assessment of patients with CHF. The integration of multiple Holter ECG parameters, such as TWA, LVPs, and HRV, can significantly enhance the diagnostic assessment of CHF caused by IHD. This comprehensive approach allows for a more nuanced understanding of the patient’s condition and potential outcomes. Full article

Non-invasive transcranial electrical stimulation is a category of neuromodulation techniques used for various disorders. Although medically approved devices exist, the variety of consumer electrical stimulation devices is increasing. Because clinical trials and animal tests are costly and risky, using a brain phantom can provide preliminary experimental validation. However, existing brain phantoms are often costly or require excessive preparation time, precluding their use for rapid, real-time optimization of stimulation settings. A limitation of direct electric fields in a phantom is the lack of 3D spatial resolution. Using well-researched modalities such as transcranial direct current stimulation (tDCS) and newer modalities such as amplitude-modulated transcranial pulsed-current stimulation (am-tPCS), a range of materials was tested for use as electrical phantoms. Based on cost, preparation time, and efficiency, ground beef and agar gel with a 10% salt mix were selected. The measured values for the total dosages were 0.55 W-s for am-tPCS and 0.91 W-s for tDCS. Due to a low gain on the recording electrodes, the signal efficiency measured against the power delivered was 4.2% for tDCS and 3.1% for am-tPCS. Issues included electrodes shifting in the soft material and the low sensitivity of the recording electrodes. Despite these issues, the effective combination of the phantom and recording methodologies can enable low costs and the rapid testing, experimentation, and verification of consumer neuromodulation devices in three dimensions. Additionally, the efficiency factors (EFs) between the observed dosage and the delivered dosage could streamline the comparison of experimental configurations. As demonstrated by comparing two types of electrical neuromodulation devices across the 3D space of a phantom, EFs can be used in conjunction with a cost-effective, time-expedient phantom to rapidly iterate and optimize stimulation parameters. Full article

On 1 January 2024, a large earthquake occurred in Japan’s Noto region. Many buildings collapsed as a result of violent shaking. Electricity and water supplies were cut off, and communications were disrupted. On 5 January, four days after the earthquake, we visited Noto and conducted disaster-relief activities. This report integrates and discusses the results of the site visits, information broadcasts by public institutions, and previous research. Evacuation centers lacked water and proper sanitation, leading to health issues, including infectious diseases. Disaster Medical Assistance Teams (DMAT) were delayed in implementing infection control measures. Isolated evacuation centers faced communication and supply challenges. Infrastructure restoration, power supply, and toilet facilities at evacuation centers were delayed because of geographical challenges. It is important to have a team that can determine and carry out the necessary activities on site, even without instructions from the DMAT. It is believed to be effective to decide in advance how volunteer teams and the private sector will conduct their activities, assuming that they will be unable to contact public institutions during a disaster. In large-scale disasters, evacuees must operate evacuation centers autonomously. To achieve this, it is necessary for residents to regularly come together as a community. Systematically recording and accumulating these experiences will contribute to improved disaster prevention and mitigation planning. We hope that the experiences we obtained through the abovementioned disaster will be useful for preparing for future disasters. Full article

Background/Objectives: The effectiveness of a rhythm control strategy in patients with atrial fibrillation (AF) and reduced left ventricular ejection fraction (LVEF < 50%) in real-world practice remains uncertain. Our objective was to evaluate the real-world outcomes of a rhythm control strategy in patients with AF and reduced LVEF, focusing on changes in LV systolic function and brain natriuretic peptide (BNP) levels. Methods: The study retrospectively reviewed the medical records of 80 patients with concurrent AF and reduced LVEF who underwent rhythm control therapy between March 2015 and December 2021. Results: The patients had an average age of 63.6 years and an initial LVEF of 34.3%. Sinus rhythm was restored using anti-arrhythmic drugs (38, 47.5%) or electrical cardioversion (42, 52.5%). Over a follow-up period of 53.0 months, AF recurred in 65% of patients, with 57.7% undergoing catheter ablation. Significant improvements were noted in LVEF (from 34.3% to 55.1%, p < 0.001) and BNP levels (from 752 pg/mL to 72 pg/mL, p < 0.001) at the last follow-up. Nearly all patients (97.5%) continued with the rhythm control strategy during the follow-up period. Conclusions: In real-world settings, a rhythm control strategy proves to be feasible and effective for improving LVEF and reducing BNP levels in AF patients with reduced LVEF. Full article