Real-time Signal Monitoring Research Articles

Adaptive probe position correction for automated complex weld inspection based on structural signal monitoring

ABSTRACT To ensure comprehensive coverage of welds, multi-axis motions are necessary for the probe during the automatic detection of complex welds. Guaranteeing the effectiveness of ultrasonic data during this process is crucial for ensuring detection accuracy and reliability. Taking tubular Y-joints as an example, this paper presents an adaptive probe posture correction method based on structural signal monitoring: (1) The structural and acoustic model of tubular Y-joints is established to select and predict the target structural signal. (2) Feature extraction and signal tracking algorithms are developed to achieve real-time monitoring of signals. (3) A posture correction method is proposed based on signal characteristics: time-domain characteristics correspond to position adjustments, while amplitudes correspond to orientation corrections. Building upon this, a feedback mechanism for probe posture is established. The effectiveness of the developed method is verified through underwater automatic detection experiments of tubular Y-joints. Results demonstrate that, with the assistance of the probe posture correction method, the coverage of the effective area increases to more than 95%, and embedded defects are fully detected through a single scan. In conclusion, the adaptive probe posture correction method based on structural signal monitoring presents a promising approach for the automatic ultrasonic examination of complex welds.

A comparison of the acoustic waves generated in proton and carbon ion therapy

Hadron therapy, which employs particles such as protons and carbon-ions, is a promising method of cancer treatment due to its unique ability to deliver maximum energy at the Bragg peak near the tumor, sparing surrounding healthy tissue. Ionoacoustic waves, generated by thermal expansion from electronic collisions and localized heating, can be detected to optimize dose delivery and verify particle range, thus improving treatment precision. These waves offer a unique opportunity for comparative studies of different particle therapies. In this study, a mathematical model and computational simulations are used to compare the characteristics of ionoacoustic waves generated in tissue by proton and carbon-ion beams. In particular, we assess the impact of the nuclear fragmentation tail on the ionoacoustic signals generated in carbon-ion therapy. Our approach will allow us to make some important observations to study the comparative effects of proton and carbon-ion therapy. The aim of this work is to perform a comprehensive comparative analysis of ionoacoustic waves from proton and carbon-ion treatments, focusing on their potential for in-vivo range verification. This research addresses the current gap in understanding the use of ionoacoustic signals for range verification in ion beam therapy, which is critical given the growing clinical application of carbon ion therapy and its under-explored acoustic properties. This study pioneers the feasibility of using acoustic imaging from carbon-ion beams to detect the Bragg peak position and measure tumor dose in real-time. Carbon-ion dose mapping and relative biological effectiveness (RBE) assessment can be facilitated by real-time signal monitoring. Our study aims to significantly advance the field by addressing the lack of a verification technique for carbon-ion beams, focusing on the considerable impact of the nuclear fragmentation tail on ionoacoustic signal waveforms, which provides crucial insights into the unique energy deposition properties of carbon-ions.

High-precision high-speed nanopore ping-pong control system based on field programmable gate array.

"Molecular ping-pong," emerging as a control strategy in solid-state nanopore technology, presents a highly promising approach for repetitive measurements of single biomolecules, such as DNA. This paper introduces a high-precision, high-speed nanopore molecular ping-pong control system consisting of a home-built trans-impedance amplifier (TIA), a control system based on a Field Programmable Gate Array (FPGA), and a LabVIEW program operating on the host personal computer. Through feedback compensation and post-stage boosting, the TIA achieves a high bandwidth of about 200kHz with a gain of 100 MΩ, along with low input-referred current noise of 1.6 × 10-4pA2/Hz at 1kHz and 1.1 × 10-3pA2/Hz at 100kHz. The FPGA-based control system demonstrates a minimum overall response time (tdelay) of 6.5 μs from the analog input current signal trigger to the subsequent reversal of the analog output drive voltage signal, with a control precision of 1 μs. Additionally, a LabVIEW program has been developed to facilitate rapid data exchange and communication with the FPGA program, enabling real-time signal monitoring, parameter adjustment, and data storage. Successful recapture of individual DNA molecules at various tdelay, resulting in an improvement in capture rate by up to 2 orders of magnitude, has been demonstrated. With unprecedented control precision and capture efficiency, this system provides robust technical support and opens novel research avenues for nanopore single-molecule sensing and manipulation.

Shape-adaptive underwater adhesive based on supramolecular assembly for robustly integrated underwater wireless sensing/communication and bioelectronic adhesion

Developing multifunctional supramolecular adhesives, capable of instant underwater adhesion and multi-responsive sensing, is crucial for marine exploitation. However, producing underwater conductive adhesives that can effectively bind and conform to the complex contours of substrate surfaces is challenging. Herein, drawing inspiration from traditional gourmet “gluten” processing, we devised an “one-pot kneading-washing” supramolecular assembly strategy to engineer a shape-adaptive multifunctional underwater electroactive adhesive (e-PT/GS) for underwater sensing/communication and leakage sealing. Utilizing multiple non-covalent interactions, e-PT/GS demonstrated excellent electrical conductivity, underwater self-healing capability, anti-swelling properties, and the ability to achieve rapid, stable, and long-lasting underwater adhesion to a wide range of substrates in various harsh environments (e.g., acids, alkalis, seawater, and salt solutions). E-PT/GS exhibited anticipative shape-adaptability, repelling interfacial water and filling irregularities on the substrate surface, thereby establishing tight and unprecedentedly adaptable underwater contact with the substrates. In combination with the multi-dimensional sensing origins, e-PT/GS was utilized for underwater sealing and in-situ real-time monitoring of signals from the sealing points. Additionally, it was applied in body motion perception, wireless and underwater communications and enabled the collection of steady and authentic ECG signals. The proposed novel strategy is expected to significantly advance the design and applications of the next-generation conductive underwater adhesives.

Traffic Signal Control and Management System

Abstract: The congestion of vehicles on the road is increasing day by day and also the management of such large traffic by traditional approach isn't adequate enough. In today's scenario the traditional approach works efficiently only if the count is sparse, as the density of vehicles on a particular side of road increases or if the traffic is comparatively larger on one side than other side in such case the approach fails. Hence, we aim to redesign the traffic signal system that is static switching to signal switching, which can performs real-time signal monitoring and handling. So, in this project the switching time of signal will be decided based on real time image detection with good accuracy in dense traffic. This practice can prove its most effectiveness in releasing the congested traffic at an efficient and faster rate.

We-VoltamoStat: A wearable potentiostat for voltammetry analysis with a smartphone interface

Wearable technology, such as electronic components integrated into clothing or worn as accessories, is becoming increasingly prevalent in fields like healthcare and biomedical monitoring. These devices allow for continuous monitoring of important biomarkers for medical diagnosis, monitoring of physiological health, and evaluation. However, an open-source wearable potentiostat is a relatively new technology that still faces several design limitations such as short battery lifetime, bulky size, heavy weight, and the requirement for a wire for data transmission, which affects comfortability during long periods of measurement. In this work, an open-source wearable potentiostat device named We-VoltamoStat is developed to allow interested parties to use and modify the device for creating new products, research, and teaching purposes. The proposed device includes improved and added features, such as wireless real-time signal monitoring and data collection. It also has an ultra-low power consumption battery estimated to deliver 15 mA during operating mode for 33 h and 20 min and 5 mA during standby mode for 100 h without recharging. Its convenience for wearable applications, tough design, and compact size of 67x54x38 mm make it suitable for wearable applications. Cost-effectiveness is another advantage, with a price less than 120 USD. Validation performance tests indicate that the device has good accuracy, with an R2 value of 0.99 for linear regression of test accuracy on milli-, micro-, and nano-Ampere detection. In the future, it is recommended to improve the design and add more features to the device, including new applications for wearable potentiostats.

Bioinspired shark skin-based liquid metal triboelectric nanogenerator for self-powered gait analysis and long-term rehabilitation monitoring

Real-time gait monitoring is crucial for neuromuscular diagnosis and rehabilitation of neuromuscular ailments. However, the existing wearable sensors for gait analysis suffer from several drawbacks, such as external power requirement, poor sensitivity, short-term stability, and professional operator requirement, which restrict their applicability outside clinical settings. Here, a next-generation self-powered solid-liquid triboelectric nanogenerator-based flexible wearable sensor is developed. The proposed sensor is composed of a highly resilient liquid metal encapsulated within an innovative bio-mimicked shark skin-like microstructure embedded on the Ecoflex surface. The unique surface morphology imparts hydrophobicity to the solid triboelectric layer, which prevents the liquid metal adhesion during sensing and facilitates highly sensitive real-time monitoring of signals and long-term stability. The as-designed low-cost, highly scalable self-powered sensor, which is also compatible with diverse detection strategies, provides an on-demand user-friendly point-of-care gait detection and rehabilitation monitoring system with significant applications in personalized health care and sports science.

Embedded AM-FM Signal Decomposition Algorithm for Continuous Human Activity Monitoring

AM-FM decomposition techniques have been successfully used for extracting significative features from a large variety of signals, helping realtime signal monitoring and pattern recognition, since they represent signals as a simultaneous composition of amplitude modulation and frequency modulation, where the carriers, amplitude envelopes, and the instantaneous frequencies are the features to be estimated. Human activities often involve repetitive movements, such as in running or cycling, where sinusoidal AM-FM decompositions of signals have already demonstrated to be useful to extract compact features to aid monitoring, classification, or detection. In this work we thus present the challenges and results of implementing the iterated coherent Hilbert decomposition (ICHD), a particularly effective algorithm to obtain an AM-FM decomposition, within a resource-constrained and low-power ARM Cortex-M4 microcontroller that is present in a wearable sensor we developed. We apply ICHD to the gyroscope data acquired from an inertial measurement unit (IMU) that is present in the sensor. Optimizing the implementation allowed us to achieve real-time performance using less then 16 % of the available CPU time, while consuming only about 5.4 mW of power, which results in a run-time of over 7 days using a small 250 mAh rechargeable cell.

A Scoring Framework and Apparatus for Epilepsy Seizure Detection Using a Wearable Belt.

To develop a wearable device that can detect epilepsy seizures. In particular, due to their prevalence, attention is focused on detecting the generalized tonic-clonic seizure (GTCS) type. When a seizure is detected, an alert phone call is initiated and an alarm SMS sent to the nearest health-care provider (and/or a predesignated family member), including the patient's location as global positioning system (GPS) coordinates. A wearable belt is developed including an Arduino processor that constantly acquires data from four different sensing modalities and monitors the acquired signal patterns for abnormalities. The sensors are a heart rate sensor, electromyography sensor, blood oxygen level (oxygen saturation) sensor, and an accelerometer to detect sudden falls. Higher-than-normal threshold levels are established for each sensor's signal. If two or more signal measurements exceed the corresponding threshold value for a predetermined time interval, then the seizure alarm is triggered. Clinical trials were not pursued in this study as this is the initial phase of system development (phase 0). Instead, the instrumented belt seizure detection prototype was tested on nine healthy individuals mimicking, to some degree, seizure symptoms. A total of eighteen trials took place of which half had <2 sensor thresholds exceeded and no alarm, whereas the other half resulted in activating the alarm when two or more sensor thresholds were exceeded for at least the predetermined time interval corresponding to each of the higher-than-normal sensor readings. For each trial that triggered the alarm when a seizure was detected, the on-board GPS and global system for mobile communication (GSM) units successfully initiated an alert phone call to a predesignated number in addition to sending an SMS message, including GPS location coordinates. Continuous real-time monitoring of signals from the four different sensors allows the developed wearable belt to detect GTCS while reducing false alarms. The proposed device produces an important alarm that may save a patient's life.

Tissue post-classification using the measured acoustic signals during 355 nm laser atherectomy procedures.

The current laser atherectomy technologies to treat patients with challenging (to-cross) total chronic occlusions with a step-by-step (SBS) approach (without leading guide wire), are lacking real-time signal monitoring of the ablated tissues, and carry the risk for vessel perforation. We present first time post-classification of ablated tissues using acoustic signals recorded by a microphone placed nearby during five atherectomy procedures using 355 nm solid-state Auryon laser device performed with an SBS approach, some with highly severe calcification. Using our machine-learning algorithm, the classification results of these ablation signals recordings from five patients showed 93.7% classification accuracy with arterial vs nonarterial wall material. While still very preliminary and requiring a larger study and thereafter as commercial device, the results of these first acoustic post-classification in SBS cases are very promising. This study implies, as a general statement, that online recording of the acoustic signals using a noncontact microphone, may potentially serve for an online classification of the ablated tissue in SBS cases. This technology could be used to confirm correct positioning in the vasculature, and by this, to potentially further reduce the risk of perforation using 355 nm laser atherectomy in such procedures.

FPGA-based elastic in-circuit debugging for complex digital logic design

In digital integrated circuit design, the emergence of intellectual property (IP) reuse technology reduces the complexity of system on chip (SoC) design, and makes the SoC have more and more powerful functions. Unfortunately, it also increases the verification difficulty, and extends the whole system design cycle. Aiming at the low efficiency of stimulating mechanism, the difficulty of real-time signal monitoring and non-reusability of module-level verification platform for IP design based on field-programmable gate array (FPGA), we propose a kind of elastic in-circuit debugging method for complex digital logic design so as to optimise the verification process. Based on the extension of traditional IP verification platform, we build the IP in-circuit debugging platform, which has some advantages such as elasticity, configurability, extensibility and humanisation. After verification of multiple IP instances, the results show that the method has strong universality and can improve the efficiency of IP verification.

Real-time detection of BRCA1 gene mutations using a monolithic silicon optocoupler array

The monolithic silicon optocoupler presented here offers a platform for a new generation of fully integrated devices fabricated through the mature and inexpensive silicon technology. Using the developed optocoupler, real-time detection of the most common mutations in BRCA1 gene related to predisposition to hereditary breast/ovarian cancer was accomplished. For this purpose, oligonucleotides corresponding to wild- and mutant-type sequences were immobilized onto different optocouplers and the hybridization with fluorescently labeled complementary or non-complementary sequences was monitored in real time. Hybridization of fluorescently labeled oligonucleotides to the immobilized ones modulated the coupling efficiency between the light emitting diode and the detector in a concentration-dependent manner. Using as label the AlexaFluor ® 647 dye (whose absorption maximum fits the emission maximum of the light source) a detection limit of 0.9 nM (9 fmol) was achieved. Real-time signal monitoring, especially during dehybridization, improved considerably the discrimination between wild-type and mutant sequences due to the ability to calculate dissociation kinetics upon washing independently for each one mutation. The bioanalytical capabilities of the transducer along with the fact that dense transducer arrays can be fabricated on a single chip open new frontiers in the manufacturing of microsystems appropriate for point-of-care analysis.

Real-time acquisition and remote monitoring of steady state tokamak (SST-1) diagnostics data

The architecture of data acquisition system (DAS) for the tokamak SST-1 is essentially distributed and heterogeneous. With the long discharge duration of about 1000 s, that imposes a requirement of sampling data for an equally long duration from the variety of fast and slow diagnostics, the challenge is also to cater the need of a real time monitoring of signals by multiple locally networked users. With these objectives, the DAS is based on a model where the objects of the systems are integrated with the Central Control System of SST-1 using the TCP/IP communication. Communication of each object with the Central Server is facilitated with a dedicated, 100 Mbps, fully duplex, Ethernet connection. The DAS software essentially meets the demand of an active remote configuration of hardware digitizers, like PXI system and that of the initialization of acquisition within the local network. The present work describes the TCP/IP based DAS software in labview for configuring, acquiring, and subsequently, pushing the sampled data into network. The focus is also on a client utility for real-time monitoring of SST-1 diagnostics signals by multiple clients during the discharges. We also describe the model implemented for archival and retrieval of SST-1 diagnostics data using an MDSplus server and the model tree, with its sub trees necessitated by the different SST-1 diagnostics system. In addition to this, viewing the SST-1 diagnostics signals across the network using JSCOPE and browsing the signals using Web is also described, along with a matlab plotting tool for the SST-1 diagnostics data.