A Biofeedback Based Auto-Controlled Neurostimulator Design for Proper NCS Signal Acquisition and Measurement

This paper presents the design of a biofeedback based auto-controlled neurostimulator for acquiring nerve response. Nerve conduction study (NCS) employs an electrical stimulator that generates a stimulus to be applied over the skin of an underlying nerve. Conventional neurostimulator uses manual control of voltage or current to generate the nerve responses. It is observed that the stimulation for supramaximal response varies with subjects due to different skin resistances of the subjects. Such measurement needs repeated trials which is time consuming, irritating to subjects and often suffers difficulties in real-time applications. This study proposes a portable neurostimulator based on the skin resistance as bio-feedback parameter to control the stimulus. A custom made NCS setup is developed for experimental recording of real-time nerve signals and identified the best compound muscle action potential signal for generating optimal stimulus i.e., supramaximal stimulus (SS) manually. Then, mathematical models are investigated using real-time data and models are implemented in a microcontroller (µC) based stimulator. The µC triggers a pulse train of specific duty cycle to a buck converter for producing the required optimal voltage which is used as a SS across the electrodes. Online experimental results with new subjects show that the proposed design is efficacious and adaptable with safety.

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Numerical Control Lathe Cutting Force Signal On-Line Monitoring Design

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.711.329 ◽

2014 ◽

Vol 711 ◽

pp. 329-332

Author(s):

Lin Zhao

Keyword(s):

Cutting Force ◽

Real Time ◽

Piezoelectric Sensor ◽

Numerical Control ◽

Signal Acquisition ◽

Time Data ◽

Main Research ◽

Monitoring Design ◽

Force Signal ◽

On Line

The main research direction of Numerical control lathe cutting force signal on-line monitoring is to process real-time monitoring, using the sensor, charge amplifier, video acquisition card and computer to collect data and signal. Signal acquisition makes use of the piezoelectric sensor signals and send them to the computer in order to acquire the real-time data and display the dynamic signal so that monitor the process. Signal processing is the course that data will be collected for subsequent processing and analyzing. It includes display, filtering, correlation analysis, spectral analysis, etc. We can conclude the signal’s characteristics after the time domain and frequency domain analysis of signals.

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A Study on Developing Cardiac Signals Recording Framework (CARDIF) Using a Reconfigurable Real-Time Embedded Processor

International Journal of Biomedical and Clinical Engineering ◽

10.4018/ijbce.2019070102 ◽

2019 ◽

Vol 8 (2) ◽

pp. 31-44

Author(s):

Uma Arun ◽

Natarajan Sriraam

Keyword(s):

Real Time ◽

Signal To Noise Ratio ◽

Physiological State ◽

Parameters Estimation ◽

Signal Acquisition ◽

Virtual Instrumentation ◽

Time Data ◽

Embedded Processor ◽

Fidelity Measures ◽

The Time Domain

Due to recent developments in technology, there is a significant growth in healthcare monitoring systems. The most widely monitored human physiological parameters is electrocardiogram (ECG) which is useful for inferring the physiological state of humans. Most of the existing multi-channel ECG acquisition systems were not accessible in resource-constrained settings. This research study proposes a cardiac signal recording framework (CARDIF) using a reconfigurable input-output real-time embedded processor by employing a virtual instrumentation platform. The signal acquisition was configured using Lab VIEW virtual instrumentation block sets. A graphical user interface (GUI) was developed for real-time data acquisition and visualization. The time domain heart rate variability (HRV) statistics were calculated using CARDIF, and the same were compared with a clinical grade 12-channel ECG system. The quality of the acquired signals obtained from the proposed and standard systems was measured and compared by calculating signal-to-noise ratio (SNR). The proposed CARDIF was evaluated qualitatively by visual inspection by a clinician and quantitatively by fidelity measures and vital parameters estimation. The results are quite promising and can be extended for clinical validations.

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DESIGN CONSIDERATIONS FOR RIVER FLOATING SENSORS

ASEAN Engineering Journal ◽

10.11113/aej.v8.15494 ◽

2018 ◽

Vol 8 (1) ◽

pp. 1-13

Author(s):

Zool Hilmi Ismail ◽

Amzar Omairi ◽

Toru Namerikawa ◽

Adha Imam Cahyadi

Keyword(s):

Power Generation ◽

Real Time ◽

Design Methodology ◽

Generation Model ◽

Time Data ◽

Design Decisions ◽

Design Considerations ◽

Custom Made ◽

Real Time Data

In order to utilize the flow of a river to generate power, it is crucial to develop a system that is able to obtain and record the river’s characteristics in various aspects. A simple but effective method has to be created to allow researchers to collect and study the parameters of a river in order to predetermine the final build of the power generation model. A floating sensor that is able to collect and give a real-time data has been developed using readily available hardware as well as custom made parts. This paper describes a design methodology for river floating sensors and results from a case study performed in the actual controlled channel are presented to demonstrate the effectiveness of the design decisions.

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A Real-Time Fiber Optical System for Wellbore Monitoring: A Johan Sverdrup Case Study

10.2118/205405-ms ◽

2021 ◽

Author(s):

Maximilian Georg Schuberth ◽

Håkon Sunde Bakka ◽

Claire Emma Birnie ◽

Stefan Dümmong ◽

Kjetil Eik Haavik ◽

...

Keyword(s):

Decision Making ◽

Real Time ◽

Large Data ◽

Pipeline Architecture ◽

Distributed Temperature Sensing ◽

Time Data ◽

Data Pipeline ◽

Start Up ◽

Custom Made ◽

Gas Lift

Abstract Fiber Optic (FO) sensing capabilities for downhole monitoring include, among other techniques, Distributed Temperature Sensing (DTS) and Distributed Acoustic Sensing (DAS). The appeal of DTS and DAS data is based on its high temporal and spatial sampling, allowing for very fine localization of processes in a wellbore. Furthermore, the broad frequency spectrum that especially DAS data is acquired with, enables observations, ranging from more continuous effects like oil flow, to more distinct effects like opening and closing of valves. Due to the high data volume of hundreds of Gb per well per hour, DAS data has traditionally been acquired acquisition-based, where data is recorded for a limited amount of time and processed at a later point in time. This limits the decision-making capability based on this data as reacting to events is only possible long after the event occurred. Equinor has addressed these decision-making shortcomings by building a real-time streaming solution for transferring, processing, and interpretation of its FO data at the Johan Sverdrup field in the North Sea. The streaming solution for FO data consists of offshore interrogators streaming raw DAS and DTS data via a dedicated bandwidth to an onshore processing cluster. There, DAS data is transformed into FO feature data, e.g., Frequency Band Energies, which are heavily decimated versions of the raw data; allowing insight extraction, while significantly reducing data volumes. DTS and DAS FO feature data are then streamed to a custom-made, cloud-based visualization and integration platform. This cloud-based platform allows efficient inspection of large data sets, control and evaluation of applications based on these data, and sharing of FO data within the Johan Sverdrup asset. During the last year, this FO data streaming pipeline has processed several tens of PB of FO data, monitoring a range of well operations and processes. Qualitatively, the benefits and potential of the real-time data acquisitions have been illustrated by providing a greater understanding of current well conditions and processes. Alongside the FO data pipeline, multiple prototype applications have been developed for automated monitoring of Gas Lift Valves, Safety Valve operations, Gas Lift rate estimation, and monitoring production start-up, all providing insights in real-time. For certain use cases, such as monitoring production start-up, the FO data provides a previously non-existent monitoring solution. In this paper, we will discuss in detail the FO data pipeline architecture from-platform-to-cloud, illustrate several data examples, and discuss the way-forward for "real-time" FO data analytics.

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Ambulatory Assessment

European Psychologist ◽

10.1027/1016-9040.14.2.109 ◽

2009 ◽

Vol 14 (2) ◽

pp. 109-119 ◽

Cited By ~ 66

Author(s):

Ulrich W. Ebner-Priemer ◽

Timothy J. Trull

Keyword(s):

Real Time ◽

Clinical Psychology ◽

Real Life ◽

Ambulatory Assessment ◽

Computer Assisted ◽

Affective Valence ◽

Time Data ◽

Physiological Processes ◽

Context Specific ◽

Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

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