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- 实验方案
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[IEEE 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC) - Mon Tresor, Plaine Magnien, Mauritius (2018.12.6-2018.12.7)] 2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC) - OTA-C Filters for Biomedical Signal Processing Applications using Hybrid CMOS-CNFET Technology
摘要： Analog filters for biomedical signal processing applications deals with very slow or low frequency electrical activities of the physiological signals. This paper proposes first order, second order, fifth order elliptic low pass, second order notch and high pass OTA-C filters using hybrid CMOS-CNFET technology. Carbon Nanotube Field Effect Transistors (CNFETs) and CMOS devises can be heterogeneously integrated on a single 3-D chip to realize important signal processing building blocks such as OTA-C filters. Proposed circuits use Operational Transconductance Amplifier (OTA) as a building block for OTA-C filters. Realized filter circuits satisfy ultra-low power consumption requirement of wearable and implantable biomedical devices. The transistors used in the circuit operate in weak inversion to achieve ultra-low power consumption.
关键词： Noise Filtering,OTA-C Filters,Biomedical Signal Processing,Carbon Nanotube Field Effect Transistors
更新于2025-09-23 15:22:29
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[IEEE 2018 Innovations in Intelligent Systems and Applications (INISTA) - Thessaloniki (2018.7.3-2018.7.5)] 2018 Innovations in Intelligent Systems and Applications (INISTA) - Piezologist: A Novel Wearable Piezoelectric-based Cardiorespiratory Monitoring System
摘要： In this paper, the design, prototyping and software development of a novel wearable cardiorespiratory parameters monitoring sensor and software applications illustrated. Piezologist is an unobtrusive chest worn device. It comprises a patch-type sensor and a mobile application. The sensor utilizes piezoelectric material as the cardiorespiratory signal sensing component and MetaWearC board as the signal acquisition unit. The board also comes with Bluetooth Low Energy (BLE) support which is utilized for the raw signal transmission. The novelty aspect of the system rests on the fact that not only using a single cheap piezoelectric sheet common cardiorespiratory parameters (such as heart rate, respiration rate, and cycles) were obtained similar to previous studies but ECG waveform and blood pressure data were also extracted successfully using the same sensor. In addition, sensor packaging design and prototyping and their effect on the acquired signal strength on one hand and the package size (volume and weight) on the other hand were studied and reported. For performance validation purpose, the developed cardiorespiratory monitoring system results were validated against two commercial sensor devices namely 3-lead ECG sensor from eHealth sensor kit and Zephyr belt-type BioHarness sensor, and the results were reported herein. The validation process outcomes confirmed that the cardiorespiratory signals extracted using Piezologist conform with a heartbeat, respiratory cycle and ECG waveform obtained using the commercial sensors. Furthermore, a usability study was conducted to compare the user experience offered by Piezologist for measuring cardiorespiratory parameters against the commercially available sensors. The study highlighted the potential that Piezologist will take over the commercial available belt-type, watch-type and 3-lead ECG sensors.
关键词： biomedical signal processing,heart rate extraction,wearable sensors,Sensors,Vital signs,ECG waveform,Home healthcare,cardiorespiratory,Heartbeats,mobile healthcare,Respiration rate
更新于2025-09-23 15:22:29
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A Fast Fluorescence Background Suppression Method for Raman Spectroscopy Based on Stepwise Spectral Reconstruction
摘要： Raman spectroscopy is a rapid and non-destructive technique for detecting unique spectral fingerprints from biological samples. Raw Raman spectra often come with strong fluorescence background, which makes spectral interpretation challenging. Although fluorescence background can be suppressed experimentally, this approach requires sophisticated and costly instruments. For convenience and cost-effectiveness, numerical methods have been used frequently to remove fluorescence background. Unfortunately, many of such methods suffer from long computation time. Therefore, a fast numerical method for fluorescence suppression is highly desirable especially in Raman spectroscopic imaging where Raman measurements from many pixels need to be processed rapidly. In response to this demand, we propose a fast numerical method for fluorescence background suppression based on the strategy of stepwise spectral reconstruction that we previously developed. Compared with traditional computational methods, including polynomial fitting, wavelet transform, Fourier transform, and peak detection, our results consistently show significant advantages in both accuracy and computational efficiency when tested on Raman spectra measured from phantoms and cells as well as surfaced enhanced Raman spectra from blood serum samples. In particular, our method yields clean Raman spectra closest to the reference results generated by polynomial fitting while several orders of magnitude faster than others. Therefore, the proposed fast fluorescence suppression method is promising in Raman spectroscopic imaging or related application in which high computation efficiency is critical and a calibration dataset is available.
关键词： Raman spectroscopy,fluorescence suppression,Raman imaging,Biomedical signal processing
更新于2025-09-11 14:15:04
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A Signal Processing Method for Respiratory Rate Estimation through Photoplethysmography
摘要： Monitoring of respiration is crucial for determining a patient′s health status, specially previously and after an operation. However, many conventional methods are difficult to use in a spontaneously ventilating patient. This paper presents a method for estimating respiratory rate from the signal of a photoplethysmograph. This is a non-invasive sensor that can be used to obtain an estimation of beats per minute of a given patient by measuring light reflection on the patient’s blood vessel and counting changes in blood flow. The PPG signal also offers information about respiration, so respiratory rate can be obtained through signal processing. The proposed method based on digital filtering was implemented in a wearable device and tested on 30 volunteers, and the results were compared with the ones measured by traditional ways. The results show that there is no statistically significant difference between the data measured by the device and the traditional method.
关键词： biomedical signal processing,telemedicine,photoplethysmography,respiratory rate
更新于2025-09-11 14:15:04
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Biosensor-based feature extraction and physiological parameters measurement for biomedical applications
摘要： Physiological signal processing has significantly increased recently among the biomedical researchers for developing wearable standalone devices. Wearable devices are essential in hospital which is used for various biomedical applications such as heart rate and blood pressure measurement. In noisy environment, producing an algorithm for the physiological signal processing and feature extraction is an essential task which depends on the physiological conditions. In this paper, the software-based algorithms are developed for physiological signal processing and physiological parameter measurement. This paper presents biosensor-based real-time acquisition, processing and peak detection of ECG and PPG signals for heart rate, pulse rate and blood pressure measurement. ECG and PPG amplifiers were designed and the real-time signals are acquired through analogue devices and processed using LabVIEW and MatLab environment. The advantages of proposed work are very simple, low cost, easy integration with programming environment and gives continuous monitoring of physiological signals.
关键词： PPG signal,heart rate,ECG signal,biomedical signal processing
更新于2025-09-09 09:28:46
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[Institution of Engineering and Technology 12th European Conference on Antennas and Propagation (EuCAP 2018) - London, UK (9-13 April 2018)] 12th European Conference on Antennas and Propagation (EuCAP 2018) - A Liquid with Tuneable Dielectric Properties for Wideband Microwave Sensing of Biological Targets
摘要： Biomedical microwave systems require antenna-to-body matching to transfer electromagnetic energy efficiently through the skin and inside the body. In this paper a paraffin oil and saline water based matching liquid is presented that can be modified in a straight-forward manner to match various dielectrics. The permittivity of this liquid may be varied between 10-52 by altering the proportions of paraffin oil to water. The conductivity can be varied between 0.3 and 1.0S/m (at 3GHz) by altering the salinity of the water, without significantly altering the permittivity. Dielectric measurements and one- and two-pole Debye parameters are given for a range of different mixtures at frequencies of 0.5-10GHz. The results highlight the flexibility of the matching liquid and mark it as a suitable antenna coupling medium as well as a biological phantom material in the low GHz range.
关键词： Biomedical signal processing,Dispersive media,Microwave imaging
更新于2025-09-04 15:30:14