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Introduction to Functional Magnetic Resonance Imaging, Principles and TechniquesIntroduction to Functional Magnetic Resonance Imaging, Principles and Techniques. By BuxtonR. B.. Cambridge University Press, Cambridge2002. ISBN 0-521-58113-3. 536 pages 134 line diagrams, 34 halftone figures. Price hardback: GBP 95.00.

Breathing rate (BR) is a key physiological parameter used in a range of clinical settings. Despite its diagnostic and prognostic value, it is still widely measured by counting breaths manually. A plethora of algorithms have been proposed to estimate BR from the electrocardiogram (ECG) and pulse oximetry (photoplethysmogram, PPG) signals. These BR algorithms provide opportunity for automated, electronic, and unobtrusive measurement of BR in both healthcare and fitness monitoring. This paper presents a review of the literature on BR estimation from the ECG and PPG. First, the structure of BR algorithms and the mathematical techniques used at each stage are described. Second, the experimental methodologies that have been used to assess the performance of BR algorithms are reviewed, and a methodological framework for the assessment of BR algorithms is presented. Third, we outline the most pressing directions for future research, including the steps required to use BR algorithms in wearable sensors, remote video monitoring, and clinical practice.

Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review

Without a fixed security infrastructure, mobile ad hoc networks must distribute intrusion detection among their nodes. But even though a distributed intrusion-detection system can combine data from multiple nodes to estimate the likelihood of an intrusion, the observing nodes might not be reliable. The Dempster-Shafer theory of evidence is well suited for this type of problem because it reflects uncertainty. Moreover, Dempster's rule for combination gives a numerical procedure for fusing together multiple pieces of evidence from unreliable observers. The authors review the Dempster-Shafer theory in the context of distributed intrusion detection and demonstrate the theory's usefulness.

Dempster-shafer theory for intrusion detection in Ad hoc networks : Ah hoc and P2P security

Wearable health and wellness trackers based on optical detection are promising candidates for public health uses due to their noninvasive tracking of vital health signs. However, so far, the use of rigid technologies hindered the ultimate performance and form factor of the wearable. Here, we demonstrate a new class of flexible and transparent wearables based on graphene sensitized with semiconducting quantum dots (GQD). We show several prototype wearable devices that are able to monitor vital health signs noninvasively, including heart rate, arterial oxygen saturation (SpO2), and respiratory rate. Operation with ambient light is demonstrated, offering low-power consumption. Moreover, using heterogeneous integration of a flexible ultraviolet (UV)–sensitive photodetector with a near-field communication circuit board allows wireless communication and power transfer between the photodetectors and a smartphone, offering battery-free operation. This technology paves the way toward seamlessly integrated wearables, and empowers the user through wireless probing of the UV index.

https://advances.sciencemag.org/content/advances/5/9/eaaw7846.full.pdf

Flexible graphene photodetectors for wearable fitness monitoring.

Background: Blood pressure (BP) measurements have been used widely in clinical and private environments. Recently, the use of ECG monitors has proliferated; however, they are not enabled with BP estimation. We have developed a method for BP estimation using only electrocardiogram (ECG) signals. Methods: Raw ECG data are filtered and segmented, and, following this, a complexity analysis is performed for feature extraction. Then, a machine-learning method is applied, combining a stacking-based classification module and a regression module for building systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP) predictive models. In addition, the method allows a probability distribution-based calibration to adapt the models to a particular user. Results: Using ECG recordings from 51 different subjects, 3129 30-s ECG segments are constructed, and seven features are extracted. Using a train-validation-test evaluation, the method achieves a mean absolute error (MAE) of 8.64 mmHg for SBP, 18.20 mmHg for DBP, and 13.52 mmHg for the MAP prediction. When models are calibrated, the MAE decreases to 7.72 mmHg for SBP, 9.45 mmHg for DBP and 8.13 mmHg for MAP. Conclusion: The experimental results indicate that, when a probability distribution-based calibration is used, the proposed method can achieve results close to those of a certified medical device for BP estimation.

https://www.mdpi.com/1424-8220/18/4/1160/pdf

Non-Invasive Blood Pressure Estimation from ECG Using Machine Learning Techniques

Measurement of blood volumetric changes in human body by photoplethysmographic sensors is used in present study. Objective is to measured different parameters that are heart rate, respiratory rate, BP. PPG signal is acquired by PPG sensor, microcontroller and RS 232. The acquired PPG signal is displayed in MATLAB. Frequency domain analysis of PPG signal shows a two peaks first at around 0.25 to 0.35 Hz and second at around 1 to 1.5 Hz. FFT at 1Hz relates to 60 BPM and FFT at 0.25 Hz relates to 15 respiratory cycles per minute. For BP Measurement, the pulse height of PPG is proportional to the difference between the systolic and the diastolic pressure in the arteries. The standard blood pressure monitoring instrument is used to calculate correlation coefficient. The arterial blood pressure is calculated based on these coefficients. PPG signal is used to detect blood pressure pulsations in a finger and achieved an accuracy of (0.8 ± 7) mmHg and (0.9 ± 6) mmHg for systolic and diastolic pressure, respectively. The developed PPG based method can be used as a noninvasive alternative to the conventional occluding-cuff approaches for long-term and continuous monitoring of blood pressure, heart rate and respiratory rate.

Respiratory rate, heart rate and continuous measurement of BP using PPG

Detection of blood volume change in the skin by using Photoplethysmogram (PPG) sensor is based on the principle that hemoglobin in the blood absorbs infrared light than the other tissue. Favorable optical window is around 990 nm range. The reflectance type photoplethysmographic sensor is designed using two different detectors. Objective is to compare the response of PPG sensor by using Light Dependent resistors (LDR) and OPT101 as a detector. Signal is recorded by placing the sensor on a finger tip for wavelength ranging from visible to near IR (400 to 1000 nm) range. It is observed that the PPG signal captured using LDR is around 660 nm wavelength but for the OPT101 response is 500 nm to 1000 nm. That is OPT 101 can be used to capture PPG in visible and infrared region. Brain mapping using optical sensor OPT101 is preferable for the measurement of blood volume and blood flow. For source of 660 nm, LDR or OPT 101 can be used to detect the peripheral pulse. LDR is not suitable for the measurement in infrared range.

Comparative analysis of LDR and OPT 101 detectors in reflectance type PPG sensor

Mahalingam Sundhararajana,∗, Xiao-Zhi Gaob and Hamed Vahdat Nejadc aDepartment of Electronics and Communication Engineering, Bharath Institute of Higher Education and Research, Bharath University, Chennai, India bDepartment of Machine Vision and Pattern Recognition Laboratory, Lappeenranta University of Technology, Finland cDepartment of Computer Science and Engineering, University of Birjand, Birjand, Iran

/pdf/artificial-intelligent-techniques-and-its-applications-4qzu85sg41.pdf

Artificial intelligent techniques and its applications

In the last few years the Global Positioning System (GPS) has been used in a variety of applications for which new and more restrictive requirements in the design of the receiving antenna have been introduced. In particular, for high precision GPS application, such as differential GPS, GPS-based space graft altitude determination or geodetic surveying, receiving antenna with superior rejection to multipath signals is required. Multipath arises when the GPS transmitted signal takes different paths to receiving antenna and being the signals from these paths added with different spaces, this result in a significant amplitude and phase distortion.

http://www.eurasianjournals.com/pdf-114597-43999?filename=Study of Micristrip Patch.pdf

Study of Micristrip Patch Antenna with Truncated Corners

— Action, cognition, emotion and perception can be mapped in the brain by using set of techniques. Translating unimodal concepts from one modality to another is an important step towards understanding the neural mechanisms. This paper provides a comprehensive survey of multimodal analysis of brain signals such as fMRI, EEG, MEG, NIRS and motivations, assumptions and pitfalls associated with it. All these non-invasive brain modalities complement and restrain each other and hence improve our understating of functional and neuronal organization. By combining the various modalities together, we can exploit the strengths and flaws of individual brain imaging methods. Integrated anatomical analysis and functional measurements of human brain offer a powerful paradigm for the brain mapping. Here we provide the brief review on non invasive brain modalities, describe the future of co-analysis of these brain signals. Keywords- EEG, fMRI, MEG, NIRS and BMI.

M. Sundhararajan

Papers

Respiratory rate, heart rate and continuous measurement of BP using PPG

Comparative analysis of LDR and OPT 101 detectors in reflectance type PPG sensor

Artificial intelligent techniques and its applications

Study of Micristrip Patch Antenna with Truncated Corners

Brain Connectivity Analysis Methods for Better Understanding of Coupling