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Statistical Parametric Mapping The Analysis Of Functional Brain Images

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

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.

A novel feature ranking algorithm for biometric recognition with PPG signals

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

Blood pressure (BP) is one of the important vital signs that need to be monitored for personal healthcare. This paper describes the method developed by the authors to measure systolic blood pressure from pulse transit time (PTT) Pulse transit time is the time taken for the arterial pulse pressure wave to travel from the aortic valve to a peripheral site. It is usually measured from the R wave on the electrocardiogram to a photoplethysmography signal. PTT is inversely proportional to blood pressure. This method does not require an air cuff and only a minimal inconvenience of attaching electrodes and LED/photo detector sensors on a subject. Twenty three healthy subjects (age 18–60 yrs) were studied. Blood pressure measurement is carried out using pulse transit time and is compared with sphygmomanometry, the reference standard and the oscillometric based automatic BP measuring machine. The results show that the standard deviation of their differences was around 3 mmHg. The developed pulse transit time based method can be used as a noninvasive and cuffless alternative to the conventional occluding-cuff approaches for long-term and continuous monitoring of blood pressure.

Continuous cuffless blood pressure monitoring based on PTT

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

Optical sensors that use photons as sensing elements are increasingly becoming important and relevant in the field of non-invasive diagnostics. The reason is that they have simple construction, easy to use and relatively inexpensive in comparison with tools such as EEG, MRI and FMRI that can be used for research with much investment. Among the many optical sensors available, the PPG (photoplethysmography) sensors, are capable of measuring blood volumetric changes in the subcutaneous vessels. Objective is to diagnose parameters like heart rate, respiratory rate. Real time PPG signal is obtained from sensor and heart rate is calculated from it. .Reflectance type of PPG sensor has been used to diagnose the parameters. Detailed analysis of frequency spectrum (FFT) of PPG signal shows a cardiac peak around 1Hz corresponding to 60 pulsations a minute and respiratory peak around 0.25 Hz corresponding to 15 inspiration/expiration cycles per minute.

Applications of Finger Photoplethysmography

Infusion pumps have a widespread use in the health care and Intensive Care Unit (ICU) of each hospital. The use of infusion pumps is advocated over manual flow control system on the basis of assuring precise and accurate delivery of prescribed fluid volumes over a specified time and to help in better nursing management. Transfusion speed of the pump must be changed as per the patients need and alarm indication for various abnormalities must be given. Manually setting all parameters is very time-consuming and a mistake could mean a high risk for the patients. Thus there is an obvious need of a system that can take care of this from central room. The developed system is a network which consists of a host computer (PC), transfusion monitors and interconnection mechanisms. The host computer manages the basic data of patients, transfusion information as well as controls the transfusion monitors through a wireless network to regulate the transfusion speed and give an alarm at the abnormality. A Graphical User Interface (GUI) is developed in Visual Basic (VB), which analyses the infusion history. The communication between the PC and the infusion pump occurs via a wireless network using ZigBee. The history report is generated in MS Excel format, which can be referred by the Physician. The developed system can be efficiently used for remote supervision of transfusion monitors in the ICU by hospital staff.

Wireless Transfusion Supervision and analysis using embedded system

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.

Nivedita Daimiwal

Papers

Continuous cuffless blood pressure monitoring based on PTT

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

Applications of Finger Photoplethysmography

Wireless Transfusion Supervision and analysis using embedded system

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