Comparison between red, green and blue light reflection photoplethysmography for heart rate monitoring during motion

Reflection photoplethysmography (PPG) using 530 nm (green) wavelength light has the potential to be a superior method for monitoring heart rate (HR) during normal daily life due to its relative freedom from artifacts. However, little is known about the accuracy of pulse rate (PR) measured by 530 nm light PPG during motion. Therefore, we compared the HR measured by electrocadiography (ECG) as a reference with PR measured by 530, 645 (red), and 470 nm (blue) wavelength light PPG during baseline and while performing hand waving in 12 participants. In addition, we examined the change of signal-to-noise ratio (SNR) by motion for each of the three wavelengths used for the PPG. The results showed that the limit of agreement in Bland-Altman plots between the HR measured by ECG and PR measured by 530 nm light PPG (±0.61 bpm) was smaller than that achieved when using 645 and 470 nm light PPG (±3.20 bpm and ±2.23 bpm, respectively). The ΔSNR (the difference between baseline and task values) of 530 and 470nm light PPG was significantly smaller than ΔSNR for red light PPG. In conclusion, 530 nm light PPG could be a more suitable method than 645 and 470nm light PPG for monitoring HR in normal daily life. © 2013 IEEE

SwellFit: Developing A Wearable Sensor for Monitoring Peripheral Edema

Peripheral edema is a swelling of the legs, feet, or hands due to the accumulation of excessive fluid in the tissues. For patients with some chronic diseases, peripheral edema is a crucial indicator of onset or exacerbation of the condition. Thus, early detection of peripheral edema is important for timely diagnosis of associated diseases. However, existing techniques for edema assessment are a subjective measurement for which a human operator estimates the amount of swelling using a tape measure or by pressing the swollen area with the tip of an index finger. As a systematic approach to assessing peripheral edema, we develop SwellFit, an experimental prototype of a novel wearable technology that monitors peripheral edema by tracking changes in ankle curvature. Through a series of proof-of-concept experiments, we demonstrate that SwellFit detects ankle swelling even in the presence of substantial noise in the raw sensor readings

Motion-Resistant Pulse Oximetry Processing Based on Time-Frequency Analysis

This paper proposes an alternative method for pulse oximetry processing based on time-frequency analysis. Instead of using the fast Fourier transform (FFT), the continuous wavelet transform (CWT) together with the median calculation was proposed for finding the frequency components of the normalized first derivative red and infrared photoplethysmographic signals. In order to estimate the arterial oxygen saturation (%SpO_2), the ratio of each red CWT modulus to each corresponding infrared CWT modulus was computed at each frequency, and then converted to the oxygen saturation by using the saturation equation obtained from calibration. All of the oxygen saturation data were plotted on a histogram. The greatest oxygen saturation with the most occurrences was considered to represent the %SpO_2. Experimental results showed that the proposed method was more resistant to the motion artifact than the conventional method.This paper proposes an alternative method for pulse oximetry processing based on time-frequency analysis.  Instead of using the fast Fourier transform (FFT), the continuous wavelet transform (CWT) together with the median calculation was proposed for finding the frequency components of the normalized first derivative red and infrared photoplethysmographic signals (PPG).  In order to estimate the arterial oxygen saturation (%SpO2), the ratio of each red CWT modulus to each corresponding infrared CWT modulus was computed at each frequency, and then converted to the oxygen saturation by using the saturation equation obtained from calibration.  All of the oxygen saturation data were plotted on a histogram.  The greatest oxygen saturation with the most occurrences was considered to represent the %SpO2. The experiments were held to evaluate the performance of the proposed processing method compared with the conventional pulse oximetry (CPO) processing.  The red and infrared PPGs were acquired from left and right index fingers simultaneously by using the PPG measurement system constructed in the laboratory.  During measurement, the left index finger was stationary, while the right index finger was performed the finger bend to induce the motion artifact (MA) in transient and periodic manners.  All detected PPGs were processed by the proposed method and the CPO processing.  The %SpO2 obtained from different processing methods and positions were compared.  Experimental results showed that the proposed method was more resistant to the MA than the conventional method

A multi-channel opto-electronic sensor to accurately monitor heart rate against motion artefact during exercise

This study presents the use of a multi-channel opto-electronic sensor (OEPS) to effectively monitor critical physiological parameters whilst preventing motion artefact as increasingly demanded by personal healthcare. The aim of this work was to study how to capture the heart rate (HR) efficiently through a well-constructed OEPS and a 3-axis accelerometer with wireless communication. A protocol was designed to incorporate sitting, standing, walking, running and cycling. The datasets collected from these activities were processed to elaborate sport physiological effects. t-test, Bland-Altman Agreement (BAA), and correlation to evaluate the performance of the OEPS were used against Polar and Mio-Alpha HR monitors. No differences in the HR were found between OEPS, and either Polar or Mio-Alpha (both p > 0.05); a strong correlation was found between Polar and OEPS (r: 0.96, p < 0.001); the bias of BAA 0.85 bpm, the standard deviation (SD) 9.20 bpm, and the limits of agreement (LOA) from −17.18 bpm to +18.88 bpm. For the Mio-Alpha and OEPS, a strong correlation was found (r: 0.96, p < 0.001); the bias of BAA 1.63 bpm, SD 8.62 bpm, LOA from −15.27 bpm to +18.58 bpm. These results demonstrate the OEPS to be capable of carrying out real time and remote monitoring of heart rate

A Wearable System for Real-Time Continuous Monitoring of Physical Activity

Over the last decades, wearable systems have gained interest for monitoring of physiological variables, promoting health, and improving exercise adherence in different populations ranging from elite athletes to patients. In this paper, we present a wearable system for the continuous real-time monitoring of respiratory frequency (fR), heart rate (HR), and movement cadence during physical activity. The system has been experimentally tested in the laboratory (by simulating the breathing pattern with a mechanical ventilator) and by collecting data from one healthy volunteer. Results show the feasibility of the proposed device for real-time continuous monitoring of fR, HR, and movement cadence both in resting condition and during activity. Finally, different synchronization techniques have been investigated to enable simultaneous data collection from different wearable modules.Ministerio de Economía y Competitivida

Opto-physiological modeling applied to photoplethysmographic cardiovascular assessment

This paper presents opto-physiological (OP) modeling and its application in cardiovascular assessment techniques based on photoplethysmography (PPG). Existing contact point measurement techniques, i.e., pulse oximetry probes, are compared with the next generation noncontact and imaging implementations, i.e., non-contact reflection and camera-based PPG. The further development of effective physiological monitoring techniques relies on novel approaches to OP modeling that can better inform the design and development of sensing hardware and applicable signal processing procedures. With the help of finite-element optical simulation, fundamental research into OP modeling of photoplethysmography is being exploited towards the development of engineering solutions for practical biomedical systems. This paper reviews a body of research comprising two OP models that have led to significant progress in the design of transmission mode pulse oximetry probes, and approaches to 3D blood perfusion mapping for the interpretation of cardiovascular performance

Data-driven methods for analyzing ballistocardiograms in longitudinal cardiovascular monitoring

Cardiovascular disease (CVD) is the leading cause of death in the US; about 48% of American adults have one or more types of CVD. The importance of continuous monitoring of the older population, for early detection of changes in health conditions, has been shown in the literature, as the key to a successful clinical intervention. We have been investigating environmentally-embedded in-home networks of non-invasive sensing modalities. This dissertation concentrates on the signal processing techniques required for the robust extraction of morphological features from the ballistocardiographs (BCG), and machine learning approaches to utilize these features in non-invasive monitoring of cardiovascular conditions. At first, enhancements in the time domain detection of the cardiac cycle are addressed due to its importance in the estimation of heart rate variability (HRV) and sleep stages. The proposed enhancements in the energy-based algorithm for BCG beat detection have shown at least 50% improvement in the root mean square error (RMSE) of the beat to beat heart rate estimations compared to the reference estimations from the electrocardiogram (ECG) R to R intervals. These results are still subject to some errors, primarily due to the contamination of noise and motion artifacts caused by floor vibration, unconstrained subject movements, or even the respiratory activities. Aging, diseases, breathing, and sleep disorders can also affect the quality of estimation as they slightly modify the morphology of the BCG waveform.Includes bibliographical reference