Wrist PPG Research Articles

Heart Rate Estimation From Wrist-Worn Photoplethysmography: A Review

Photoplethysmography (PPG) is a low-cost, non-invasive, and optical technique used to detect blood volume changes in the microvascular tissue bed, measured from the skin surface. It has traditionally been used in commercial medical devices for oxygen saturation, blood pressure monitoring, and cardiac activity for assessing peripheral vascular disease and autonomic function. There has been a growing interest to incorporate PPG sensors in daily life, capable of use in ambulatory settings. However, inferring cardiac information (e.g. heart rate) from PPG traces in such situations is extremely challenging, because of interferences caused by motion. Following the IEEE Signal Processing Cup in 2015, numerous methods have been proposed for estimating particularly the average heart rate using wrist-worn PPG during physical activity. Details on PPG technology, sensor development, and applications have been well documented in the literature. Hence, in this paper, we have presented a comprehensive review of state-of-the-art research on heart rate estimation from wrist-worn PPG signals. Our review also encompasses brief theoretical details about PPG sensing and other potential applications-biometric identification, disease diagnosis using wrist PPG. This paper will set a platform for future research on pervasive monitoring using wrist PPG.

A Method for Respiration Rate Detection in Wrist PPG Signal Using Holo-Hilbert Spectrum

Respiration is a crucial vital sign to indicate acidotic state of human body. In this paper, we have developed a Holo-Hilbert spectral analysis (HHSA)-based approach to detect subject’s respiration frequency from wrist photoplethysmogram (PPG) signals. The HHSA is a two-layer EMD architecture which first decomposes the original signal into intrinsic mode functions and then tries to find additive and multiplicative interactions among the participating components. The HHSA enables frequency-modulated (FM) and amplitude-modulated (AM) features of a signal can be comprehensively presented on a Holo-Hilbert spectrum (HHS). With the help of HHSA, subject’s respiration frequency can be identified on HHS by finding the AM frequency with the most prominent amplitude around the FM frequency of heart rate. The efficacy of the proposed method has been demonstrated in two designed experiments. In the first experiment, 75 subjects with ages ranged from 20–80 years old, and the difference between the detected results of proposed method and the readouts of transthoracic impedance plethysmography is 0.04 ± 0.96 breathes-per-minute (brm). In the second experiment, six subjects were requested to breathe at 6, 12, 18, 24 brm, following the pacing rhythms of a metronome. The difference between detected respiration rates and expected breathing rates is 0.01 ± 0.70 brm. The HHSA-based approach has manifested its capability to extract respiration-induced multiplicative component in PPG signal. It avoids the ambiguity of frequency representation in signal multiplication when using traditional additive decomposition methods.

The Accuracy of Atrial Fibrillation Detection from Wrist Photoplethysmography. A Study on Post-Operative Patients.

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Although not life-threatening itself, AF significantly increases the risk of stroke and myocardial infarction. Current tools available for screening and monitoring of AF are inadequate and an unobtrusive alternative, suitable for long-term use, is needed. This paper evaluates an atrial fibrillation detection algorithm based on wrist photoplethysmographic (PPG) signals. 29 patients recovering from surgery in the post-anesthesia care unit were monitored. 15 patients had sinus rhythm (SR, 67.5± 10.7 years old, 7 female) and 14 patients had AF (74.8± 8.3 years old, 8 female) during the recordings. Inter-beat intervals (IBI) were estimated from PPG signals. As IBI estimation is highly sensitive to motion or other types of noise, acceleration signals and PPG waveforms were used to automatically detect and discard unreliable IBI. AF was detected from windows of 20 consecutive IBI with 98.45±6.89% sensitivity and 99.13±1.79% specificity for 76.34±19.54% of the time. For the remaining time, no decision was taken due to the lack of reliable IBI. The results show that wrist PPG is suitable for long term monitoring and AF screening. In addition, this technique provides a more comfortable alternative to ECG devices.

Monitoring of heart rate and inter-beat intervals with wrist plethysmography in patients with atrial fibrillation

Objective: Atrial fibrillation (AF) causes marked risk for patients, while silent fibrillation may remain unnoticed if not suspected and screened. Development of comfortable yet accurate beat-to-beat heart rate (HR) monitoring with good AF detection sensitivity would facilitate screening and improve treatment. The purpose of this study was to evaluate whether a wrist-worn photoplethysmography (PPG) device can be used to monitor beat-to-beat HR accurately during post-operative treatment in patients suffering from AF and whether wrist-PPG can be used to distinguish AF from sinus rhythm (SR).Approach: Twenty-nine patients (14 with AF, 15 with SR, mean age 71.5 years) with multiple comorbidities were monitored during routine post-operative treatment. The monitoring included standard ECG, finger PPG monitoring and a wrist-worn PPG monitor with green and infrared light sources. The HR from PPG sensors was compared against ECG-derived HR.Main results: The wrist PPG technology had very good HR and beat detection accuracy when using green light. For the SR group, the mean absolute error (MAE) for HR was 1.50 bpm, and for the inter-beat intervals (IBI), the MAE was 7.64 ms. For the AF group, the MAE for HR was 4.28 bpm and for IBI, the MAE was 14.67 ms. Accuracy for the infrared (IR) channel was worse. Finger PPG provided similar accuracy for HR and better accuracy for the IBI. AF detection sensitivity using green light was 99.0% and the specificity was 93.0%. Performance can be improved by discarding unreliable IBI periods.Significance: Results suggest that wrist PPG measurement allows accurate HR and beat-to-beat HR monitoring also in AF patients, and could be used for differentiating between SR and AF with very good sensitivity.

Description of a Database Containing Wrist PPG Signals Recorded during Physical Exercise with Both Accelerometer and Gyroscope Measures of Motion

Wearable heart rate sensors such as those found in smartwatches are commonly based upon Photoplethysmography (PPG) which shines a light into the wrist and measures the amount of light reflected back. This method works well for stationary subjects, but in exercise situations, PPG signals are heavily corrupted by motion artifacts. The presence of these artifacts necessitates the creation of signal processing algorithms for removing the motion interference and allowing the true heart related information to be extracted from the PPG trace during exercise. Here, we describe a new publicly available database of PPG signals collected during exercise for the creation and validation of signal processing algorithms extracting heart rate and heart rate variability from PPG signals. PPG signals from the wrist are recorded together with chest electrocardiography (ECG) to allow a reference/comparison heart rate to be found, and the temporal alignment between the two signal sets is estimated from the signal timestamps. The new database differs from previously available public databases because it includes wrist PPG recorded during walking, running, easy bike riding and hard bike riding. It also provides estimates of the wrist movement recorded using a 3-axis low-noise accelerometer, a 3-axis wide-range accelerometer, and a 3-axis gyroscope. The inclusion of gyroscopic information allows, for the first time, separation of acceleration due to gravity and acceleration due to true motion of the sensor. The hypothesis is that the improved motion information provided could assist in the development of algorithms with better PPG motion artifact removal performance.

Gyroscope vs. accelerometer measurements of motion from wrist PPG during physical exercise

Many wearable devices include PPG (photoplethysmography) sensors for non-invasive heart rate monitoring. However, PPG signals are heavily corrupted by motion interference, and rely on simultaneous motion measurements to remove the interference. Accelerometers are used commonly, but cannot differentiate between acceleration due to movement and acceleration due to gravity. This paper compares measurements of motion using accelerometers and gyroscopes to give a more complete estimate of wrist motion. Results show the two sensor signals are very different, with low correlations present. When used in a wrist PPG heart rate algorithm gyroscope motion estimates obtain better performance in half of the cases.