The Use of Wrist EMG Increases the PPG Heart Rate Accuracy in Smartwatches

Friman, Severi; Vehkaoja, Antti; Perez-Macias, Jose Maria

doi:10.1109/jsen.2022.3219297

Cited by 5 publications

(5 citation statements)

References 20 publications

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“…As for walking, the mean absolute error (MAE) offered by our algorithm for walking is 1.86 bpm (beats per minute), the second best but very close to the best [46] of all the reported results. Among all the studies in Table 2, most of them [8,10,22,23,29,46] render better results, with MAEs under 3 bpm, where two-channel PPGs and an accelerometer are employed for HR estimation, the same as in this study, to achieve favorable performance. On top of these studies are those [29,46] that achieve MAEs under 2 bpm for walking.…”

Section: Discussionmentioning

confidence: 88%

“…The performance of the proposed two sub-algorithms is compared herein to the results delivered by other reported past studies. Table 1 [6,13,19] and Table 2 [8,10,[22][23][24][25]29,46] show the comparison among the algorithms for hand movement and walking, respectively. The mean absolute error (MAE) is considered the main metric for performance comparison.…”

Section: Discussionmentioning

confidence: 99%

“…A new algorithm of motion artifact removal (MAR) is engineered herein for reconstructing MR-free PPG signals based on the decomposed Hankel matrices in Equations ( 5)- (7) and their mutual correlation in Equation (8). The associated computation flow is shown in Figure 10, while the pseudo-code is given below.…”

Section: The Computational Flow Of the Proposed Mar Algorithmmentioning

confidence: 99%

“…x y x y x y (8) where the correlation value ρx,y gives the similarity index between the two signals, with expected values µx and µy, and standard σx and σy of the two signals. The components in measured PPG that are highly correlated to accelerations are removed.…”

Section: The Computational Flow Of the Proposed Mar Algorithmmentioning

confidence: 99%

“…Some researchers, such as Hanyu et al [6], have also used the standard deviation and mean error along with selected parameters to detect MAs and remove them. Another method is to consider the spectral analysis of measured raw PPG signals based on ensemble empirical mode decomposition (EEMD) with spectrum subtraction (SS) [7,8]. In this method, corrupted PPG signals are classified into corrupted, moderately corrupted, and clean by the thresholds on the amplitudes and frequencies of dominant peaks.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Precision Heart Rate Estimation Using a PPG Sensor Patch Equipped with New Algorithms of Pre-Quality Checking and Hankel Decomposition

Thakur

Chao

Tsai

2023

Sensors

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A new method for accurately estimating heart rates based on a single photoplethysmography (PPG) signal and accelerations is proposed in this study, considering motion artifacts due to subjects’ hand motions and walking. The method comprises two sub-algorithms: pre-quality checking and motion artifact removal (MAR) via Hankel decomposition. PPGs and accelerations were collected using a wearable device equipped with a PPG sensor patch and a 3-axis accelerometer. The motion artifacts caused by hand movements and walking were effectively mitigated by the two aforementioned sub-algorithms. The first sub-algorithm utilized a new quality-assessment criterion to identify highly noise-contaminated PPG signals and exclude them from subsequent processing. The second sub-algorithm employed the Hankel matrix and singular value decomposition (SVD) to effectively identify, decompose, and remove motion artifacts. Experimental data collected during hand-moving and walking were considered for evaluation. The performance of the proposed algorithms was assessed using the datasets from the IEEE Signal Processing Cup 2015. The obtained results demonstrated an average error of merely 0.7345 ± 8.1129 beats per minute (bpm) and a mean absolute error of 1.86 bpm for walking, making it the second most accurate method to date that employs a single PPG and a 3-axis accelerometer. The proposed method also achieved the best accuracy of 3.78 bpm in mean absolute errors among all previously reported studies for hand-moving scenarios.

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