Search Results (66)

This study aims to investigate asymmetries in muscle activation and co-contraction of main lower limb muscles during flamenco Zap-3 footwork with consideration of the footwork speed and dancer proficiency. Twelve flamenco dancers participated, including six professionals and six amateurs. Each participant performed the Zap-3 sequence under three speed conditions: 160 beats per minute (bpm), 180 bpm and the fastest speed level (F). The normalized surface electromyography was recorded in the gastrocnemius medialis (GM), biceps femoris (BF), tibialis anterior (TA) and rectus femoris (RF) in the dominant (DL) and non-dominant leg (NDL). The co-contraction index was also calculated for selected muscle pairs. The results showed that significant asymmetries occurred only in professional dancers and exclusively at the F speed level. Specifically, the value of the GM in the NDL was higher than that of the DL (p < 0.05, d = 1.97); the value of the BF in the DL was higher than that of the NDL (p < 0.05, d = 1.86) and the co-contraction index of BF/RF in the DL was higher than that of the NDL (p < 0.05, d = 1.87). Understanding these asymmetries may help to inform individualized training strategies aimed at optimizing performance and reducing potential risks. Full article

Cardiorespiratory fitness is a predictor of long-term health, traditionally assessed through structured exercise protocols that require maximal effort and controlled laboratory conditions. These protocols, while clinically validated, are often inaccessible, physically demanding, and unsuitable for unsupervised monitoring. This study proposes a non-invasive, unsupervised alternative—predicting the heart rate a person would reach after completing the step test, using wearable data collected during natural daily activities. Ground truth post-exercise heart rate was obtained through the Queens College Step Test, which is a submaximal protocol widely used in fitness settings. Separately, wearable sensors recorded heart rate (HR), blood oxygen saturation, and motion data during a protocol of lifestyle tasks spanning a range of intensities. Two machine learning models were developed—a Human Activity Recognition (HAR) model that classified daily activities from inertial data with 96.93% accuracy, and a regression model that estimated post step test HR using motion features, physiological trends, and demographic context. The regression model achieved an average root mean squared error (RMSE) of 5.13 beats per minute (bpm) and a mean absolute error (MAE) of 4.37 bpm. These findings demonstrate the potential of test-free methods to estimate standardized test outcomes from daily activity data, offering an accessible pathway to infer cardiorespiratory fitness. Full article

Danionella, a transparent freshwater species belonging to the Cyprinidae family, has emerged as a valuable model organism in biological and medical research due to its optical transparency. The cardiovascular system of Danionella larvae provides a unique opportunity for non-invasive heart rate monitoring in aquatic animals. Traditional approaches for evaluating larval heart rate often require manual or semi-automated definition of the cardiac region in video recordings. In this study, we developed a simplified heart rate monitoring system that estimates heartbeat activity by analyzing interframe luminance differences in video sequences of Danionella larvae. Our system successfully measured heart rates in the range of 150–155 beats per minute (bpm), consistent with previous findings reporting rates between 140 and 200 bpm. The non-invasive nature of this method offers significant advantages for high-throughput screening and long-term physiological monitoring. Furthermore, this system has potential applications in evaluating environmental stressors, supporting survival and health assessments, and guiding habitat management strategies to ensure stable populations of adult fish in both natural and laboratory settings. Full article

We assessed the test validity of the Apple Watch series 6 measure of heart rate variability (HRV) by comparing it with the reference measure assessed via a Biopac 3-lead electrocardiogram (ECG). We recruited 78 healthy adults (aged 20–75 years). HRV was measured using an in-lab protocol while resting, talking, watching a movie, before walking, and after walking. We conducted a synchronized countdown for each condition to guarantee that the recordings would be aligned between the two devices by using event markers in the Biopac at the exact time that the Apple Watch Breathe app began and ended. We assessed test validity using the Bland–Altman method, and both precision and accuracy were estimated using Lin’s concordance correlation coefficient. The highest level of agreement and concordance between devices occurred during rest. We observed near-perfect agreement for R-R intervals and beats per minute (BPM) measures, with mean absolute percentage errors (MAPE) of 1.15% during resting conditions. We observed moderate levels of agreement and concordance for N-N intervals at rest with a MAPE of 31.31% during resting conditions. The Apple Watch provides a high level of validity for measuring R-R intervals and BPM in healthy adults. Further research is needed to determine if HRV measures with the Apple Watch offer a significant opportunity for the surveillance of CVD risk. Full article

In order to address the issue of heart rate susceptibility to motion artifacts (MAs) when extracting it from photoplethysmography (PPG) signals, a heart rate estimation algorithm based on the finite state machine (FSM) is proposed. The algorithm first applies band-pass filtering to the PPG and three-axis acceleration signals. The strength of MA is assessed based on the acceleration data. If a strong MA is detected, recursive least squares (RLS) filtering is applied; otherwise, it is omitted. Then, the signal is subjected to an empirical wavelet transform (EWT). Based on the EWT results, the current state is identified, and the corresponding spectral peak screening method is selected to estimate the heart rate. The mean absolute errors of the algorithm on 12 sets of public data and 8 sets of testing data are 0.93 and 1.76 beats per minute (bpm), respectively. The results of the experiment show that compared with other dominant algorithms, the proposed algorithm estimates heart rate with a smaller mean absolute error and can extract heart rate more effectively. Full article

A 67-year-old man started treatment due to frequent asymptomatic premature ventricular complexes (PVCs) accidentally being registered during a preventive examination by a specialist, because of which he was referred to cardiologist. During the initial 24-hour (h) ECG monitoring, 4.5% PVCs and one episode of asymptomatic non-sustained ventricular tachycardia (NSVT) with three PVCs in row, at a frequency of 150 beats per minute (bpm), were detected. After the introduction of beta blockers into therapy, a lower number of PVCs, without NSVT, were recorded in the control 24 h Holter ECG, while transthoracic echocardiography (TTE) showed normal left ventricular (LV) systolic function without cardiomyopathy. So, an exercise test was indicated, and it was interrupted in the third minute at 120 beats per minute (bpm) due to fatigue and pain in the hips, without malignant arrhythmias, angina or dyspneic complaints. During the rest period, a significant inferolateral depression of the ST junction was observed, which recovered in the ninth minute. Immediately after the ECG monitoring stopped, the patient lost consciousness; his pulse was not palpable, but breathing was audible, so cardiac massage was started. After he had regained consciousness, the ECG showed alternating sinus and junctional rhythm with the lowest frequency of 33 bpm, which was accompanied by marked hypotension (80/50 mmHg). The patient was immediately hospitalized; coronary angiography and repeated TTE were completely normal, while continuous ECG monitoring did not confirm malignant rhythm disorders or asystole. It was concluded that it was vasovagal syncope (VVS), most likely caused by the Bezold–Jarisch reflex (BJR). Full article

Background: The outstanding capabilities of modern Positron Emission Tomography (PET) to highlight small tumor lesions and provide pathological function assessment are at peril from image quality degradation caused by respiratory and cardiac motion. However, the advent of the long axial field-of-view (LAFOV) scanners with increased sensitivity, alongside the precise time-of-flight (TOF) of modern PET systems, enables the acquisition of ultrafast time resolution images, which can be used for estimating and correcting the cyclic motion. Methods: 0.25 s so-called [¹⁸F]FDG PET histo image series were generated in the scope of for detecting respiratory and cardiac frequency estimates applicable for performing device-less data-driven gated image reconstructions. The frequencies of the cardiac and respiratory motion were estimated for 18 patients using Short Time Fourier Transform (STFT) with 20 s and 30 s window segments, respectively. Results: The Fourier analysis provided time points usable as input to the gated reconstruction based on eight equally spaced time gates. The cardiac investigations showed estimates in accordance with the measured pulse oximeter references (p = 0.97) and a mean absolute difference of 0.4 ± 0.3 beats per minute (bpm). The respiratory frequencies were within the expected range of 10–20 respirations per minute (rpm) in 16 out of 18 patients. Using this setup, the analysis of three patients with visible lung tumors showed an increase in tumor SUV_max and a decrease in tumor volume compared to the non-gated reconstructed image. Conclusions: The method can provide signals that were applicable for gated reconstruction of both cardiac and respiratory motion, providing a potential increased diagnostic accuracy. Full article

This paper proposes a new approach for wide angle monitoring of vital signs in smart home applications. The person is tracked using an indoor radar. Upon detecting the person to be static, the radar automatically focuses its beam on that location, and subsequently breathing and heart rates are extracted from the reflected signals using continuous wavelet transform ($CWT$) analysis. In this way, leveraging the radar’s on-chip processor enables real-time monitoring of vital signs across varying angles. In our experiment, we employ a commercial multi-input multi-output (MIMO) millimeter-wave FMCW radar to monitor vital signs within a range of $1.15$ to $2.3$ m and an angular span of $-44.8$ to $+44.8$ deg. In the Bland–Altman plot, the measured results indicate the average difference of $-1.5$ and $0.06$ beats per minute (BPM) relative to the reference for heart rate and breathing rate, respectively. Full article

The aim of this study was to verify the accuracy of predicting oxygen consumption (O₂) in predominantly aerobic activities based on net heart rate (netHR), sex, and body mass index (BMI) in active adults. NetHR is the value of the difference between the resting HR (HR_rest) and the average HR value obtained during a given session or period of physical activity. These activities must be continuous, submaximal, and of a stabilized intensity. The magnitude of the netHR depends mainly on the intensity of the exercise. The HR is measured in beats per minute (bpm). A total of 156 participants, 52 women and 104 men, between the ages of 18 and 81, had their netHR and net oxygen intake (netVO₂) assessed. There were 79 participants in group 1 (prediction sample) (52 males and 27 females). There were 77 people in group 2 (validation sample) (52 males and 25 females). The results of the multiple linear regression showed that netVO₂ (R² = 85.2%, SEE = 3.38) could be significantly predicted by sex (p < 0.001), netHR (p < 0.001), and BMI (p < 0.001). The Bland–Altman plots satisfied the agreement requirements, and the comparison of the measured and estimated netVO₂ revealed non-significant differences with a trivial effect size. We calculated the formula NetVO₂ (mL/(kg·min)) = 16 + 3.67 (sex) + 0.27 (netHR) − 0.57 (BMI) to predict netVO₂, where netVO₂ is the amount of oxygen uptake (mL/(kg·min)) above the resting value, netHR is the heart rate (beats per minute) above the resting value measured during exercise, sex is equal to zero for women and one for men, and BMI is the body mass index. In addition, based on the knowledge of VO₂, it was possible to estimate the energy expenditure from a particular training session, and to determine or prescribe the exercise intensity in MET (metabolic equivalent of task). Full article

Heart rate is a key vital sign that can be used to understand an individual’s health condition. Recently, remote sensing techniques, especially acoustic-based sensing, have received increasing attention for their ability to non-invasively detect heart rate via commercial mobile devices such as smartphones and smart speakers. However, due to signal interference, existing methods have primarily focused on monitoring a single user and required a large separation between them when monitoring multiple people. These limitations hinder many common use cases such as couples sharing the same bed or two or more people located in close proximity. In this paper, we present an approach that can minimize interference and thereby enable simultaneous heart rate monitoring of multiple individuals in close proximity using a commonly available smart speaker prototype. Our user study, conducted under various real-life scenarios, demonstrates the system’s accuracy in sensing two users’ heart rates when they are seated next to each other with a median error of 0.66 beats per minute (bpm). Moreover, the system can successfully monitor up to four people in close proximity. Full article

This study aims to analyze the agreement of cardiopulmonary variables between a cardiopulmonary exercise test with elastic resistance (CPxEL) and high-intensity interval exercise with elastic resistance (EL-HIIE). Methods: Twenty-two physically independent participants were recruited. Visit one consisted of conducting a health survey and anthropometric assessment. On visit two, the participants performed CPxEL. After seven days, on visit three, the participants performed EL-HIIE. The CPxEL was carried out on a rubber mat demarcated by lines representing eight stages. The test consisted of alternating back and forth steps against elastic resistance. The increments were performed at a rate of one stage per minute, following a cadence controlled by a metronome calibrated by beats per minute (bpm). The EL-HIIE was performed at the stage corresponding to an intensity of ~85% VO_2max, as determined by CPxEL. The EL-HIIE consisted of 10 × 1 min (work):1 min (passive rest), with a cadence of 200 bpm. Cardiopulmonary parameters, heart rate (HR), and oxygen consumption (VO₂) were measured during exercise. Bland–Altman was applied to analyze the agreement between the HR and VO₂ found in EL-HIIE and the values prescribed by CPxEL (~85–90% VO_2max). Results: The HRpeak and VO₂peak in the EL-HIIE showed good agreement with the VO_2CPxEL and HR_CPxEL values, showing an average difference of (−1.7 mL·kg⁻¹·min⁻¹) and (0.3 bpm). Conclusions: The results of the present study demonstrate the agreement of cardiopulmonary variables between the CPxEL and the EL-HIIE. Therefore, for a more specific prescription of EL-HIIE intensity, CPxEL can be used. Full article

Objective: This study aims to evaluate image quality in patients with heart rates above or equal to 70 beats per minute (bpm), performed on a 16 cm scanner (256-slice General Electric Revolution) in comparison to a CT scanner with only 4 cm of coverage (64 slice Volume CT). Background: Recent advancements in image acquisition, such as whole-heart coverage in a single rotation and post-processing methods in coronary computed tomographic angiography (CCTA), include motion-correction algorithms, such as SnapShot Freeze (SSF), which improve temporal resolution and allow for the assessment of coronary artery disease (CAD) with lower motion scores and better image qualities. Studies from the comprehensive evaluation of high temporal- and spatial-resolution cardiac CT using a wide coverage system (CONVERGE) registry (a multicenter registry at four centers) have shown the 16 cm CT scanner having a better image quality in comparison to the 4 cm scanner. However, these studies failed to include patients with undesirable or high heart rates due to well-documented poor image acquisition on prior generations of CCTA scanners. Methods: A prospective, observational, multicenter cohort study comparing image quality, quantitively and qualitatively, on scans performed on a 16 cm CCTA in comparison to a cohort of images captured on a 4 cm CCTA at four centers. Participants were recruited based on broad inclusion criteria, and each patient in the 16 cm CCTA arm of the study received a CCTA scan using a 256-slice, whole-heart, single-beat scanner. These patients were then matched by age, gender, and heart rate to patients who underwent CCTA scans on a 4 cm CT scanner. Image quality was graded based on the signal-to-noise ratio, contrast-to-noise ratio, and on a Likert scale of 0–4: 0, very poor—4, excellent. Results: 104 patients were evaluated for this study. The mean heart rate was 75 ± 7 in the 4 cm scanner and 75 ± 7 in the 16 cm one (p = 0.426). The signal-to-noise and contrast-to-noise ratios were higher in the 16 cm scanner (p = 0.0001). In addition, more scans were evaluated as having an excellent quality on the 16 cm scanner than on the 4 cm scanner (p < 0.0001) based on a 4-point Likert scale. Conclusions: The 16 cm scanner has a superior image quality for fast heart rates compared to the 4 cm scanner. This study shows that there is a significantly higher frequency of excellent and good studies showing better contrast-to-noise and signal-to-noise ratios with the 16 cm scanner compared to the 4 cm scanner. Full article

Background: Heart rate (HR) is considered the main vital sign in newborns during perinatal transition, with a threshold of 100 beats per minute (bpm), below which, intervention is recommended. However, recent changes in delivery room management, including delayed cord clamping, are likely to have influenced normal HR transition. Objective: To summarize the updated knowledge about the factors, including measurement methods, that influence HR in newborn infants immediately after birth. Additionally, this paper provides an overview of delivery room HR as a prognostic indicator in different subgroups of newborns. Methods: We searched PubMed, EMBASE, and Google Scholar with the terms infant, heart rate, delivery room, resuscitation, pulse oximetry, and electrocardiogram. Results: Seven studies that described HR values in newborn infants immediately after birth were included. Pulse oximetry-derived HR percentiles after immediate cord clamping may not be applicable to the current practice of delayed cord clamping and the increasing use of delivery room electrocardiograms. Mask ventilation may adversely affect HR, particularly in premature and non-asphyxiated infants. Prolonged bradycardia is a negative prognostic factor, especially if combined with hypoxemia in infants <32 weeks of gestation. Conclusions: HR assessment in the delivery room remains important. However, the cardiopulmonary transition is affected by delayed cord clamping, gestational age, and underlying conditions. Full article

Unobtrusive monitoring of children’s heart rate (HR) and respiratory rate (RR) can be valuable for promoting the early detection of potential health issues, improving communication with healthcare providers and reducing unnecessary hospital visits. A promising solution for wireless vital sign monitoring is radar technology. This paper presents a novel approach for the simultaneous estimation of children’s RR and HR utilizing ultra-wideband (UWB) radar using a deep transfer learning algorithm in a cohort of 55 children. The HR and RR are calculated by processing radar signals via spectrogram from time epochs of 10 s (25 sample length of hamming window with 90% overlap) and then transforming the resultant representation into 2-dimensional images. These images were fed into a pre-trained Visual Geometry Group-16 (VGG-16) model (trained on ImageNet dataset), with weights of five added layers fine-tuned using the proposed data. The prediction on the test data achieved a mean absolute error (MAE) of 7.3 beats per minute (BPM < 6.5% of average HR) and 2.63 breaths per minute (BPM < 7% of average RR). We also achieved a significant Pearson’s correlation of 77% and 81% between true and extracted for HR and RR, respectively. HR and RR samples are extracted every 10 s. Full article

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. Full article