Search Results (42)

Real-time simultaneous monitoring of cardiac and respiratory signals in wearable systems remains challenging due to motion artifacts under varying body postures. This paper proposes an edge wearable integrated with novel methods to acquire and process cardiac and respiratory signals simultaneously from the chest. For respiration monitoring, the system captures chest motion using an IMU and applies dynamic filtering with real-time axis selection in a custom mobile application. It automatically selects the best respiratory axis from six IMU vectors: x, y, z, xy, yz, and zx, improving robustness across body postures and device placements. The proposed system can also capture and process electrocardiogram (ECG) data simultaneously for cardiac monitoring. Cardiac and respiration data were taken from eight healthy subjects, including males and females, followed by five protocols. The overall mean absolute error (MAE) for eight subjects is found to be 0.64 breath per minute (BrPM) after validation by a commercial sensor. In real time, the wearable continuously provides ECG and breathing signal streaming, ECG beat detection, and cardiac and breathing rates with an overall latency of 13.8 ms. The results indicate that the system can monitor the cardio-respiratory signals in real time under static and light-movement conditions. Full article

Rapid eye movement sleep (REM) is a critical sleep stage associated with several sleep disorders, including sleep apnea and rapid eye movement sleep behavior disorder. Polysomnography (PSG) is the gold standard for identifying REM periods and diagnosing sleep disorders. However, PSG is typically conducted in sleep medicine centers using specialized equipment, where sleep experts assess sleep conditions through measurements such as brain activity, respiration, heart activity, and eye movements. An overnight stay in a sleep laboratory can adversely affect a patient’s natural sleep quality, introducing the risk of iatrogenic sleep disturbances. Recent studies have explored sleep stage detection using lightweight wearable devices, such as smartwatches, which offer lower cost but rely on a limited set of psychological signals. In this study, we propose a machine learning approach for REM sleep staging based solely on breathing rate (BR) and heart rate (HR), without relying on PSG recordings. Experimental evaluations conducted on the Dreamt dataset demonstrate the feasibility of the proposed approach and its potential to provide meaningful information for sleep staging. Future work will focus on developing a fully non-contact REM detection framework by integrating video-based estimation of HR and BR. Full article

This paper proposes a low-cost measurement system that can be used to perform simultaneous blood pressure (BP) and breathing (BR) measurements. Regarding BP measurements, the main parameters that are accessed include systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure blood pressure (MAP), and heartbeat rate (HR). Concerning BR measurements, the main parameters that are accessed include the inspiration period and amplitude (IPA), the expiration period and amplitude (EPA), and the breathing rate (BR), as well as the statistical and standard deviation of all these parameters. The dual measurement capability of the proposed measurement system is very important since blood pressure and breathing parameters are not statistically independent and it is possible to obtain additional and valuable clinical information from the information provided by both biomedical variables when measured simultaneously. The analysis of the correlation between these variables is particularly important after performing intensive physical exercises, since it enables cardiac rehabilitation assessment, pre-surgical risk evaluation, detection of silent ischemia, and monitoring of chronic diseases recovery, among others. Regarding the performance evaluation of the proposed biomedical device, a prototype of the measurement system was developed, tested, and calibrated. Several experimental tests were carried out to evaluate the performance of the proposed measurement system and to obtain the correlation coefficients between different blood pressure and breathing parameters. The tests were based on a statistically significant number of measurements that were performed with a population that integrated twenty students in two groups with different habits of physical exercise practice but subjected to a set of common physical exercises, with graduated intensity levels. Full article

Many commercial wearable sensor systems typically rely on a single continuous cardiorespiratory sensing modality, photoplethysmography (PPG), which suffers from inherent biases (i.e., differences in skin tone) and noise (e.g., motion and pressure artifacts). In this research, we present a wearable device that provides robust estimates of cardiorespiratory variables by combining three physiological signals from the upper arm: multiwavelength PPG, single-sided electrocardiography (SS-ECG), and bioimpedance plethysmography (BioZ), along with an inertial measurement unit (IMU) providing 3-axis accelerometry and gyroscope information. We evaluated the multimodal device on 16 subjects by its ability to estimate heart rate (HR) and breathing rate (BR) in the presence of various static and dynamic noise sources (e.g., skin tone and motion). We proposed a hierarchical approach that considers the subject’s skin tone and signal quality to select the optimal sensing modality for estimating HR and BR. Our results indicate that, when estimating HR, there is a trade-off between accuracy and robustness, with SS-ECG providing the highest accuracy (low mean absolute error; MAE) but low reliability (higher rates of sensor failure), and PPG/BioZ having lower accuracy but higher reliability. When estimating BR, we find that fusing estimates from multiple modalities via ensemble bagged tree regression outperforms single-modality estimates. These results indicate that multimodal approaches to cardiorespiratory monitoring can overcome the accuracy–robustness trade-off that occurs when using single-modality approaches. Full article

The effect of ambient temperature on various physiological parameters were obtained to determine the upper critical temperature (UCT) in Iberian pigs. After an adaptation period at 28 °C, eight barrows (99 kg) were individually moved to two respirometry chambers and fed ad libitum (standard diet). The heat production (HP) and respiratory quotient (RQ) were measured over 24 h and some physiological parameters were measured every two days at 24, 26, 28, 30 and 32 °C. No differences (p > 0.05) were found in the heart rate (HR; 97.7 beats/min) and rectal temperature (RT; 39.7 °C) between ambient temperatures. Breathing rate (BR) and skin temperature (ST) increased (272 and 2.4%, respectively; p < 0.05) along with the temperature; whereas voluntary feed intake (VFI), retained energy (RE) and respiratory quotient (RQ) decreased (40.3, 65.8 and 10.5%, respectively; p < 0.001). Overall, HP slightly decreased (19.2%; p < 0.01) when the temperature increased. The reduction in RE when the temperature increased was related more to the decrease in VFI rather than to the concomitant reduction in HP. The UCT can be established at 28 for BR, 30 for VFI and RE, and 32 °C for ST, HP and RQ. Overall, the UCT was stablished at 28–30 °C, indicating the good adaptation of Iberian pigs to heat. Full article

Monitoring heart rate (HR) is vital for health management and athletic performance, and wearable technology enables scientists to obtain real-time cardiovascular insights. This study compares Machine Learning (ML) techniques, including Long Short-Term Memory (LSTM) networks, Physics-Informed Neural Networks (PINNs), and 1D Convolutional Neural Networks (1D CNNs). Then, we develop a hybrid Singular Spectrum Analysis (SSA)-Augmented ML technique to predict HR using wearable sensor data. Additionally, we investigate the impact of incorporating auxiliary physiological inputs, such as breathing rate (BR) and RR intervals, on predictive accuracy. The study utilizes the cardiorespiratory data acquired through wearable sensors while practising sports, including 126 recordings from 81 participants (53 males, 28 females) engaged in 10 different sports. Physiological signals were collected at 1 Hz using the BioHarness 3.0 (Zephyr Technology, Mangaluru, India). The dataset includes individuals with varied levels of sports experience (beginner, intermediate, and advanced), allowing for a more comprehensive evaluation of HR variability across different expertise levels. Our results demonstrate that the hybrid SSA-LSTM model reaches the lowest prediction error by effectively capturing HR dynamics. Furthermore, integrating HR, BR, and RR data significantly enhances accuracy over single or dual parameter inputs. These findings support adopting multivariate machine learning models for health monitoring, improving HR prediction accuracy for fitness and preventive healthcare. Full article

Objective: To investigate the cut-off value of the breathing reserve for predicting a decline in cardiorespiratory fitness (CRF) among healthy middle-aged Chinese individuals. Methods: Healthy middle-aged individuals who underwent cardiopulmonary exercise testing (CPET) at the Peking University Third Hospital from May to October 2021 were selected. The study included 321 participants, with an average age of 48.8 ± 5.7 years. They were divided into two groups based on the peak oxygen uptake (VO₂peak): the adequate CRF group and the CRF decline group. Multivariate logistic regression analysis was used to explore the factors influencing CRF. Results: In the male CRF decline group, heart rate, alanine aminotransferase, end-tidal partial pressure of carbon dioxide (PETCO₂), and breathing reserve (BR%) were significantly higher, while the oxygen uptake at the anaerobic threshold (VO₂@AT) was lower. An elevated BR% was independently associated with CRF decline (OR = 1.111, 95% CI: 1.068–1.156). The female CRF decline group had significantly higher FEV1/FVC and BR% and significantly lower age, fasting glucose, hemoglobin, and VO₂@AT compared to the adequate CRF group. Elevated BR% was independently associated with CRF decline (OR = 1.086, 95% CI: 1.038–1.137). The receiver operating characteristic (ROC) curve for the males showed an area under the curve (AUC) of 0.769 (95% CI: 0.703–0.827) with an appropriate BR% cut-off value of 49.9%, sensitivity of 59.9%, and specificity of 77.8%. For the females, the ROC curve displayed an AUC of 0.694 (95% CI: 0.607–0.773) with an appropriate BR% cut-off value of 57.0%, sensitivity of 58.7%, and specificity of 86.0%. Conclusions: The breathing reserve was independently associated with CRF. The appropriate cut-off values for BR% to predict CRF decline were 49.9% for the males and 57.0% for the females. Full article

This study aims to decrease the number of drunk drivers, a significant social problem. Traditional methods to measure alcohol intake include blood alcohol concentration (BAC) and breath alcohol concentration (BrAC) tests. While BAC testing requires blood samples and is impractical, BrAC testing is commonly used in drunk driving enforcement. In this study, the multiple biological signals of electrocardiogram (ECG), photoplethysmogram (PPG), and electrodermal activity (EDA) were collected non-invasively and with minimal driver restraint in a driving simulator. Data were collected from 10 participants for approximately 10 min at BrAC levels of 0.00%, 0.03%, and 0.08%, which align with the latest Korean drunk driving standards. The collected data underwent frequency filtering and were segmented into 30 s intervals with a 10 s overlap to extract heart rate variability (HRV) and pulse arrival time (PAT). Using more than 10 machine learning algorithms, the classification accuracy reached 88%. The results indicate that it is possible to classify a driver’s level of intoxication using only non-invasive biological signals within a short period of about 30 s, potentially aiding in the prevention of drunk driving. Full article

Background: Impairment in autonomic activity is a prognostic marker in patients with heart failure (HF), and its involvement has been suggested in cardiovascular complications of obstructive sleep apnea syndrome (OSAS) and Cheyne–Stokes respiration (CSR). This prospective observational study aims to investigate the implications of sleep-disordered breathing (SDB) on hemodynamic regulation and autonomic activity in chronic HF patients. Methods: Chronic HF patients, providing confirmation of reduced ejection fraction (≤35%), underwent polysomnography, real-time hemodynamic, heart rate variability (HRV), and baroreceptor reflex sensitivity (BRS) assessments using the Task Force Monitor. BRS was assessed using the sequencing method during resting conditions and stress testing. Results: Our study population (n = 58) was predominantly male (41 vs. 17), with a median age of 61 (±11) yrs and a median BMI of 30 (±5) kg/m². Patients diagnosed with CSR were 13.8% (8/58) and 50.0% (29/58) with OSAS. No differences in the real-time assessment of hemodynamic regulation, heart rate variability, or baroreceptor reflex function were found between patients with OSAS, CSR, and patients without SDB. A subgroup analysis of BRS and HRV in patients with severe SDB (AHI > 30/h) and without SDB (AHI < 5) revealed numerically reduced BRS and increased LF/HF-RRI values under resting conditions, as well as during mental testing in patients with severe SDB. Patients with moderate-to-severe SDB had a shorter overall survival, which was, however, dependent upon age. Conclusions: Chronic HF patients with severe SDB may exhibit lower baroreceptor function and impaired cardiovascular autonomic function in comparison with HF patients without SDB. Full article

Background: Catheter ablation (CA) is a well-established treatment for atrial fibrillation (AF). However, its effects on autonomic function and underlying mechanisms remain poorly understood. This study investigated autonomic and haemodynamic changes following CA and explored their potential implications for patient outcomes. Methods: Seventy-eight patients with AF underwent CA and were followed up at one, three, and six months. Autonomic function was assessed using a combination of head-up tilt (HUT), handgrip (HG), and deep breathing (DB) manoeuvres along with baroreflex sensitivity (BRS) and baroreflex effectiveness index (BEI) evaluation. Heart rate (HR), blood pressure (BP), and their variability were measured at each time point. Results: Significant autonomic alterations were observed after ablation, particularly at one month, with reductions in parasympathetic tone and baroreflex function. These changes gradually normalised by six months. Both pulmonary vein isolation (PVI) and cryoablation (CryO) had similar effects on autonomic regulation. Improvements in quality of life, measured by the AFEQT scores, were consistent with these physiological changes. Conclusions: CA for AF induces significant time-dependent autonomic and haemodynamic changes with recovery over six months. These findings underscore the need for ongoing monitoring and personalised post-ablation management. Further research is required to explore the mechanisms driving these alterations and their long-term impacts on patient outcomes. Full article

Background/Objectives: To assess free-breathing, dynamic radial magnetic resonance angiography (MRA) for detecting endoleaks post-endovascular aortic repair (EVAR) in cases with inconclusive computed tomography angiography (CTA). Methods: This prospective single-center study included 17 participants (mean age, 70 ± 9 years; 13 males) who underwent dynamic radial MRI (Golden-angle RAdial Sparse Parallel-Volumetric Interpolated BrEath-hold, GRASP-VIBE) after inconclusive multiphasic CT for the presence of endoleaks during the follow-up of EVAR-treated abdominal aortic aneurysms. CT and MRI datasets were independently assessed by two radiologists for image quality, diagnostic confidence, and the presence/type of endoleak. Statistical analyses included interrater and intermethod agreement, and diagnostic performance (sensitivity, specificity, area under the curve (AUC)). Results: Subjective image analysis demonstrated good image quality and interrater agreement (k ≥ 0.6) for both modalities, while diagnostic confidence was significantly higher in MRA (p = 0.03). There was significantly improved accuracy for detecting type II endoleaks on MRA (AUC 0.97 [95% CI: 0.87, 1.0]) compared to CTA (AUC 0.66 [95% CI: 0.41, 0.91]; p = 0.03). Although MRA demonstrated higher values for sensitivity, specificity, AUC, and interrater agreement, none of the other types nor the overall detection rate for endoleaks showed differences in the diagnostic performance over CT (p ≥ 0.12). CTA and MRA revealed slight to moderate intermethod concordance in endoleak detection (k = 0.3–0.64). Conclusions: The GRASP-VIBE MRA characterized by high spatial and temporal resolution demonstrates clinical feasibility with good image quality and superior diagnostic confidence. It notably enhances diagnostic performance in detecting and classifying endoleaks, particularly type II, compared to traditional multiphase CTA with inconclusive findings. Full article

Heart rate variability (HRV), systolic blood pressure variability (BPV), and spontaneous baroreflex sensitivity (BRS) are indirect and approximate measures of autonomic regulation of the cardiovascular system. Studies have shown differences in HRV and BRS between males and females; however, no study has observed differences in BPV, HRV, or BRS between male and female athletes. One hundred males (age 21.2 ± 2.1 y; BMI 27.4 ± 4.5 kg/m²) and sixty-five females (age: 19.7 ± 1.6 y; BMI 22.7 ± 2.2 kg/m²) were assessed during the pre-season baseline. We collected resting beat-to-beat blood pressure and R-R intervals using finger photoplethysmography and a 3-lead electrocardiogram, respectively. Participants underwent a controlled slow breathing protocol (six breaths/minute: 5 s inhale, 5 s exhale) for 5 min. Spectral and linear analysis was conducted on blood pressure and ECG data. Regression curves were fitted to the blood pressure and R-R signals, with the slopes providing the BRS parameters. Male athletes had significantly (p < 0.05) lower mean heart rate, RR interval SD2/SD1, HRV % low-frequency, and higher BP high-frequency power during controlled respiration. No differences were found in any BRS parameters. HRV and BPV responses to a slow breathing protocol differed between male and female athletes; however, BRS responses did not. Full article

Smokefree laws are intended to protect against second-hand smoke (SHS) in outdoor areas. We examined if exposure to PM2.5 particles in outdoor smoking areas changed breathing rates in 60 patients with asthma (n = 30) or with COPD (n = 30), in an open, non-randomised, interventional study model in Czechia, Ireland and Spain. The patients wore a PM2.5 particle monitor (AirSpeck) and a breath monitor (RESpeck) for 24 h to determine changes in breathing rates (Br) at rest and during a visit to an outside smoking area. Spirometry and breath CO were measured before and the day after visiting an outdoor smoking area. The PM2.5 levels at the 60 venues were highly variable, ranging from ≥2000 µg/m³ (in 4 premises) to ≤10 µg/m³ (in 3 premises, which had only a single wall in the structure). At 39 venues, the mean PM 2.5 levels were ≥25 µg/m³. The breathing rate changed significantly in 57 of the 60 patients, resulting in an increase in some patients and a decrease in others. Comprehensive smokefree laws were ineffective in protecting asthma and COPD patients from exposure to high levels of SHS in outside areas of pubs and terraces, which should be avoided by these patients. These findings also support the extension of smokefree laws to outside areas. Full article

Sub-maximal physical load (sub-max) training is optimal for athletes. However, few methods can directly assess whether training is sub-max. Therefore, this study aimed to identify metrics that could assess sub-max training by predicting maximal physical load, helping athletes to avoid the risks associated with maximal training. Physiological data were collected from 30 participants in a bicycle incremental exercise experiment, including the R-R interval (RR), stroke volume (SV), breath-to-breath interval (BB), and breathing rate (BR). Sample Entropy (SampEn) analysis was used to assess the complexity of the physiological data. BR increased with exercise time but could not be used to identify the sub-max stage; however, SampEn BB could effectively identify the sub-max stage (p < 0.05), as could the novel indicators SampEn SV and cardiac output (p < 0.01). This study also identified the threshold value of each SampEn value in sub-max, which can be used as a sports science indicator to assess the load of athletes. The results suggest that SampEn-based indicators can be used to assess sub-max and maximal physical load. These findings can be used as a guide for quantitative exercise healthcare. Full article

Abnormalities in cardiorespiratory measurements have repeatedly been found in patients with panic disorder (PD) during laboratory-based assessments. However, recordings performed outside laboratory settings are required to test the ecological validity of these findings. Wearable devices, such as sensor-imbedded garments, biopatches, and smartwatches, are promising tools for this purpose. We systematically reviewed the evidence for wearables-based cardiorespiratory assessments in PD by searching for publications on the PubMed, PsycINFO, and Embase databases, from inception to 30 July 2022. After the screening of two-hundred and twenty records, eight studies were included. The limited number of available studies and critical aspects related to the uncertain reliability of wearables-based assessments, especially concerning respiration, prevented us from drawing conclusions about the cardiorespiratory function of patients with PD in daily life. We also present preliminary data on a pilot study conducted on volunteers at the Villa San Benedetto Menni Hospital for evaluating the accuracy of heart rate (HR) and breathing rate (BR) measurements by the wearable Zephyr BioPatch compared with the Quark-b2 stationary testing system. Our exploratory results suggested possible BR and HR misestimation by the wearable Zephyr BioPatch compared with the Quark-b2 system. Challenges of wearables-based cardiorespiratory assessment and possible solutions to improve their reliability and optimize their significant potential for the study of PD pathophysiology are presented. Full article