Search Results (107)

Background: Self-report physical activity (PA) scales, accelerometry, and heart rate (HR) monitoring are reliable tools for PA measurement for children with cerebral palsy (CP); however, there are limitations for those who are primary wheelchair users. The purpose of our study was to evaluate face and construct validity of the PROMIS^® Pediatric PA parent proxy short form 8a in measuring PA amount and intensity in children with CP who are non-ambulatory. Methods: Face validity: Semi-structured interviews with parents and pediatric physical therapists (PTs) were conducted about the appropriateness of each item on the PROMIS^® Pediatric PA short form. Construct validity: Children with CP who were non-ambulatory participated in a one-week observational study. PA amount and intensity were examined using PA monitors (Actigraph GT9X) and HR monitors (Fitbit Charge 4). Activity counts and time in sedentary and non-sedentary intensity zones were derived and compared to the PROMIS^® T-scaled score. Results: Twenty-two physical therapists (PTs) and fifteen parents participated in the interviews, and ten children completed 1-week PA observation. Eight and seven participants completed sufficient time of uninterrupted PA and HR monitor wear, respectively. Parents and PTs agreed that several questions were not appropriate for children with CP who were non-ambulatory. PA intensity via activity counts derived from wrist worn monitors showed a strong positive correlation with the PROMIS^® PA measure. Conclusions: Construct validity in our small sample was established between PROMIS^® scores and accelerometry activity counts when documenting PA amount and intensity; however, there were some differences on PROMIS^® face validity per parent and PT respondents. Despite some concerns regarding face validity, the PROMIS^® Pediatric PA parent proxy short form 8a shows promise as a valid measure of physical activity amount and intensity in non-ambulatory children with CP, warranting further investigation and refinement. Full article

To elucidate the changes in gas exchange across the life course, we estimated the age trajectories of O₂ saturation, CO₂ (as either end-tidal or serum bicarbonate), resting heart rate, and resting respiratory rate from age 2 yr onward in female and male patients separately. We utilized two sources’ data: electronic health records (EHR) representing ambulatory visits of approximately 53,000 individuals and sleep clinic polysomnogram (PSG) records representing an additional ~21,000. We used linear regression to estimate age-group-specific mean response levels for women and men. We compared estimated female–male differences between pre- and post-pubertal children and between pre- and post-menopausal periods among adults. Women between 15 and 45 years had higher O₂ saturation and lower serum bicarbonate levels or end-tidal CO₂ levels than men of similar ages. For O₂ saturation and for both measures of CO₂, the female–male difference was larger on average among adults at pre-menopausal ages than those at post-menopausal ages. Women had higher O₂ saturation throughout their lives than men; however, the difference disappeared in the elderly. Women between menarche and menopause had significantly lower end-tidal CO₂ and serum bicarbonate than men of similar ages. After menopause, however, women appeared to have higher mean levels of both end-tidal CO₂ and serum bicarbonate than men. Full article

We present a hermetically sealed capacitive microelectromechanical system (MEMS) strain sensor designed for arterial pulse waveform extraction using the strain plethysmography (SPG) modality. The MEMS strain sensor features a small form factor of 3.3 mm × 3.3 mm × 1 mm, leverages a nano-gap fabrication process to improve the sensitivity, and uses a differential sensing mechanism to improve the linearity and remove the common mode drift. The MEMS strain sensor is interfaced with an application-specific integrated circuit (ASIC) to form a compact strain sensing system. This system exhibits a high strain sensitivity of 316 aF/µε, a gauge factor (GF) of 35, and a strain sensing resolution of 1.26 µε, while maintaining a linear range exceeding 700 µε. SPG signals have been reliably captured at both the fingertip and wrist using the MEMS strain sensor with high signal quality, preserving various photoplethysmography (PPG) features. Experimental results demonstrate that heart rate (HR) and heart rate variability (HRV) can be estimated from the SPG signal collected at the fingertip and wrist using the sensor with an accuracy of over 99%. Pulse arrival time (PAT) and pulse transit time (PTT) have been successfully extracted using the sensor together with a MEMS seismometer, showcasing its potential for ambulatory BP monitoring (ABPM) application. Full article

Background: Monitoring pulse rate is fundamental to cardiovascular health management and early detection of rhythm disturbances. While oscillometric blood pressure measurement is well established and validated in clinical practice, its use for pulse rate monitoring, particularly via wrist-worn devices, remains largely unexplored. Objective: This study investigates whether a smartwatch that performs oscillometric blood pressure measurements at the wrist can also deliver reliable pulse rate readings using the same method. Methods: This study compared pulse rates recorded by the Omron HeartGuide smartwatch and conventional ambulatory blood pressure monitors in 50 patients over 24 h. Measurements were taken consecutively, and data were analyzed using intraclass correlation coefficients (ICCs) and Bland–Altman plots. Results: The study showed a high ICC of 0.971, indicating excellent agreement between devices. The average pulse rate difference was 1.5 bpm, with the Omron HeartGuide reporting slightly lower rates, especially in patients with atrial fibrillation. Conclusions: This study demonstrates that oscillometric pulse-rate monitoring at the wrist can achieve a high degree of accuracy, comparable to conventional upper-arm devices. Given that oscillometric smartwatches like the Omron HeartGuide are already used for blood pressure monitoring, the findings suggest that they may also be suitable for pulse rate measurement, potentially enhancing their role in telemetric healthcare, but further research is needed, particularly in patients with arrhythmias. Full article

Atrial fibrillation (AF) is a type of cardiac arrhythmia with a worldwide prevalence of more than 37 million among the adult population. This elusive disease is a major risk factor for ischemic stroke, along with increased rates of significant morbidity and eventual mortality. It is clinically diagnosed using medical-grade electrocardiogram (ECG) sensors in ambulatory settings. The recent emergence of consumer-grade wearables equipped with photoplethysmography (PPG) sensors has exhibited considerable promise for non-intrusive continuous monitoring in free-living conditions. However, the scarcity of large-scale public PPG datasets acquired from wearable devices hinders the development of intelligent automatic AF detection algorithms unaffected by motion artifacts, saturated ambient noise, inter- and intra-subject differences, or limited training data. In this work, we present a deep learning framework that leverages convolutional layers with a bidirectional long short-term memory (CNN-BiLSTM) network and an attention mechanism for effectively classifying raw AF rhythms from normal sinus rhythms (NSR). We derive and feed heart rate variability (HRV) and pulse rate variability (PRV) features as auxiliary inputs to the framework for robustness. A larger teacher model is trained using the MIT-BIH Arrhythmia ECG dataset. Through transfer learning (TL), its learned representation is adapted to a compressed student model (32x smaller) variant by using knowledge distillation (KD) for classifying AF with the UMass and MIMIC-III datasets of PPG signals. This results in the student model yielding average improvements in accuracy, sensitivity, F1 score, and Matthews correlation coefficient of 2.0%, 15.05%, 11.7%, and 9.85%, respectively, across both PPG datasets. Additionally, we employ Gradient-weighted Class Activation Mapping (Grad-CAM) to confer a notion of interpretability to the model decisions. We conclude that through a combination of techniques such as TL and KD, i.e., pre-trained initialization, we can utilize learned ECG concepts for scarcer PPG scenarios. This can reduce resource usage and enable deployment on edge devices. Full article

Botulinum neurotoxin (BoNT) intoxication is a rare but severe condition that is characterized by autonomic and neuromuscular dysfunction. This study aimed to evaluate autonomic impairment and blood pressure variability in patients with botulinum intoxication during an outbreak, compared to healthy controls, and to assess their progression over a six-month follow-up period. Methods: Twenty (n = 20) male patients diagnosed with BoNT intoxication and 34 age- and sex-matched healthy controls were enrolled. At baseline, all subjects underwent 24 h ambulatory blood pressure monitoring (ABPM), and clinostatic and orthostatic blood pressure measurements. Autonomic function parameters, including mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP), SBP and DBP variability, SBP and DBP load, pulse pressure (PP), blood pressure variability ratio (BPVR), and morning surge, were analyzed. Follow-up assessments were conducted after six months. Results: Patients with botulinum intoxication exhibited significantly lower SBP, DBP, and blood pressure variability parameters compared to healthy controls. Orthostatic hypotension was present in 55% of patients at baseline, improving to 5% at follow-up. Respiratory failure occurred in 40% of cases, necessitating non-invasive ventilation in 35% and intubation in 20%. At six-month follow-up, mean SBP, DBP, heart rate, and blood pressure variability parameters increased significantly, indicating partial recovery of autonomic control. However, residual abnormalities in autonomic regulation persisted. Conclusions: BoNT intoxication leads to notable autonomic dysfunction, marked by impaired blood pressure regulation and a high prevalence of orthostatic hypotension. Although partial recovery occurs, long-term autonomic impairment persists, highlighting the necessity for ongoing cardiovascular monitoring and further research to accelerate autonomic recovery through targeted therapeutic interventions. Full article

Background/Objectives: Previously undiagnosed atrial fibrillation (PUAF) is a significant cause of embolic stroke of undetermined source (ESUS). This study aimed to determine whether early heart rhythm monitoring with a Holter ECG after acute stroke enhances the detection of PUAF compared to standard ambulatory monitoring in ESUS patients, assuming that early cardiac monitoring would lead to a higher detection rate of PUAF. Methods: This cohort study included 100 patients aged 50 and older diagnosed with ESUS and exhibiting sinus rhythm for at least 24 h. All participants were hospitalized in a stroke unit and underwent 48 h of Holter ECG monitoring. A group of 100 ESUS patients who underwent outpatient delayed Holter ECG monitoring served as controls. Results: This study revealed a significantly higher detection rate of AF in the hospitalized group compared to the outpatient group (20% vs. 5%; p = 0.001). The mean age and distribution of risk factors, including hypertension, diabetes, hyperlipidemia, ischemic heart disease, heart failure, chronic kidney disease, smoking, previous stroke, and malignancy, did not differ between the groups. There were no significant differences in initial stroke severity or in outcomes between the groups. Conclusions: Early Holter ECG monitoring in the hospitalized ESUS patients significantly increased the detection rate of PUAF compared to ambulatory monitoring, highlighting the importance of timely cardiac assessment in stroke management. Full article

Japan is facing challenges associated with its super-aging society, including increased social security burdens and a rise in the elderly workforce due to a declining younger labor force. Extending the healthy life expectancy is one countermeasure, necessitating lifestyle improvements such as frailty prevention and ensuring adequate sleep duration. This study investigated the relationship between heart rate variability (HRV) and sleep duration among older adults (aged ≥ 65) using electrocardiogram (ECG) and three-axis accelerometer data from the Allostatic State Mapping by the Ambulatory ECG Repository (ALLSTAR) database, recorded between January 2019 and March 2021. Inclusion criteria required a sinus rhythm and recording durations ≥80%. Continuous 24 h ECG and accelerometer data were analyzed for 55,154 participants (mean age 76 ± 6). The results consistently showed significant differences in HRV metrics, including MRRI, SDRR, ULF, LF, HF, and LF/HF, across sleep duration groups (G1–G4). Short-sleep groups (G4) exhibited decreased MRRI and SDRR and increased LF/HF, suggesting active lifestyles but reduced HRV. Conversely, long-sleep groups (G1) showed increased MRRI and reduced LF/HF but exhibited age-related declines in SDRR and ULF. These findings indicate that both insufficient and excessive sleep may contribute to HRV reduction in older adults. This study provides critical insights for improving elderly lifestyles through tailored interventions in exercise and sleep management. Full article

Background/Objectives: Post-infectious syndromes, including Post-COVID syndrome, Chronic Fatigue Syndrome, and late-stage Lyme disease, are associated with overlapping clinical features and autonomic dysfunction. Despite shared symptoms such as fatigue and orthostatic intolerance, the underlying pathophysiology and specific patterns of autonomic dysfunction may differ. This study aimed to evaluate and compare autonomic nervous system function in these syndromes using multiple diagnostic modalities to identify unique characteristics and improve differentiation between these conditions. Methods: This cross-sectional study included 758 patients, which were divided into four groups: Post-COVID syndrome, Chronic Fatigue Syndrome following Post-COVID syndrome, Chronic Fatigue Syndrome unrelated to COVID-19, and late-stage Lyme disease. Autonomic nervous system function was assessed using cardiovascular reflex tests, the Head-Up Tilt Test, beat-to-beat analysis, five-minute electrocardiogram recordings, 24 h Holter electrocardiogram monitoring, and 24 h ambulatory blood pressure monitoring. Statistical analyses compared parameters across the groups, focusing on patterns of sympathetic and parasympathetic dysfunction. Results: The patients with Lyme disease showed distinct autonomic patterns, including a higher prevalence of orthostatic hypotension (53.4%) and changes in heart rate variability during the Head-Up Tilt Test suggestive of adrenergic failure. Compared to the other groups, patients with Lyme disease exhibited reduced baroreceptor sensitivity and diminished changes in frequency domain heart rate variability parameters during orthostatic stress. Parasympathetic dysfunction was less prevalent in the Lyme disease group, while the Post-COVID syndrome and Chronic Fatigue Syndrome groups showed more pronounced autonomic imbalances. Conclusions: The patients with Post-COVID syndrome, Chronic Fatigue Syndrome, and late-stage Lyme disease exhibited varying degrees and types of autonomic dysfunction. Late-stage Lyme disease is characterized by adrenergic failure and distinct hemodynamic responses, differentiating it from other syndromes. The functional assessment of autonomic nervous system function could aid in understanding and managing these conditions, offering insights for targeted therapeutic interventions. Full article

Goals of automated detection of epileptic seizures using wearable devices include objective documentation of seizures, prevention of sudden unexpected death in epilepsy (SUDEP) and seizure-related injuries, obviating both the unpredictability of seizures and potential social embarrassment, and finally to develop seizure-triggered on-demand therapies. Automated seizure detection devices are based on the analysis of EEG signals (scalp-EEG, subcutaneous EEG and intracranial EEG), of motor manifestations of seizures (surface EMG, accelerometry), and of physiologic autonomic changes caused by seizures (heart and respiration rate, oxygen saturation, sweat secretion, body temperature). While the detection of generalized tonic-clonic and of focal to bilateral tonic-clonic seizures can be achieved with high sensitivity and low false alarm rates, the detection of focal seizures is still suboptimal, especially in the everyday ambulatory setting. Multimodal seizure detection devices in general provide better performance than devices based on single measurement parameters. Long-term use of seizure detection devices in home environments helps to improve the accuracy of seizure diaries and to reduce seizure-related injuries, while evidence for prevention of SUDEP is still lacking. Automated seizure detection devices are generally well accepted by patients and caregivers. Full article

Background/Objectives: Chronic fatigue syndrome and post-COVID-19 syndrome are associated with dysfunction of the autonomic nervous system, which may manifest as syncope and orthostatic intolerance. This study aimed to compare autonomic nervous system function in patients with chronic fatigue syndrome of unknown etiology and those with chronic fatigue syndrome secondary to post-COVID-19 syndrome using multiple diagnostic modalities, and to assess the prevalence and characteristics of syncope in these populations. Methods: This cross-sectional study included 440 patients examined at the Neurocardiological Laboratory of the Institute for Cardiovascular Diseases “Dedinje”. Patients were divided into three groups: chronic fatigue syndrome of unknown etiology (Group 1, n = 210), chronic fatigue syndrome secondary to post-COVID-19 syndrome (Group 2, n = 137), and healthy controls (Group 3, n = 91). Diagnostic modalities included cardiovascular reflex tests, the head-up tilt test, beat-to-beat analysis, 24 h Holter electrocardiogram monitoring, and 24 h ambulatory blood pressure monitoring. Statistical analyses were performed using analysis of variance, Tukey’s honestly significant difference test, and the Mann–Whitney U test. Results: Both chronic fatigue syndrome groups demonstrated significant autonomic nervous system dysfunction compared to healthy controls (p < 0.05), including reduced baroreceptor sensitivity and impaired heart rate variability parameters. Syncope prevalence was high in both chronic fatigue syndrome groups, with extreme blood pressure variability observed in 45–47% of patients during the head-up tilt test. Patients with post-COVID-19 chronic fatigue syndrome exhibited greater blood pressure increases during the head-up tilt test than those with chronic fatigue syndrome of unknown etiology (p < 0.05). Conclusions: Patients with chronic fatigue syndrome, irrespective of etiology, exhibit significant autonomic nervous system dysfunction and a high prevalence of syncope. Post-COVID-19 chronic fatigue syndrome demonstrates distinct hemodynamic patterns, suggesting unique pathophysiological mechanisms that warrant further investigation. Full article

Early assessment of respiratory mechanics is crucial for early-stage diagnosing and managing lung diseases, leading to greater patient outcomes. Traditional methods like spirometry are limited in continuous monitoring and patient compliance as they require forced maneuvers with significant patient cooperation, which may not be available in fragile individuals. The Forced Oscillation Technique (FOT) is a non-invasive measurement method, only based on the tidal breathing at rest from the patient for a limited time period. The proposed solution integrates low-frequency FOT with continuous monitoring using Equivital (EQV) sensors to enhance respiratory mechanics information with heart rate variability. Data were collected over a two-hour period from six healthy volunteers, measuring respiratory impedance every 7 min and continuously recording physiological parameters. The best-fitting fractional-order models for impedance data were identified using genetic algorithms. This study also explores the correlation between impedance model parameters and EQV data, discussing the potential of AI tools for forecasting respiratory properties. Our findings indicate that combined monitoring techniques and AI analysis provides additional complementary information, subsequently aiding the improved evaluation of respiratory function and tissue mechanics. The proposed protocol allows for ambulatory assessment and can be easily performed in normal breathing conditions. Full article

Background/Objectives: In Europe, the prevalence of AF is expected to increase 2.5-fold over the next 50 years with a lifetime risk of 1 in 3–5 individuals after the age of 55 years and a 34% rise in AF-related strokes. The PREFATE project investigates evidence gaps in the early detection of atrial fibrillation in high-risk populations within primary care. This study aims to estimate the prevalence of device-detected atrial fibrillation (DDAF) and assess the feasibility and impact of systematic screening in routine primary care. Methods: The prospective cohort study (NCT 05772806) included 149 patients aged 65–85 years, identified as high-risk for AF. Participants underwent 14 days of cardiac rhythm monitoring using the Fibricheck^® app (CE certificate number BE16/819942412), alongside evaluations with standard ECG and transthoracic echocardiography. The primary endpoint was a new AF diagnosis confirmed by ECG or Holter monitoring. Statistical analyses examined relationships between AF and clinical, echocardiographic, and biomarker variables. Results: A total of 18 cases (12.08%) were identified as positive for possible DDAF using FibriCheck^® and 13 new cases of AF were diagnosed during follow-up, with a 71.4-fold higher probability of confirming AF in FibriCheck^®-positive individuals than in FibriCheck^®-negative individuals, resulting in a post-test odds of 87.7%. Significant echocardiographic markers of AF included reduced left atrial strain (<26%) and left atrial ejection fraction (<50%). MVP ECG risk scores ≥ 4 strongly predicted new AF diagnoses. However, inconsistencies in monitoring outcomes and limitations in current guidelines, particularly regarding AF burden, were observed. Conclusions: The study underscores the feasibility and utility of AF screening in primary care but identifies critical gaps in diagnostic criteria, anticoagulation thresholds, and guideline recommendations. Full article

This study aimed to examine the acute and chronic effects of an exercising table tennis program on cardiac Autonomic Nervous System (ANS) and functional capacity in people with tetraplegia. Twenty males with tetraplegia (C6–C7), with a mean age of 38.50 ± 4.04 years old, were randomly assigned into two equal groups: A, who followed a 6-month exercise training program with table tennis 3 times per week, and B, who remained untrained. Additionally, 11 healthy sedentary men (group C) with a mean age of 39.71 ± 5.87 years old participated in the study as healthy controls. At baseline, all participants underwent a short-term (5 min) and a long-term (24 h ambulatory) ECG monitoring to evaluate the heart rate variability (HRV) indices and a maximal arm ergometric and dynamometric testing of the upper limbs. Moreover, the acute cardiac autonomic responses to maximal arm cycle exercise test were evaluated by Polar S810i sensor chest strap. At the end of the 6-month study, all parameters were revaluated only in groups A and B. At baseline, there was no statistically significant difference between the two patient groups. However, intra-group changes at the end of the 6-month study regarding the 24-h HRV monitoring indicated that group A statistically increased the standard deviation of R-R intervals (SDNN) by 13.9% (p = 0.007), the standard deviation of R-R intervals calculated every 5 min (SDANN) by 8.4% (p = 0.007), the very low frequency (VLF) by 7.1% (p = 0.042), and the low frequency [LF (ms²)] by 10.5% (p = 0.009), which almost reached the levels of group C. Favorable improvements were also noticed at the end of the study for group A in maximal exercise time of the upper limbs by 80.4% (p < 0.001) and maximal strength of the right hand by 27.8% (p < 0.001). Linear regression analysis after training showed that maximal exercise time was positively correlated with SDNN (r = 0.663, p = 0.036) and with LF (ms²) (r = 0.623, p = 0.045). Our results indicate that a 6-month table tennis training program is efficient and can improve cardiac ANS activity mainly by increasing sympathovagal balance. Full article

Background: Arterial hypertension (AH) is a significant risk factor for cardiovascular disease and is associated with increased arterial stiffness, particularly as measured by pulse wave velocity (PWV). This study aims to explore the relationships between age groups, antihypertensive and new oral antidiabetic drugs, body composition, and arterial stiffness parameters in hypertensive patients. Methods: A single-center cross-sectional study was conducted including 584 participants who underwent 24 h ambulatory blood pressure monitoring (including central blood pressure (BP) and PWV measurement), body composition analysis, and provided medical history and current pharmacotherapy data. Results: The study found that PWV was significantly higher in patients with poorly regulated BP in those aged 65 years and older. Significant PWV predictors included systolic BP, heart rate, peripheral mean arterial pressure, peripheral pulse pressure, augmentation index, calcium channel blockers, moxonidine, sodium–glucose co-transporter 2 inhibitors, urapidil, and statin prescription. Also, statistically significant negative correlations were found between PWV and visceral fat level, fat-free mass, and the percentage of muscle mass. Conclusions: The findings suggest that arterial stiffness is interconnected with peripheral and central blood pressure parameters, body composition parameters, and prescribed hypertensive and new antidiabetic drugs. Full article