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Frontiers in Medicine 2024The continuous monitoring of the health status of patients is essential for the effective monitoring of disease progression and the management of symptoms. Recently,... (Review)
Review
The continuous monitoring of the health status of patients is essential for the effective monitoring of disease progression and the management of symptoms. Recently, health monitoring using non-contact sensors has gained interest. Therefore, this study aimed to investigate the use of non-contact sensors for health monitoring in hospital settings and evaluate their potential clinical applications. A comprehensive literature search was conducted using PubMed to identify relevant studies published up to February 26, 2024. The search terms included "hospital," "monitoring," "sensor," and "non-contact." Studies that used non-contact sensors to monitor health status in hospital settings were included in this review. Of the 38 search results, five studies met the inclusion criteria. The non-contact sensors described in the studies were radar, infrared, and microwave sensors. These non-contact sensors were used to obtain vital signs, such as respiratory rate, heart rate, and body temperature, and were then compared with the results from conventional measurement methods (polysomnography, nursing records, and electrocardiography). In all the included studies, non-contact sensors demonstrated a performance similar to that of conventional health-related parameter measurement methods. Non-contact sensors are expected to be a promising solution for health monitoring in hospital settings.
PubMed: 38933102
DOI: 10.3389/fmed.2024.1421901 -
Frontiers in Cardiovascular Medicine 2024Aging is the most significant contributor to the increasing prevalence of atrial fibrillation (AF). Dysbiosis of gut microbiota has been implicated in age-related...
OBJECTIVE
Aging is the most significant contributor to the increasing prevalence of atrial fibrillation (AF). Dysbiosis of gut microbiota has been implicated in age-related diseases, but its role in AF development remains unclear. This study aimed to investigate the correlations between changes in the autonomic nervous system, short-chain fatty acids (SCFAs), and alterations in gut microbiota in aged rats with AF.
METHODS
Electrophysiological experiments were conducted to assess AF induction rates and heart rate variability in rats. 16S rRNA gene sequences extracted from fecal samples were used to assess the gut microbial composition. Gas and liquid chromatography-mass spectroscopy was used to identify SCFAs in fecal samples.
RESULTS
The study found that aged rats exhibited a higher incidence of AF and reduced heart rate variability compared to young rats. Omics research revealed disrupted gut microbiota in aged rats, specifically a decreased Firmicutes to Bacteroidetes ratio. Additionally, fecal SCFA levels were significantly lower in aged rats. Importantly, correlation analysis indicated a significant association between decreased SCFAs and declining heart rate variability in aged rats.
CONCLUSIONS
These findings suggest that SCFAs, as metabolites of gut microbiota, may play a regulatory role in autonomic nervous function and potentially influence the onset and progression of AF in aged rats. These results provide novel insights into the involvement of SCFAs and autonomic nervous system function in the pathogenesis of AF. These results provide novel insights into the involvement of SCFAs and autonomic nervous system function in the pathogenesis of AF.
PubMed: 38932988
DOI: 10.3389/fcvm.2024.1394929 -
Pharmaceutics Jun 2024Landiolol, a highly cardioselective agent with a short half-life (2.4-4 min), is commonly used as a perfusor or bolus application to treat tachycardic arrhythmia. Some...
The Impact of Chronic Oral Beta-Blocker Intake on Intravenous Bolus Landiolol Response in Hospitalized Intensive Care Patients with Sudden-Onset Supraventricular Tachycardia-A Post Hoc Analysis of a Cross-Sectional Trial.
Landiolol, a highly cardioselective agent with a short half-life (2.4-4 min), is commonly used as a perfusor or bolus application to treat tachycardic arrhythmia. Some small studies suggest that prior oral β-blocker use results in a less effective response to intravenous β-blockers. This study investigated whether prior chronic oral β-blocker (Lβ) or no prior chronic oral β-blocker (L-) intake influences the response to intravenous push-dose Landiolol in intensive care patients with acute tachycardic arrhythmia. The effects in 30 patients (67 [55-72] years) were analyzed, 10 (33.3%) with and 20 (66.7%) without prior oral β-blocker therapy. Arrhythmias were diagnosed as tachycardic atrial fibrillation in 14 patients and regular, non-fluid-dependent, supraventricular tachycardia in 16 cases. Successful heart rate control (Lβ 4 vs. L- 7, = 1.00) and rhythm control (Lβ 3 vs. L- 6, = 1.00) did not significantly differ between the two groups. Both groups showed a significant decrease in heart rate when comparing before and after the bolus administration, without significant differences between the two groups (Lβ -26/min vs. L- -33/min, = 0.528). Oral β-blocker therapy also did not influence the change in mean arterial blood pressure after Landiolol bolus administration (Lβ -5 mmHg vs. L- -4 mmHg, = 0.761). A prior chronic intake of β-blockers neither affected the effectiveness of push-dose Landiolol in heart rate or rhythm control nor impacted the difference in heart rate or mean arterial blood pressure before and after the Landiolol boli.
PubMed: 38931959
DOI: 10.3390/pharmaceutics16060839 -
Pharmaceutics Jun 2024Epinephrine autoinjectors (EAIs) are used for the treatment of severe allergic reactions in a community setting; however, their utility is limited by low prescription... (Review)
Review
Epinephrine autoinjectors (EAIs) are used for the treatment of severe allergic reactions in a community setting; however, their utility is limited by low prescription fulfillment rates, failure to carry, and failure to use due to fear of needles. Given that delayed administration of epinephrine is associated with increased morbidity/mortality, there has been a growing interest in developing needle-free, easy-to-use delivery devices. (epinephrine nasal spray) consists of three Food and Drug Administration (FDA)-approved components: epinephrine, Intravail A3 (absorption enhancer), and a Unit Dose Spray (UDS). 's development pathway was established in conjunction with the FDA and the European Medicines Agency and included multiple clinical trials to evaluate pharmacokinetic and pharmacodynamic responses under a variety of conditions, such as self-administration and allergic and infectious rhinitis, as well as an animal anaphylaxis model of severe hypotension, where demonstrated a pharmacokinetic profile that is within the range of approved injection products and a pharmacodynamic response that is as good or better than injections. The increased pulse rate (PR) and blood pressure (BP) observed even one minute following the administration of confirm the activation of α and β adrenergic receptors, which are the key components of epinephrine's mechanism of action. The results suggest that will provide a safe and effective needle-free option for the treatment of severe allergic reactions, including anaphylaxis.
PubMed: 38931932
DOI: 10.3390/pharmaceutics16060811 -
Sensors (Basel, Switzerland) Jun 2024Heart rate variability (HRV) is related to cardiac vagal control and emotional regulation and an index for cardiac vagal control and cardiac autonomic activity. This...
Heart rate variability (HRV) is related to cardiac vagal control and emotional regulation and an index for cardiac vagal control and cardiac autonomic activity. This study aimed to develop the Taiwan HRV normative database covering individuals aged 20 to 70 years and to assess its diagnosing validity in patients with major depressive disorder (MDD). A total of 311 healthy participants were in the HRV normative database and divided into five groups in 10-year age groups, and then the means and standard deviations of the HRV indices were calculated. We recruited 272 patients with MDD for cross-validation, compared their HRV indices with the normative database, and then converted them to Z-scores to explore the deviation of HRV in MDD patients from healthy groups. The results found a gradual decline in HRV indices with advancing age in the HC group, and females in the HC group exhibit higher cardiac vagal control and parasympathetic activity than males. Conversely, patients in the MDD group demonstrate lower HRV indices than those in the HC group, with their symptoms of depression and anxiety showing a negative correlation with HRV indices. The Taiwan HRV normative database has good psychometric characteristics of cross-validation.
Topics: Humans; Heart Rate; Depressive Disorder, Major; Male; Female; Adult; Middle Aged; Aged; Autonomic Nervous System; Young Adult; Databases, Factual; Taiwan; Electrocardiography; Heart
PubMed: 38931788
DOI: 10.3390/s24124003 -
Sensors (Basel, Switzerland) Jun 2024Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical...
Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical signal processing and is strongly associated with other vital signs such as blood pressure, heart rate, and heart rate variability. Various physiological signals, such as photoplethysmogram (PPG) signals, are used to extract respiratory information. RR is also estimated by detecting peak patterns and cycles in the signals through signal processing and deep-learning approaches. In this study, we propose an end-to-end RR estimation approach based on a third-generation artificial neural network model-spiking neural network. The proposed model employs PPG segments as inputs, and directly converts them into sequential spike events. This design aims to reduce information loss during the conversion of the input data into spike events. In addition, we use feedback-based integrate-and-fire neurons as the activation functions, which effectively transmit temporal information. The network is evaluated using the BIDMC respiratory dataset with three different window sizes (16, 32, and 64 s). The proposed model achieves mean absolute errors of 1.37 ± 0.04, 1.23 ± 0.03, and 1.15 ± 0.07 for the 16, 32, and 64 s window sizes, respectively. Furthermore, it demonstrates superior energy efficiency compared with other deep learning models. This study demonstrates the potential of the spiking neural networks for RR monitoring, offering a novel approach for RR estimation from the PPG signal.
Topics: Humans; Respiratory Rate; Neural Networks, Computer; Photoplethysmography; Signal Processing, Computer-Assisted; Heart Rate; Algorithms; Deep Learning
PubMed: 38931763
DOI: 10.3390/s24123980 -
Sensors (Basel, Switzerland) Jun 2024Sensor-based assessments in medical practice and rehabilitation include the measurement of physiological signals such as EEG, EMG, ECG, heart rate, and NIRS, and the...
Sensor-based assessments in medical practice and rehabilitation include the measurement of physiological signals such as EEG, EMG, ECG, heart rate, and NIRS, and the recording of movement kinematics and interaction forces. Such measurements are commonly employed in clinics with the aim of assessing patients' pathologies, but so far some of them have found full exploitation mainly for research purposes. In fact, even though the data they allow to gather may shed light on physiopathology and mechanisms underlying motor recovery in rehabilitation, their practical use in the clinical environment is mainly devoted to research studies, with a very reduced impact on clinical practice. This is especially the case for muscle synergies, a well-known method for the evaluation of motor control in neuroscience based on multichannel EMG recordings. In this paper, considering neuromotor rehabilitation as one of the most important scenarios for exploiting novel methods to assess motor control, the main challenges and future perspectives for the standard clinical adoption of muscle synergy analysis are reported and critically discussed.
Topics: Humans; Biomechanical Phenomena; Electromyography; Movement; Muscle, Skeletal
PubMed: 38931719
DOI: 10.3390/s24123934 -
Sensors (Basel, Switzerland) Jun 2024Photoplethysmography (PPG) is widely utilized in wearable healthcare devices due to its convenient measurement capabilities. However, the unrestricted behavior of users...
Photoplethysmography (PPG) is widely utilized in wearable healthcare devices due to its convenient measurement capabilities. However, the unrestricted behavior of users often introduces artifacts into the PPG signal. As a result, signal processing and quality assessment play a crucial role in ensuring that the information contained in the signal can be effectively acquired and analyzed. Traditionally, researchers have discussed signal quality and processing algorithms separately, with individual algorithms developed to address specific artifacts. In this paper, we propose a quality-aware signal processing mechanism that evaluates incoming PPG signals using the signal quality index (SQI) and selects the appropriate processing method based on the SQI. Unlike conventional processing approaches, our proposed mechanism recommends processing algorithms based on the quality of each signal, offering an alternative option for designing signal processing flows. Furthermore, our mechanism achieves a favorable trade-off between accuracy and energy consumption, which are the key considerations in long-term heart rate monitoring.
Topics: Photoplethysmography; Heart Rate; Humans; Signal Processing, Computer-Assisted; Algorithms; Monitoring, Physiologic; Wearable Electronic Devices
PubMed: 38931686
DOI: 10.3390/s24123901 -
Sensors (Basel, Switzerland) Jun 2024Well-being can reflect people's psychological conditions and be used alongside physiological parameters to evaluate patients' physical and mental health. The modern...
Well-being can reflect people's psychological conditions and be used alongside physiological parameters to evaluate patients' physical and mental health. The modern medical environment increasingly incorporates digital carriers, human-computer interaction devices, sensible spaces, and the execution of suitable algorithms. Slow design in healthy human-computer interaction is often used to reflect people's dependence on or support from behaviors or objects, promoting the stability of behaviors as well as meaningful and positive changes. Therefore, in this study, we propose a slow sensing model, develop a Slow Well-Being Gardening system, and use it to evaluate behavioral data from radiation therapy patients during treatment sessions and horticultural therapy. This study is based on SENS and slow design, setting the hospital lounge as a sensible space and establishing a sensor system. After a 10-day inspection, the process was evaluated and verified. Ultimately, data from facial detection (smile) and HRV showed that the patients in the experimental group experienced a significant improvement in their well-being, feeling better than those in the control group who maintained the most common state in normal treatment. Therefore, it can be inferred that the Slow Well-Being Gardening model is indeed valid and can be further developed.
Topics: Humans; Gardening; Horticultural Therapy; Female; Male; Algorithms; Middle Aged; Smiling; Heart Rate; Radiotherapy
PubMed: 38931555
DOI: 10.3390/s24123771 -
Sensors (Basel, Switzerland) Jun 2024The remote monitoring of vital signs via wearable devices holds significant potential for alleviating the strain on hospital resources and elder-care facilities. Among...
The remote monitoring of vital signs via wearable devices holds significant potential for alleviating the strain on hospital resources and elder-care facilities. Among the various techniques available, photoplethysmography stands out as particularly promising for assessing vital signs such as heart rate, respiratory rate, oxygen saturation, and blood pressure. Despite the efficacy of this method, many commercially available wearables, bearing Conformité Européenne marks and the approval of the Food and Drug Administration, are often integrated within proprietary, closed data ecosystems and are very expensive. In an effort to democratize access to affordable wearable devices, our research endeavored to develop an open-source photoplethysmographic sensor utilizing off-the-shelf hardware and open-source software components. The primary aim of this investigation was to ascertain whether the combination of off-the-shelf hardware components and open-source software yielded vital-sign measurements (specifically heart rate and respiratory rate) comparable to those obtained from more expensive, commercially endorsed medical devices. Conducted as a prospective, single-center study, the research involved the assessment of fifteen participants for three minutes in four distinct positions, supine, seated, standing, and walking in place. The sensor consisted of four PulseSensors measuring photoplethysmographic signals with green light in reflection mode. Subsequent signal processing utilized various open-source Python packages. The heart rate assessment involved the comparison of three distinct methodologies, while the respiratory rate analysis entailed the evaluation of fifteen different algorithmic combinations. For one-minute average heart rates' determination, the Neurokit process pipeline achieved the best results in a seated position with a Spearman's coefficient of 0.9 and a mean difference of 0.59 BPM. For the respiratory rate, the combined utilization of Neurokit and Charlton algorithms yielded the most favorable outcomes with a Spearman's coefficient of 0.82 and a mean difference of 1.90 BrPM. This research found that off-the-shelf components are able to produce comparable results for heart and respiratory rates to those of commercial and approved medical wearables.
Topics: Humans; Photoplethysmography; Respiratory Rate; Heart Rate; Software; Male; Signal Processing, Computer-Assisted; Female; Wearable Electronic Devices; Monitoring, Physiologic; Adult; Prospective Studies; Algorithms
PubMed: 38931550
DOI: 10.3390/s24123766