555 research outputs found

    Evaluation of Respiratory Muscle Activity by Means of Concentric Ring Electrodes

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    © 2021 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Surface electromyography (sEMG) can be used for the evaluation of respiratory muscle activity. Recording sEMG involves the use of surface electrodes in a bipolar configuration. However, electrocardiographic (ECG) interference and electrode orientation represent considerable drawbacks to bipolar acquisition. As an alternative, concentric ring electrodes (CREs) can be used for sEMG acquisition and offer great potential for the evaluation of respiratory muscle activity due to their enhanced spatial resolution and simple placement protocol, which does not depend on muscle fiber orientation. The aim of this work was to analyze the performance of CREs during respiratory sEMG acquisitions. Respiratory muscle sEMG was applied to the diaphragm and sternocleidomastoid muscles using a bipolar and a CRE configuration. Thirty-two subjects underwent four inspiratory load spontaneous breathing tests which was repeated after interchanging the electrode positions. We calculated parameters such as (1) spectral power and (2) median frequency during inspiration, and power ratios of inspiratory sEMG without ECG in relation to (3) basal sEMG without ECG (R-ins/noise), (4) basal sEMG with ECG (R-ins/cardio) and (5) expiratory sEMG without ECG (R-ins/exp). Spectral power, R-ins/noise and R-ins/cardio increased with the inspiratory load. Significantly higher values (p < 0.05) of R-ins/cardio and significantly higher median frequencies were obtained for CREs. R-ins/noise and R-ins/exp were higher for the bipolar configuration only in diaphragm sEMG recordings, whereas no significant differences were found in the sternocleidomastoid recordings. Our results suggest that the evaluation of respiratory muscle activity by means of sEMG can benefit from the remarkably reduced influence of cardiac activity, the enhanced detection of the shift in frequency content and the axial isotropy of CREs which facilitates its placement.This work was supported in part by the CERCA Program/Generalitat de Catalunya, in part by the Secretaria d'Universitats i Recerca de la Generalitat de Catalunya under Grant GRC 2017 SGR 01770, in part by the Spanish Grants RTI2018-098472-B-I00, RTI2018-094449-A-I00-AR (MCIU/AEI/FEDER, UE) and DPI2015-68397-R (MINECO/FEDER), and in part by the Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN, Instituto de Salud Carlos III/FEDER). The first author was supported by the IFARHU-SENACYT Scholarship Program from the Panama Government under Grant 270-2012-273.Estrada-Petrocelli, L.; Torres, A.; Sarlabous, L.; Ràfols-De-Urquía, M.; Ye Lin, Y.; Prats-Boluda, G.; Jané, R.... (2021). Evaluation of Respiratory Muscle Activity by Means of Concentric Ring Electrodes. IEEE Transactions on Biomedical Engineering. 68(3):1005-1014. https://doi.org/10.1109/TBME.2020.3012385S1005101468

    Radio telemetry devices to monitor breathing in non-sedated animals

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    Radio telemetry equipment has significantly improved over the last 10-15 years and is increasingly being used in research for monitoring a variety of physiological parameters in non-sedated animals. The aim of this review is to provide an update on the current state of development of radio telemetry for recording respiration. Our literature review found only rare reports of respiratory studies via radio telemetry. Much of this article will hence report our experience with our custom-built radio telemetry devices designed for recording respiratory signals, together with numerous other physiological signals in lambs. Our current radio telemetry system allows to record 24 simultaneous signals 24h/day for several days. To our knowledge, this is the highest number of physiological signals, which can be recorded wirelessly. Our devices have been invaluable for studying respiration in our ovine models of preterm birth, reflux laryngitis, postnatal exposure to cigarette smoke, respiratory syncytial virus infection and nasal ventilation, all of which are relevant to neonatal respiratory problems

    Development of a Signal Processing Library for Extraction of SpO2, HR, HRV, and RR from Photoplethysmographic Waveforms

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    Non-invasive remote physiological monitoring of soldiers on the battlefield has the potential to provide fast, accurate status assessments that are key to improving the survivability of critical injuries. The development of WPI’s wearable wireless pulse oximeter, designed for field-based applications, has allowed for the optimization of important hardware features such as physical size and power management. However, software-based digital signal processing (DSP) methods are still required to perform physiological assessments. This research evaluated DSP methods that were capable of providing arterial oxygen saturation (SpO2), heart rate (HR), heart rate variability (HRV), and respiration rate (RR) measurements derived from data acquired using a single optical sensor. In vivo experiments were conducted to evaluate the accuracies of the processing methods across ranges of physiological conditions. Of the algorithms assessed, 13 SpO2 methods, 1 HR method, 6 HRV indices, and 4 RR methods were identified that provided clinically acceptable measurement accuracies and could potentially be employed in a wearable pulse oximeter

    A novel broadband forcecardiography sensor for simultaneous monitoring of respiration, infrasonic cardiac vibrations and heart sounds

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    The precordial mechanical vibrations generated by cardiac contractions have a rich frequency spectrum. While the lowest frequencies can be palpated, the higher infrasonic frequencies are usually captured by the seismocardiogram (SCG) signal and the audible ones correspond to heart sounds. Forcecardiography (FCG) is a non-invasive technique that measures these vibrations via force sensing resistors (FSR). This study presents a new piezoelectric sensor able to record all heart vibrations simultaneously, as well as a respiration signal. The new sensor was compared to the FSR-based one to assess its suitability for FCG. An electrocardiogram (ECG) lead and a signal from an electro-resistive respiration band (ERB) were synchronously acquired as references on six healthy volunteers (4 males, 2 females) at rest. The raw signals from the piezoelectric and the FSR-based sensors turned out to be very similar. The raw signals were divided into four components: Forcerespirogram (FRG), Low-Frequency FCG (LF-FCG), High- Frequency FCG (HF-FCG) and heart sounds (HS-FCG). A beat-by-beat comparison of FCG and ECG signals was carried out by means of regression, correlation and Bland–Altman analyses, and similarly for respiration signals (FRG and ERB). The results showed that the infrasonic FCG components are strongly related to the cardiac cycle (R2 > 0.999, null bias and Limits of Agreement (LoA) of ± 4.9 ms for HF-FCG; R2 > 0.99, null bias and LoA of ± 26.9 ms for LF-FCG) and the FRG inter-breath intervals are consistent with ERB ones (R2 > 0.99, non-significant bias and LoA of ± 0.46 s). Furthermore, the piezoelectric sensor was tested against an accelerometer and an electronic stethoscope: synchronous acquisitions were performed to quantify the similarity between the signals. ECG-triggered ensemble averages (synchronized with R-peaks) of HF-FCG and SCG showed a correlation greater than 0.81, while those of HS-FCG and PCG scored a correlation greater than 0.85. The piezoelectric sensor demonstrated superior performances as compared to the FSR, providing more accurate, beat-by-beat measurements. This is the first time that a single piezoelectric sensor demonstrated the ability to simultaneously capture respiration, heart sounds, an SCG-like signal (i.e., HF-FCG) and the LF-FCG signal, which may provide information on ventricular emptying and filling events. According to these preliminary results the novel piezoelectric FCG sensor stands as a promising device for accurate, unobtrusive, long-term monitoring of cardiorespiratory functions and paves the way for a wide range of potential applications, both in the research and clinical fields. However, these results should be confirmed by further analyses on a larger cohort of subjects, possibly including also pathological patients

    The Challenges and Pitfalls of Detecting Sleep Hypopnea Using a Wearable Optical Sensor: Comparative Study.

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    BACKGROUND Obstructive sleep apnea (OSA) is the most prevalent respiratory sleep disorder occurring in 9% to 38% of the general population. About 90% of patients with suspected OSA remain undiagnosed due to the lack of sleep laboratories or specialists and the high cost of gold-standard in-lab polysomnography diagnosis, leading to a decreased quality of life and increased health care burden in cardio- and cerebrovascular diseases. Wearable sleep trackers like smartwatches and armbands are booming, creating a hope for cost-efficient at-home OSA diagnosis and assessment of treatment (eg, continuous positive airway pressure [CPAP] therapy) effectiveness. However, such wearables are currently still not available and cannot be used to detect sleep hypopnea. Sleep hypopnea is defined by ≥30% drop in breathing and an at least 3% drop in peripheral capillary oxygen saturation (Spo2) measured at the fingertip. Whether the conventional measures of oxygen desaturation (OD) at the fingertip and at the arm or wrist are identical is essentially unknown. OBJECTIVE We aimed to compare event-by-event arm OD (arm_OD) with fingertip OD (finger_OD) in sleep hypopneas during both naïve sleep and CPAP therapy. METHODS Thirty patients with OSA underwent an incremental, stepwise CPAP titration protocol during all-night in-lab video-polysomnography monitoring (ie, 1-h baseline sleep without CPAP followed by stepwise increments of 1 cmH2O pressure per hour starting from 5 to 8 cmH2O depending on the individual). Arm_OD of the left biceps muscle and finger_OD of the left index fingertip in sleep hypopneas were simultaneously measured by frequency-domain near-infrared spectroscopy and video-polysomnography photoplethysmography, respectively. Bland-Altman plots were used to illustrate the agreements between arm_OD and finger_OD during baseline sleep and under CPAP. We used t tests to determine whether these measurements significantly differed. RESULTS In total, 534 obstructive apneas and 2185 hypopneas were recorded. Of the 2185 hypopneas, 668 (30.57%) were collected during baseline sleep and 1517 (69.43%), during CPAP sleep. The mean difference between finger_OD and arm_OD was 2.86% (95% CI 2.67%-3.06%, t667=28.28; P<.001; 95% limits of agreement [LoA] -2.27%, 8.00%) during baseline sleep and 1.83% (95% CI 1.72%-1.94%, t1516=31.99; P<.001; 95% LoA -2.54%, 6.19%) during CPAP. Using the standard criterion of 3% saturation drop, arm_OD only recognized 16.32% (109/668) and 14.90% (226/1517) of hypopneas at baseline and during CPAP, respectively. CONCLUSIONS arm_OD is 2% to 3% lower than standard finger_OD in sleep hypopnea, probably because the measured arm_OD originates physiologically from arterioles, venules, and capillaries; thus, the venous blood adversely affects its value. Our findings demonstrate that the standard criterion of ≥3% OD drop at the arm or wrist is not suitable to define hypopnea because it could provide large false-negative results in diagnosing OSA and assessing CPAP treatment effectiveness
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