Quantitative validation of the suprasternal pressure signal to assess respiratory effort during sleep.

Objective.Intra-esophageal pressure (Pes) measurement is the recommended gold standard to quantify respiratory effort during sleep, but used to limited extent in clinical practice due to multiple practical drawbacks. Respiratory inductance plethysmography belts (RIP) in conjunction with oronasal airflow are the accepted substitute in polysomnographic systems (PSG) thanks to a better usability, although they are partial views on tidal volume and flow rather than true respiratory effort and are often used without calibration. In their place, the pressure variations measured non-invasively at the suprasternal notch (SSP) may provide a better measure of effort. However, this type of sensor has been validated only for respiratory events in the context of obstructive sleep apnea syndrome (OSA). We aim to provide an extensive verification of the suprasternal pressure signal against RIP belts and Pes, covering both normal breathing and respiratory events.Approach.We simultaneously acquired suprasternal (207) and esophageal pressure (20) signals along with RIP belts during a clinical PSG of 207 participants. In each signal, we detected breaths with a custom algorithm, and evaluated the SSP in terms of detection quality, breathing rate estimation, and similarity of breathing patterns against RIP and Pes. Additionally, we examined how the SSP signal may diverge from RIP and Pes in presence of respiratory events scored by a sleep technician.Main results.The SSP signal proved to be a reliable substitute for both esophageal pressure (Pes) and respiratory inductance plethysmography (RIP) in terms of breath detection, with sensitivity and positive predictive value exceeding 75%, and low error in breathing rate estimation. The SSP was also consistent with Pes (correlation of 0.72, similarity 80.8%) in patterns of increasing pressure amplitude that are common in OSA.Significance.This work provides a quantitative analysis of suprasternal pressure sensors for respiratory effort measurements.

Proof-of-concept model for instantaneous heart rate-drift correction during low and high exercise exertion.

Introduction: This study aimed to model below and above anaerobic threshold exercise-induced heart rate (HR) drift, so that the corrected HR could better represent V˙O2 kinetics during and after the exercise itself. Methods: Fifteen healthy subjects (age: 28 ± 5 years; V˙O2Max: 50 ± 8 mL/kg/min; 5 females) underwent a maximal and a 30-min submaximal (80% of the anaerobic threshold) running exercises. A five-stage computational (i.e., delay block, new training impulse-calculation block, Sigmoid correction block, increase block, and decrease block) model was built to account for instantaneous HR, fitness, and age and to onset, increase, and decrease according to the exercise intensity and duration. Results: The area under the curve (AUC) of the hysteresis function, which described the differences in the maximal and submaximal exercise-induced V˙O2 and HR kinetics, was significantly reduced for both maximal (26%) and submaximal (77%) exercises and consequent recoveries. Discussion: In conclusion, this model allowed HR drift instantaneous correction, which could be exploited in the future for more accurate V˙O2 estimations.

A sleep stage estimation algorithm based on cardiorespiratory signals derived from a suprasternal pressure sensor.

Automatic estimation of sleep structure is an important aspect in moving sleep monitoring from clinical laboratories to people's homes. However, the transition to more portable systems should not happen at the expense of important physiological signals, such as respiration. Here, we propose the use of cardiorespiratory signals obtained by a suprasternal pressure (SSP) sensor to estimate sleep stages. The sensor is already used for diagnosis of sleep-disordered breathing (SDB) conditions, but besides respiratory effort it can detect cardiac vibrations transmitted through the trachea. We collected the SSP sensor signal in 100 adults (57 male) undergoing clinical polysomnography for suspected sleep disorders, including sleep apnea syndrome, insomnia, and movement disorders. Here, we separate respiratory effort and cardiac activity related signals, then input these into a neural network trained to estimate sleep stages. Using the original mixed signal the results show a moderate agreement with manual scoring, with a Cohen's kappa of 0.53 in Wake/N1-N2/N3/rapid eye movement sleep discrimination and 0.62 in Wake/Sleep. We demonstrate that decoupling the two signals and using the cardiac signal to estimate the instantaneous heart rate improves the process considerably, reaching an agreement of 0.63 and 0.71. Our proposed method achieves high accuracy, specificity, and sensitivity across different sleep staging tasks. We also compare the total sleep time calculated with our method against manual scoring, with an average error of -1.83 min but a relatively large confidence interval of ±55 min. Compact systems that employ the SSP sensor information-rich signal may enable new ways of clinical assessments, such as night-to-night variability in obstructive sleep apnea and other sleep disorders.

Extraction of cardiac-related signals from a suprasternal pressure sensor during sleep.

Objective.The accurate detection of respiratory effort during polysomnography is a critical element in the diagnosis of sleep-disordered breathing conditions such as sleep apnea. Unfortunately, the sensors currently used to estimate respiratory effort are either indirect and ignore upper airway dynamics or are too obtrusive for patients. One promising alternative is the suprasternal notch pressure (SSP) sensor: a small element placed on the skin in the notch above the sternum within an airtight capsule that detects pressure swings in the trachea. Besides providing information on respiratory effort, the sensor is sensitive to small cardiac oscillations caused by pressure perturbations in the carotid arteries or the trachea. While current clinical research considers these as redundant noise, they may contain physiologically relevant information.Approach.We propose a method to separate the signal generated by cardiac activity from the one caused by breathing activity. Using only information available from the SSP sensor, we estimate the heart rate and track its variations, then use a set of tuned filters to process the original signal in the frequency domain and reconstruct the cardiac signal. We also include an overview of the technical and physiological factors that may affect the quality of heart rate estimation. The output of our method is then used as a reference to remove the cardiac signal from the original SSP pressure signal, to also optimize the assessment of respiratory activity. We provide a qualitative comparison against methods based on filters with fixed frequency cutoffs.Main results.In comparison with electrocardiography (ECG)-derived heart rate, we achieve an agreement error of 0.06 ± 5.09 bpm, with minimal bias drift across the measurement range, and only 6.36% of the estimates larger than 10 bpm.Significance.Together with qualitative improvements in the characterization of respiratory effort, this opens the development of novel portable clinical devices for the detection and assessment of sleep disordered breathing.

Use of reaction path modelling to investigate the evolution of water chemistry in shallow to deep crystalline aquifers with a special focus on fluoride.

Crystalline aquifers are layered systems in which the hydrogeological path of waters extends from highly weathered, shallow and porous rocks to poorly weathered, deep and fissured rocks. This varying hydrogeological setting influences the water chemistry in different ways. The paper aims to reconstruct the water-rock interaction process in these various environments starting from a solid reactant represented by an average granite rock and several waters from the shallow aquifer. Afterwards, the water-rock interaction processes occurring in the deep environment are reconstructed, varying the geochemical conditions (primary reactants, secondary mineral phases allowed to precipitate, fO2 and fCO2), with a special focus on fluoride (F-). The evolution from the F-poor, Ca-HCO3 facies to the F-rich, Na-HCO3 water type of high pH was simulated using reaction path modelling. The obtained results show that the theoretical evolution trends well reproduce both shallow and deep water samples providing detailed information on the behavior of fluoride and other relevant constituents (i.e., Na, K, Ca, Mg, SiO2). The performed model represents a flexible and powerful tool for environmental research, applicable in other areas hosting F-rich groundwater.

Association between one's own consumption and harm from others' drinking: Does education play a role?

Introduction: We examined (a) whether risky drinking behaviour is related to experienced harm from others' drinking (EHFOD) and (b) whether any found relationship is modified by educational level, such that those of lower socio-economic status (SES) experience more harm even when adjusted for drinking behaviour. Method: Data from the Danish national alcohol and drug survey of 2011 (N=5133) were linked with registry data from Statistics Denmark. Eight EHFOD indicators were grouped into nuisance, harassment or harm/damage categories. Indicators for mean alcohol consumption, Alcohol Use Disorder Identification Test (AUDIT) and binge drinking were examined in relation to respondents' EHFOD with multiple logistic regression, stratified by sex and education (proxy for SES). Results: One-year prevalence of EHFOD was 50%. We found a positive and significant relationship between own alcohol consumption and EHFOD categories of harassment as well as harm/damage. Effect modification of education was significant for harassment. Among men, odds ratios for the association between risky drinking behaviour and harassment were 5.50 (95% confidence interval (CI) 3.49-8.65) in the low educational group versus 1.42 (95% CI 0.98-2.07) in the high educational group. Conclusions: Our study confirmed an overall positive relationship between EHFOD and drinking behaviour, but it varied by type of EHFOD. Furthermore, education modified this effect for harassment, suggesting evidence of the alcohol harm paradox with respect to EHFOD. More research is necessary to understand better how drinking patterns diverge between low and high educational groups as well as sex, and how this differentially affects risk for alcohol-related harms, including EHFOD.

Muscle Hypertrophy Response Is Affected by Previous Resistance Training Volume in Trained Individuals.

ABSTRACT: Scarpelli, MC, Nóbrega, SR, Santanielo, N, Alvarez, IF, Otoboni, GB, Ugrinowitsch, C, and Libardi, CA. Muscle hypertrophy response is affected by previous resistance training volume in trained individuals. J Strength Cond Res 36(4): 1153-1157, 2022-The purpose of this study was to compare gains in muscle mass of trained individuals after a resistance training (RT) protocol with standardized (i.e., nonindividualized) volume (N-IND), with an RT protocol using individualized volume (IND). In a within-subject approach, 16 subjects had one leg randomly assigned to N-IND (22 sets·wk-1, based on the number of weekly sets prescribed in studies) and IND (1.2 × sets·wk-1 recorded in training logs) protocols. Muscle cross-sectional area (CSA) was assessed by ultrasound imaging at baseline (Pre) and after 8 weeks (Post) of RT, and the significance level was set at p < 0.05. Changes in the vastus lateralis CSA (difference from Pre to Post) were significantly higher for the IND protocol (p = 0.042; mean difference: 1.08 cm2; confidence interval [CI]: 0.04-2.11). The inferential analysis was confirmed by the CI of the effect size (0.75; CI: 0.03-1.47). Also, the IND protocol had a higher proportion of individuals with greater muscle hypertrophy than the typical error of the measurement (chi-square, p = 0.0035; estimated difference = 0.5, CI: 0.212-0.787). In conclusion, individualizing the weekly training volume of research protocols provides greater gains in muscle CSA than prescribing a group standard RT volume.

Arsenic polluted waters: Application of geochemical modelling as a tool to understand the release and fate of the pollutant in crystalline aquifers.

Arsenic (As) is one of the most investigated elements worldwide due to its negative impact on the natural system. Its geochemical behavior depends on several geogenic processes, which can cause hazardous enrichment into natural waters, even in remote areas, far from anthropogenic sources. In this work the arsenic pollution issue has been addressed by studying water-rock interaction processes and applying reaction path modelling as a tool to understand the rock-to-water release of As and the fate of this natural pollutant in crystalline aquifers. In-depth geochemical characterization of several water samples discharging from crystalline aquifers was performed. The obtained data were used to fix the boundary conditions and validate the modelling outcomes. The performed modelling allowed to reconstruct the water-rock interaction processes which occur (i) in shallow and relatively shallow crystalline aquifers in which no As anomalies were observed and (ii) in As-rich areas, coupling reaction path modelling of granite dissolution with adsorption of dissolved As onto precipitating crystalline and amorphous Fe(III)-oxyhydroxides given the widespread presence of these phases in the studied environment. The results of the geochemical modelling are in agreement with the analytical data and reproduce them satisfactorily. The performed geochemical modelling is of high environmental significance because it is a flexible and powerful tool that correctly defines the water-rock interaction processes occurring in crystalline aquifers, providing valuable data to improve the knowledge on As behavior, not only in the study area, but also in similar geological settings worldwide. Therefore, the present research has broad future perspectives in the environmental field.

A multivariate non-parametric approach for estimating probability of exceeding the local natural background level of arsenic in the aquifers of Calabria region (Southern Italy).

The concept of natural background level (NBL) aims at distinguishing the natural and anthropogenic contributions to concentrations of specific contaminants, as groundwater management and protection tools. This is usually defined as a unique value at a regional scale, even when the hydrogeological and geochemical features of a certain territory are far from homogeneous. The concentration of target contaminants is affected by multiple hydrogeochemical processes. This is the case of arsenic in the Calabria region, where concentrations are definitely variable in groundwater. To overcome the limitation of a traditional approach and to include the intrinsic hydrogeological and geochemical heterogeneity into the definition of the natural contribution to As content in groundwater, an integrated probabilistic approach to the NBL assessment combining aquifer-based preselection criteria and multivariate non-parametric geostatistics was proposed. In detail, different NBL values were selected, based on the aquifer type and/or hydrogeochemical features. Then, these aquifer-based NBL values of arsenic were used in the Probability Kriging method to map the probability of exceedance and to provide contamination risk management tools. This multivariate geostatistical approach that takes advantage of the physico-chemical variables used in the aquifer-based NBL values definition allowed mapping the probability of exceedance of As in a physically-based way. The hydrogeochemical diversity of the study area and all the processes affecting As concentrations in the aquifers have been considered too. As a result, the obtained map was characterized by a short-range and long-range variability due to local hydrogeochemical anomalies and water-rock interaction and/or atmospheric precipitation. By this approach, the NBL exceedance probability maps proved to be less "noisy", because the local hydrogeochemical conditions were filtered, and more capable of pointing out anthropogenic inputs or very anomalous natural contributions, which need to be investigated more in detail and properly managed.

High-Resolution Kinematic Analysis of Root Gravitropic Bending Using RootPlot.

Root gravitropic bending is a complex growth process resulting from differential expansion of cells on the upper and lower sides of a gravistimulated root. In order to genetically dissect the molecular machinery underlying root bending, a thorough understanding of the kinetics and spatial distribution of the growth process is required. We have developed an experimental workflow that enables us to image growing roots at high spatiotemporal resolution and then convert XY-coordinates of root cellular markers into 3D representations of root growth profiles. Here, we present a detailed description of the setup for monitoring vertically oriented roots before and after gravistimulation. We also introduce our newly developed custom R-based program RootPlot, which calculates root velocity profiles from root XY-coordinate data obtained using a previously published image processing software. The raw velocity and derived relative elemental growth rate (REGR) curves are then fitted via LOWESS regression for assumption-free data analysis. The resulting smoothed growth profiles are plotted as heatmaps to visualize how different regions of the root contribute to the growth response over time. Additionally, RootPlot provides analysis of overall growth and bending rates based on root XY-coordinates.

Avaliação do luto familiar na perda gestacional e neonatal / Assessment of family grief over the gestational and neonatal loss

RESUMO: Objetivos: Avaliar o grau de luto causado pela perda gestacional ou neonatal em pais e mães, associando com va-riáveis sociodemográficas. Adicionalmente, comparar o grau de luto de acordo com o momento da perda. Métodos:Estudo transversal, realizado com aplicação de questionário sociodemográfico e questionário validado (Escala de Luto Perinatal­ELP) em pais que tiveram perda de seu filho em qualquer período gestacional ou no neonatal. Resultados: 542 pais e mães estavam aptos para participação do estudo e após serem convidados para responder à pesquisa, 104 (19,1%) concordaram em participar. Os 104 participantes foram divididos em dois grupos: perda no primeiro trimestre gestacional (76,9%), e demais trimestres somados ao período neonatal (23,1%). Evidenciou-se predomínio materno das respostas (89,4%) e idade média de 29,1±15,58 anos. A mediana do escore na ELP foi de 90 pontos, não havendo diferença entre as pontuações de acordo com o momento da perda. Primigestas e mulheres com idade <25 anos apresentaram pontuações maiores que as demais (p=0,042 e p=0,047). Ideação suicida foi relatada por 15,4% e 32,7% das mães que se culpam pela morte do bebê e têm escores significativamente maior do que aque-las que não tinham tal sentimento (p<0,0001). Estado civil, escolaridade, situação econômica, religião, realização de pré-natal, etnia e abortamento prévio não apresentaram associação significativa com os escores obtidos na ELP. Conclusão: O luto ocorreu independente da idade gestacional do momento da perda, sendo de maior intensidade nas mulheres mais jovens e naquelas com sentimento de culpa. Medidas devem ser tomadas para minimizar tal sofrimento. (AU)

ABSTRACT: Objectives: To evaluate the degree of grief caused by gestational or neonatal loss in parents, associating with socio-demographic variables. Additionally, compare the degree of grief according to the moment of loss. Methods: Cross-sectional study conducted with the application of a sociodemographic questionnaire and a validated questionnaire (Perinatal Grief Scale-PGS) in parents who lost their child at any time during pregnancy or in the neonatal period. Results: 542 fathers and mothers were able to participate in the study and after invited to respond, 104 (19.1%) were willing to participate. The 104 respondents were divided into two groups: loss in the first gestational trimester (76.9%), and other trimesters added to the neonatal period (23.1%). There was a predominance of maternal responses (89.4%) and a mean age was 29.1±15.58 years. The median PGS score was 90 points, with no difference between the scores according to the moment of loss. First pregnant and women under the age of 25 had higher scores than the others (p=0.042 and p=0.047) respectively. Suicidal ideation was reported by 15.4% and 32.7% of mothers who blame themselves for the death of the baby have significantly higher scores than those without such feelings (p <0.0001). Marital status, education, economic status, religion, prenatal care, ethnicity, and previous miscarriage were not significantly associated with the scores obtained in the PGS. Conclusion: Family grief occurred regardless of the moment of loss, being greater in younger women and those with feelings of guilt. Measures must be taken to minimize such suffering. (AU)

Effect of resistance training to muscle failure vs non-failure on strength, hypertrophy and muscle architecture in trained individuals.

The aim of this study was to compare the effects of resistance training to muscle failure (RT-F) and non-failure (RT-NF) on muscle mass, strength and activation of trained individuals. We also compared the effects of these protocols on muscle architecture parameters. A within-subjects design was used in which 14 participants had one leg randomly assigned to RT-F and the other to RT-NF. Each leg was trained 2 days per week for 10 weeks. Vastus lateralis (VL) muscle cross-sectional area (CSA), pennation angle (PA), fascicle length (FL) and 1-repetition maximum (1-RM) were assessed at baseline (Pre) and after 20 sessions (Post). The electromyographic signal (EMG) was assessed after the training period. RT-F and RT-NF protocols showed significant and similar increases in CSA (RT-F: 13.5% and RT-NF: 18.1%; P < 0.0001), PA (RT-F: 13.7% and RT-NF: 14.4%; P < 0.0001) and FL (RT-F: 11.8% and RT-NF: 8.6%; P < 0.0001). All protocols showed significant and similar increases in leg press (RT-F: 22.3% and RT-NF: 26.7%; P < 0.0001) and leg extension (RT-F: 33.3%, P < 0.0001 and RT-NF: 33.7%; P < 0.0001) 1-RM loads. No significant differences in EMG amplitude were detected between protocols (P > 0.05). In conclusion, RT-F and RT-NF are similarly effective in promoting increases in muscle mass, PA, FL, strength and activation.

Wearable monitoring of sleep-disordered breathing: estimation of the apnea-hypopnea index using wrist-worn reflective photoplethysmography.

A large part of the worldwide population suffers from obstructive sleep apnea (OSA), a disorder impairing the restorative function of sleep and constituting a risk factor for several cardiovascular pathologies. The standard diagnostic metric to define OSA is the apnea-hypopnea index (AHI), typically obtained by manually annotating polysomnographic recordings. However, this clinical procedure cannot be employed for screening and for long-term monitoring of OSA due to its obtrusiveness and cost. Here, we propose an automatic unobtrusive AHI estimation method fully based on wrist-worn reflective photoplethysmography (rPPG), employing a deep learning model exploiting cardiorespiratory and sleep information extracted from the rPPG signal trained with 250 recordings. We tested our method with an independent set of 188 heterogeneously disordered clinical recordings and we found it estimates the AHI with a good agreement to the gold standard polysomnography reference (correlation = 0.61, estimation error = 3±10 events/h). The estimated AHI was shown to reliably assess OSA severity (weighted Cohen's kappa = 0.51) and screen for OSA (ROC-AUC = 0.84/0.86/0.85 for mild/moderate/severe OSA). These findings suggest that wrist-worn rPPG measurements that can be implemented in wearables such as smartwatches, have the potential to complement standard OSA diagnostic techniques by allowing unobtrusive sleep and respiratory monitoring.

Respiratory activity extracted from wrist-worn reflective photoplethysmography in a sleep-disordered population.

OBJECTIVE: Respiratory activity is an essential parameter to monitor healthy and disordered sleep, and unobtrusive measurement methods have important clinical applications in diagnostics of sleep-related breathing disorders. We propose a respiratory activity surrogate extracted from wrist-worn reflective photoplethysmography validated on a heterogeneous dataset of 389 sleep recordings. APPROACH: The surrogate was extracted by interpolating the amplitude of the PPG pulses after evaluation of pulse morphological quality. Subsequent multistep post-processing was applied to remove parts of the surrogate with low quality and high motion levels. In addition to standard respiration rate performance, we evaluated the similarity between surrogate respiratory activity and reference inductance plethysmography of the thorax, using Spearman's correlations and spectral coherence, and assessed the influence of PPG signal quality, motion levels, sleep stages and obstructive sleep apnea. MAIN RESULTS: Prior to post-processing, the surrogate already had a strong similarity with the reference (correlation = 0.54, coherence = 0.81), and reached respiration rate estimation performance in line with the literature (estimation error = 0.76± 2.11 breaths/min). Detrimental effects of low PPG quality, high motion levels and sleep-dependent physiological phenomena were significantly mitigated by the proposed post-processing steps (correlation = 0.62, coherence = 0.88, estimation error = 0.53± 1.85 breaths/min). SIGNIFICANCE: Wrist-worn PPG can be used to extract respiratory activity, thus allowing respiration monitoring in real-world sleep medicine applications using (consumer) wearable devices.

Geochemical modeling of chromium release in natural waters and treatment by RO/NF membrane processes.

In this work, a geochemical approach was used as strong-scientific tool for pre-selection of suitable remediation systems to treat Cr-contaminated groundwaters. The geochemical characterization allowed to select Nanofiltration (NF) and Reverse Osmosis (RO) as suitable remediation processes, whereas through a new geochemical modeling, the evolution of water chemistry during the water-rock interaction was also studied. The new reaction path modelling was performed re-evaluating the role of Fe as main oxidant in the system and the analytic concentrations of relevant solutes, including Cr(VI), were reproduced. The spring with the highest Cr(VI) content was treated to lower its concentration below the threshold values. A laboratory-scale set-up was used to carry out both NF and RO experiments. The experiments were conducted on different commercial membranes varying the operating pressures. The results showed high Cr(VI) rejections (around 95%) for all tested membranes, leading to Cr(VI) concentrations below the threshold limits. The high flux, obtained already at lower operating pressures, combined with high selectivity towards Cr(VI) makes NF a favorable remediation option.

Estimation of the apnea-hypopnea index in a heterogeneous sleep-disordered population using optimised cardiovascular features.

Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder, which results in daytime symptoms, a reduced quality of life as well as long-term negative health consequences. OSA diagnosis and severity rating is typically based on the apnea-hypopnea index (AHI) retrieved from overnight poly(somno)graphy. However, polysomnography is costly, obtrusive and not suitable for long-term recordings. Here, we present a method for unobtrusive estimation of the AHI using ECG-based features to detect OSA-related events. Moreover, adding ECG-based sleep/wake scoring yields a fully automatic method for AHI-estimation. Importantly, our algorithm was developed and validated on a combination of clinical datasets, including datasets selectively including OSA-pathology but also a heterogeneous, "real-world" clinical sleep disordered population (262 participants in the validation set). The algorithm provides a good representation of the current gold standard AHI (0.72 correlation, estimation error of 0.56 ± 14.74 events/h), and can also be employed as a screening tool for a large range of OSA severities (ROC AUC ≥ 0.86, Cohen's kappa ≥ 0.53 and precision ≥70%). The method compares favourably to other OSA monitoring strategies, showing the feasibility of cardiovascular-based surrogates for sleep monitoring to evolve into clinically usable tools.

Quarter-mile walk test sensitive to training-induced fitness changes.

BACKGROUND: Cardiorespiratory fitness (CRF) is an important aspect of the overall health of an individual and its monitoring must be promoted in the general population. Thus, the aim of the study was to cross-validate and improve CRF estimation based on quarter-mile Rockport Fitness Walking Test. METHODS: Thirty participants (31.4±7.99 years) were randomized in either a four-week aerobic training group (10 men and 10 women) or a control group (eight men and two women). CRF was assessed via VO2max test and estimated via quarter-mile Rockport Fitness and Ebbeling treadmill tests, before and after the training intervention. The original quarter-mile Rockport VO2max estimation was found to greatly overestimate CRF by 22 mL/kg/min. When its coefficient was updated according to our data, it largely improved (by 6.8 mL/kg/min). Furthermore, a new algorithm for predicting VO2max was designed using multi-linear regression analysis. RESULTS: The original quarter-mile Rockport Fitness Walking Test was not sensitive to CRF changes. It showed changes in VO2max, which were significantly different from the actual observed changes (-1.1±4.08 vs. 1.61±2.84, P=0.02, respectively). The Ebbeling treadmill test appeared to systematically overestimate CRF changes. Our new algorithm showed improved sensitivity for detecting CRF changes and stability. CONCLUSIONS: The original quarter-mile Rockport Fitness Walking Test equation for predicting VO2max was neither accurate nor sensitive to changes in CRF, most likely due to cardiovascular drift. Our new algorithm, based on the same brisk walking test, can provide a more accurate estimate of CRF, which is also sensitive to VO2max changes, in a broad age range (18 to 50 years).

Sinus or not: a new beat detection algorithm based on a pulse morphology quality index to extract normal sinus rhythm beats from wrist-worn photoplethysmography recordings.

OBJECTIVE: Wrist-worn photoplethysmography (PPG) can enable free-living physiological monitoring of people during diverse activities, ranging from sleep to physical exercise. In many applications, it is important to remove the pulses not related to sinus rhythm beats from the PPG signal before using it as a cardiovascular descriptor. In this manuscript, we propose an algorithm to assess the morphology of the PPG signal in order to reject non-sinus rhythm pulses, such as artefacts or pulses related to arrhythmic beats. APPROACH: The algorithm segments the PPG signal into individual pulses and dynamically evaluates their morphological likelihood of being normal sinus rhythm pulses via a template-matching approach that accounts for the physiological variability of the signal. The normal sinus rhythm likelihood of each pulse is expressed as a quality index that can be employed to reject artefacts and pulses related to arrhythmic beats. MAIN RESULTS: Thresholding the pulse quality index enables near-perfect detection of normal sinus rhythm beats by rejecting most of the non-sinus rhythm pulses (positive predictive value 98%-99%), both in healthy subjects and arrhythmic patients. The rejection of arrhythmic beats is almost complete (sensitivity to arrhythmic beats 7%-3%), while the sensitivity to sinus rhythm beats is not compromised (96%-91%). SIGNIFICANCE: The developed algorithm consistently detects normal sinus rhythm beats in a PPG signal by rejecting artefacts and, as a first of its kind, arrhythmic beats. This increases the reliability in the extraction of features which are adversely influenced by the presence of non-sinus pulses, whether related to inter-beat intervals or to pulse morphology, from wrist-worn PPG signals recorded in free-living conditions.

On the generalizability of ECG-based obstructive sleep apnea monitoring: merits and limitations of the Apnea-ECG database.

Obstructive sleep apnea syndrome (OSAS) is a sleep disorder that affects a large part of the population and the development of algorithms using cardiovascular features for OSAS monitoring has been an extensively researched topic in the last two decades. Several studies regarding automatic apneic event classification using ECG derived features are based on the public Apnea-ECG database available on PhysioNet. Although this database is an excellent starting point for apnea topic investigations, in our study we show that algorithms for apneic-epochs classification that are successfully trained on this database (sensitivity < 85%, false detection rate <20%) perform poorly (sensitivity\textit<55%, false detection rate < 40%) in other databases which include patients with a broader spectrum of apneic events and sleep disorders. The reduced performance can be related to the complexity of breathing events, the increased number of non-breathing related sleep events, and the presence of non-OSAS sleep pathologies.