Subclinical atherosclerosis and accelerated epigenetic age mediated by inflammation: a multi-omics study.

AIMS: Epigenetic age is emerging as a personalized and accurate predictor of biological age. The aim of this article is to assess the association of subclinical atherosclerosis with accelerated epigenetic age and to investigate the underlying mechanisms mediating this association. METHODS AND RESULTS: Whole blood methylomics, transcriptomics, and plasma proteomics were obtained for 391 participants of the Progression of Early Subclinical Atherosclerosis study. Epigenetic age was calculated from methylomics data for each participant. Its divergence from chronological age is termed epigenetic age acceleration. Subclinical atherosclerosis burden was estimated by multi-territory 2D/3D vascular ultrasound and by coronary artery calcification. In healthy individuals, the presence, extension, and progression of subclinical atherosclerosis were associated with a significant acceleration of the Grim epigenetic age, a predictor of health and lifespan, regardless of traditional cardiovascular risk factors. Individuals with an accelerated Grim epigenetic age were characterized by an increased systemic inflammation and associated with a score of low-grade, chronic inflammation. Mediation analysis using transcriptomics and proteomics data revealed key pro-inflammatory pathways (IL6, Inflammasome, and IL10) and genes (IL1B, OSM, TLR5, and CD14) mediating the association between subclinical atherosclerosis and epigenetic age acceleration. CONCLUSION: The presence, extension, and progression of subclinical atherosclerosis in middle-aged asymptomatic individuals are associated with an acceleration in the Grim epigenetic age. Mediation analysis using transcriptomics and proteomics data suggests a key role of systemic inflammation in this association, reinforcing the relevance of interventions on inflammation to prevent cardiovascular disease.

Use of Uncertainty Calculation Software as a Didactic Tool to Improve the Knowledge of Chemistry Students in Analytical Method Validation.

Calculating analytical uncertainties as a part of method validation is a relevant aspect of field and laboratory practices in instrumental analytical chemistry subjects, which usually require complex algorithms. This work describes the development and didactic use of an automatic and straightforward informatics tool, implemented in an Excel macro, for calculating and interpreting the uncertainty of an analytical method against a reference method on field measurements. The software was initially developed for field testing of low-cost air quality monitoring analytical methods against reference methods, and the present work shows its adaptation to a didactic environment. The uncertainty calculation software was implemented through an Excel macro based on Visual Basic as a graphical user interface. It finds a best-fit line that describes the relation between concentrations determined by the candidate and reference methods. The software generates the analytical validation results (slope and intercept with their respective confidence limits, and expanded uncertainty of a concentration determined by the candidate method), hiding the intermediate functions and calculations. The Excel interface eases uncertainty calculations for undergraduate students, although the background mathematics can be quickly unveiled to students for didactic purposes. This tool has been applied to a laboratory exercise focused on validating experimental results obtained in the measurement of ozone levels in ambient air by passive sampling and spectrophotometric detection. The uncertainty calculation software has proved valuable by providing the student a resource to check the analytical quality of the data generated in the laboratory, while assimilating the fundamentals behind the calculations.

Entorno alimentario y su relación con obesidad en una población del noreste de México.

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Effects of Missing Data on Heart Rate Variability Metrics.

Heart rate variability (HRV) has been studied for decades in clinical environments. Currently, the exponential growth of wearable devices in health monitoring is leading to new challenges that need to be solved. These devices have relatively poor signal quality and are affected by numerous motion artifacts, with data loss being the main stumbling block for their use in HRV analysis. In the present paper, it is shown how data loss affects HRV metrics in the time domain and frequency domain and Poincaré plots. A gap-filling method is proposed and compared to other existing approaches to alleviate these effects, both with simulated (16 subjects) and real (20 subjects) missing data. Two different data loss scenarios have been simulated: (i) scattered missing beats, related to a low signal to noise ratio; and (ii) bursts of missing beats, with the most common due to motion artifacts. In addition, a real database of photoplethysmography-derived pulse detection series provided by Apple Watch during a protocol including relax and stress stages is analyzed. The best correction method and maximum acceptable missing beats are given. Results suggest that correction without gap filling is the best option for the standard deviation of the normal-to-normal intervals (SDNN), root mean square of successive differences (RMSSD) and Poincaré plot metrics in datasets with bursts of missing beats predominance (p<0.05), whereas they benefit from gap-filling approaches in the case of scattered missing beats (p<0.05). Gap-filling approaches are also the best for frequency-domain metrics (p<0.05). The findings of this work are useful for the design of robust HRV applications depending on missing data tolerance and the desired HRV metrics.

A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban Cyclists.

We present a device based on low-cost electrochemical and optical sensors, designed to be attached to bicycle handlebars, with the aim of monitoring the air quality in urban environments. The system has three electrochemical sensors for measuring NO2 and O3 and an optical particle-matter (PM) sensor for PM2.5 and PM10 concentrations. The electronic instrumentation was home-developed for this application. To ensure a constant air flow, the input fan of the particle sensor is used as an air supply pump to the rest of the sensors. Eight identical devices were built; two were collocated in parallel with a reference urban-air-quality-monitoring station and calibrated using a neural network (R2 > 0.83). Several bicycle routes were carried out throughout the city of Badajoz (Spain) to allow the device to be tested in real field conditions. An air-quality index was calculated to facilitate the user's understanding. The results show that this index provides data on the spatiotemporal variability of pollutants between the central and peripheral areas, including changes between weekdays and weekends and between different times of the day, thus providing valuable information for citizens through a dedicated cloud-based data platform.

Screen-Printed Gold Electrodes as Passive Samplers and Voltammetric Platforms for the Determination of Gaseous Elemental Mercury.

We present a methodology for the determination of gaseous elemental mercury (GEM). It is based on passive sampling of Hg on screen-printed gold electrodes (SPGEs), followed by the measurement of amalgamated mercury by square wave anodic stripping voltammetry. We have explored in detail the behavior of the SPGE electrode surface during the sampling process (by time-of-flight secondary ion mass spectrometry), the stability of the voltammetric signals, and the inter-electrode reproducibility, and obtained acceptable results. Adsorption of mercury onto the SPGE follows a nearly linear behavior until the sorbent becomes saturated (equilibrium phase) for different mercury concentrations, allowing to select a sampling time of 30 min for calibration. The theoretical behavior of the sampling system was modeled, considering the changes in the diffusive path length between the porous diffusive barrier and the adsorbed surface, L. Finally, we have tested two GEM calibration protocols. The first one is based on the measurement of the mercury stripping peak area, AHg, and the second one is based on the measurement of the mass of mercury, mHg, by standard additions. We found good correlation coefficients between the GEM concentration for both AHg (R2 = 0.9591) and mHg (R2 = 9615) in the range of 5.82 to 59.29 ng dm-3 GEM. Detection limits were 5.32 and 5.22 ng dm-3 for AHg and mHg, respectively. Our results open a new line of electroanalytical strategies for the determination of GEM in atmospheric samples.

Proposal for a Home Sleep Monitoring Platform Employing a Smart Glove.

The present paper proposes the design of a sleep monitoring platform. It consists of an entire sleep monitoring system based on a smart glove sensor called UpNEA worn during the night for signals acquisition, a mobile application, and a remote server called AeneA for cloud computing. UpNEA acquires a 3-axis accelerometer signal, a photoplethysmography (PPG), and a peripheral oxygen saturation (SpO2) signal from the index finger. Overnight recordings are sent from the hardware to a mobile application and then transferred to AeneA. After cloud computing, the results are shown in a web application, accessible for the user and the clinician. The AeneA sleep monitoring activity performs different tasks: sleep stages classification and oxygen desaturation assessment; heart rate and respiration rate estimation; tachycardia, bradycardia, atrial fibrillation, and premature ventricular contraction detection; and apnea and hypopnea identification and classification. The PPG breathing rate estimation algorithm showed an absolute median error of 0.5 breaths per minute for the 32 s window and 0.2 for the 64 s window. The apnea and hypopnea detection algorithm showed an accuracy (Acc) of 75.1%, by windowing the PPG in one-minute segments. The classification task revealed 92.6% Acc in separating central from obstructive apnea, 83.7% in separating central apnea from central hypopnea and 82.7% in separating obstructive apnea from obstructive hypopnea. The novelty of the integrated algorithms and the top-notch cloud computing products deployed, encourage the production of the proposed solution for home sleep monitoring.

Epidemiology of otorhinolaryngologic emergencies in a secondary hospital: analysis of 64,054 cases.

PURPOSE: To determine the incidence and distribution of care in relation to urgent otorhinolaryngologic pathologies by the different medical specialist units. METHODS: A descriptive, observational and retrospective study was conducted of patients seen by the Emergency Service at a secondary hospital over the course of 7 years (2011-2017). RESULTS: A total of 546,701 patients were seen during the period in question, of which 64,054 presented with otorhinolaryngologic symptoms. The attendance rate was 450/1000 inhabitants/year. The most frequent diagnoses were upper respiratory tract infection, with 13,639 cases (21.3%), tonsillopharyngitis, with 10,150 cases (15.8%) and vertigo/dizziness with 8761 cases (13.7%). Patients seen by the Hospital Emergency Service physicians and those referred to the Otorhinolaryngology or Paediatric Units were analysed both together and separately. The Hospital Emergency Service dealt with 77.1% of the cases, and referred 15.4% to the Otorhinolaryngology Unit and 7.5% to the Paediatrics Unit. Within the subgroup of patients referred to the Otorhinolaryngology Unit, the most frequent diagnoses were problems related to inflammatory ear disease (25.6%), followed by cervicofacial trauma (15.4%) and bleeding with otorhinolaryngologic symptoms (12.5%). The percentage of hospital admissions for the entire sample was 3%, while for patients referred to the Otorhinolaryngology Unit this figure was 6.8%. CONCLUSIONS: A large percentage of patients presenting at the Hospital Emergency Service do so with otorhinolaryngologic symptoms, and the vast majority are treated effectively by the physicians in that service and are referred to the specialist services on the basis of sound criteria.

Estimation of PM10 Levels and Sources in Air Quality Networks by Digital Analysis of Smartphone Camera Images Taken from Samples Deposited on Filters.

This paper explores the performance of smartphone cameras as low-cost and easily accessible tools to provide information about the levels and origin of particulate matter (PM) in ambient air. We tested the concept by digital analysis of the images of daily PM10 (particles with diameters 10 µm and smaller) samples captured on glass fibre filters by high-volume aerosol samplers at urban and rural locations belonging to the air quality monitoring network of Extremadura (Spain) for one year. The images were taken by placing the filters inside a box designed to maintain controlled and reproducible light conditions. Digital image analysis was carried out by a mobile colour-sensing application using red, green, blue/hue, saturation, value/hue, saturation, luminance (RGB/HSV/HSL) parameters, that were processed through statistical procedures, directly or transformed to greyscale. The results of the study show that digital image analysis of the filters can roughly estimate the concentration of PM10 within an air quality network, based on a significant linear correlation between the concentration of PM10 measured by an official gravimetric method and the colour parameters of the filters' images, with better results in the case of the saturation parameter (SHSV). The methodology based on digital analysis can discriminate urban and rural sampling locations affected by different local particle-emitting sources and is also able to identify the presence of remote sources such as Saharan dust outbreaks in both urban and rural locations. The proposed methodology can be considered as a useful complement to the aerosol sampling equipment of air quality network field units for a quick estimation of PM10 in the ambient air, through a simple, accessible and low-cost procedure, with further miniaturization potential.

Nafion-Protected Sputtered-Bismuth Screen-Printed Electrode for On-site Voltammetric Measurements of Cd(II) and Pb(II) in Natural Water Samples.

In this work, we explore the protection with Nafion of commercial sputtered-bismuth screen-printed electrodes (BiSPSPEs), to improve its ability for on-site determination of Cd(II) and Pb(II) ions in ambient water samples. The modified screen-printed platform was coupled with a miniaturized cell, in combination with a battery-operated stirring system and a portable potentiostat operated by a laptop for decentralized electrochemical measurements using Square-Wave Anodic Stripping Voltammetry (SWASV). We also describe a detailed electrode surface characterization by microscopy and surface analysis techniques, before and after the modification with Nafion, to get insight about modification effect on signal size and stability. Optimization of the chemical composition of the medium including the optimization of pH, and instrumental parameters, resulted in a method with detection limits in the low ng/mL range (3.62 and 3.83 ng·mL-1 for Cd and Pb respectively). Our results show an improvement of the sensitivity and stability for Nafion-protected BiSPSPEs in pH = 4.4 medium, and similar or lower detection limits than comparable methods on commercial BiSPSPEs. The values obtained for Pb(II) and Cd(II) in natural water samples agreed well with those obtained by the much more costly Inductively Coupled Plasma Mass Spectrometry, ICP-MS, technique as a reference method (recoveries from 75% to 111%).

A portable muon telescope based on small and gas-tight resistive plate chambers.

We report on the first steps in the development of a small-size muon telescope based on glass resistive plate chambers with small active area (16 × 16 cm2). The long-term goal of this project is to focus on applications of muography where the telescope may have to be operated underground and/or inside small rooms, and in challenging logistic situations. Driving principles in our design are therefore compact size, light weight, gas tightness and robustness. The first data-taking experiences have been encouraging, and we elaborate on the lessons learnt and future directions for development.This article is part of the Theo Murphy meeting issue 'Cosmic-ray muography'.

NINJA connects the co-repressor TOPLESS to jasmonate signalling.

Jasmonoyl-isoleucine (JA-Ile) is a plant hormone that regulates a broad array of plant defence and developmental processes. JA-Ile-responsive gene expression is regulated by the transcriptional activator MYC2 that interacts physically with the jasmonate ZIM-domain (JAZ) repressor proteins. On perception of JA-Ile, JAZ proteins are degraded and JA-Ile-dependent gene expression is activated. The molecular mechanisms by which JAZ proteins repress gene expression remain unknown. Here we show that the Arabidopsis JAZ proteins recruit the Groucho/Tup1-type co-repressor TOPLESS (TPL) and TPL-related proteins (TPRs) through a previously uncharacterized adaptor protein, designated Novel Interactor of JAZ (NINJA). NINJA acts as a transcriptional repressor whose activity is mediated by a functional TPL-binding EAR repression motif. Accordingly, both NINJA and TPL proteins function as negative regulators of jasmonate responses. Our results point to TPL proteins as general co-repressors that affect multiple signalling pathways through the interaction with specific adaptor proteins. This new insight reveals how stress-related and growth-related signalling cascades use common molecular mechanisms to regulate gene expression in plants.

Tracking Tidal Volume From Holter and Wearable Armband Electrocardiogram Monitoring.

A novel method for tracking the tidal volume (TV) from electrocardiogram (ECG) is presented. The method is based on the amplitude of ECG-derived respiration (EDR) signals. Three different morphology-based EDR signals and three different amplitude estimation methods have been studied, leading to a total of 9 amplitude-EDR (AEDR) signals per ECG channel. The potential of these AEDR signals to track the changes in TV was analyzed. These methods do not need a calibration process. In addition, a personalized-calibration approach for TV estimation is proposed, based on a linear model that uses all AEDR signals from a device. All methods have been validated with two different ECG devices: a commercial Holter monitor, and a custom-made wearable armband. The lowest errors for the personalized-calibration methods, compared to a reference TV, were -3.48% [-17.41% / 12.93%] (median [first quartile / third quartile]) for the Holter monitor, and 0.28% [-10.90% / 17.15%] for the armband. On the other hand, medians of correlations to the reference TV were higher than 0.8 for uncalibrated methods, while they were higher than 0.9 for personal-calibrated methods. These results suggest that TV changes can be tracked from ECG using either a conventional (Holter) setup, or our custom-made wearable armband. These results also suggest that the methods are not as reliable in applications that induce small changes in TV, but they can be potentially useful for detecting large changes in TV, such as sleep apnea/hypopnea and/or exacerbations of a chronic respiratory disease.

Persistent sleep-disordered breathing independently contributes to metabolic syndrome in prepubertal children.

BACKGROUND: Obstructive sleep apnea (OSA) is a risk factor for metabolic syndrome (MetS) in adults, but its association in prepubertal children is still questionable due to the relatively limited cardiometabolic data available and the phenotypic heterogeneity. OBJECTIVE: To identify the role of OSA as a potential mediator of MetS in prepubertal children. METHODS: A total of 255 prepubertal children from the Childhood Adenotonsillectomy Trial were included, with standardized measurements taken before OSA treatment and 7 months later. MetS was defined if three or more of the following criteria were present: adiposity, high blood pressure, elevated glycemia, and dyslipidemia. A causal mediation analysis was conducted to assess the effect of OSA treatment on MetS. RESULTS: OSA treatment significantly impacted MetS, with the apnea-hypopnea index emerging as mediator (p = .02). This mediation role was not detected for any of the individual risk factors that define MetS. We further found that the relationship between MetS and OSA is ascribable to respiratory disturbance caused by the apnea episodes, while systemic inflammation as measured by C-reactive protein, is mediated by desaturation events and fragmented sleep. In terms of evolution, patients with MetS were significantly more likely to recover after OSA treatment (odds ratio = 2.56, 95% confidence interval [CI] 1.20-5.46; risk ratio = 2.06, 95% CI 1.19-3.54) than the opposite, patients without MetS to develop it. CONCLUSION: The findings point to a causal role of OSA in the development of metabolic dysfunction, suggesting that persistent OSA may increase the risk of MetS in prepubertal children. This mediation role implies a need for developing screening for MetS in children presenting OSA symptoms.

Microbiological Survey and Evaluation of Antimicrobial Susceptibility Patterns of Microorganisms Obtained from Suspect Cases of Canine Otitis Externa in Gran Canaria, Spain.

A retrospective study of microbiological laboratory results from 2020 to 2022, obtained from a veterinary diagnostic laboratory of the island of Gran Canaria, Spain, focused on canine otitis cases, was performed. The objective of this study was to analyze the pathogen distribution, antimicrobial susceptibility, prevalence of multidrug resistant phenotypes and the role of coinfections in otitis cases in order to provide up-to-date evidence that could support effective control strategies for this prevalent pathology. A total of 604 submissions were processed for the diagnosis of canine external otitis. Of the samples analyzed, 472 were positive for bacterial or fungal growth (78.1%; 95% CI: 74.8-81.4%). A total of 558 microbiological diagnoses were obtained, divided in 421 bacterial (75.4%; 95% CI: 71.8-79.0%) and 137 fungal (24.6%; 95% CI: 20.9-28.1%) identifications. Staphylococcus pseudintermedius, Malassezia pachydermatis and Pseudomonas aeruginosa were the most prevalent microorganisms detected in clinical cases of otitis. High level antimicrobial resistance was found for Pseudomonas aeruginosa (30.7%), Proteus mirabilis (29.4%), Staphylococcus pseudintermedius (25.1%) and Escherichia coli (19%). Multidrug-resistant phenotypes were observed in 47% of the bacteria isolated. In addition, a 26.4% prevalence of methicillin-resistant Staphylococcus pseudintermedius was detected. The high prevalence of antimicrobial resistant phenotypes in these bacteria highlights the current necessity for constant up-to-date prevalence and antimicrobial susceptibility data that can support evidence-based strategies to effectively tackle this animal and public health concern.

Obstructive Sleep Apnea Screening by Joint Saturation Signal Analysis and PPG-derived Pulse Rate Oscillations.

Obstructive sleep apnea (OSA) is a high-prevalence disease in the general population, often underdiagnosed. The gold standard in clinical practice for its diagnosis and severity assessment is the polysomnography, although in-home approaches have been proposed in recent years to overcome its limitations. Today's ubiquitously presence of wearables may become a powerful screening tool in the general population and pulse-oximetry-based techniques could be used for early OSA diagnosis. In this work, the peripheral oxygen saturation together with the pulse-to-pulse interval (PPI) series derived from photoplethysmography (PPG) are used as inputs for OSA diagnosis. Different models are trained to classify between normal and abnormal breathing segments (binary decision), and between normal, apneic and hypopneic segments (multiclass decision). The models obtained 86.27% and 73.07% accuracy for the binary and multiclass segment classification, respectively. A novel index, the cyclic variation of the heart rate index (CVHRI), derived from PPI's spectrum, is computed on the segments containing disturbed breathing, representing the frequency of the events. CVHRI showed strong Pearson's correlation (r) with the apnea-hypopnea index (AHI) both after binary (r=0.94, p 0.001) and multiclass (r=0.91, p 0.001) segment classification. In addition, CVHRI has been used to stratify subjects with AHI higher/lower than a threshold of 5 and 15, resulting in 77.27% and 79.55% accuracy, respectively. In conclusion, patient stratification based on the combination of oxygen saturation and PPI analysis, with the addition of CVHRI, is a suitable, wearable friendly and low-cost tool for OSA screening at home.

Pediatric sleep apnea: Characterization of apneic events and sleep stages using heart rate variability.

Heart rate variability (HRV) is modulated by sleep stages and apneic events. Previous studies in children compared classical HRV parameters during sleep stages between obstructive sleep apnea (OSA) and controls. However, HRV-based characterization incorporating both sleep stages and apneic events has not been conducted. Furthermore, recently proposed novel HRV OSA-specific parameters have not been evaluated. Therefore, the aim of this study was to characterize and compare classic and pediatric OSA-specific HRV parameters while including both sleep stages and apneic events. A total of 1610 electrocardiograms from the Childhood Adenotonsillectomy Trial (CHAT) database were split into 10-min segments to extract HRV parameters. Segments were characterized and grouped by sleep stage (wake, W; non-rapid eye movement, NREMS; and REMS) and presence of apneic events (under 1 apneic event per segment, e/s; 1-5 e/s; 5-10 e/s; and over 10 e/s). NREMS showed significant changes in HRV parameters as apneic event frequency increased, which were less marked in REMS. In both NREMS and REMS, power in BW2, a pediatric OSA-specific frequency domain, allowed for the optimal differentiation among segments. Moreover, in the absence of apneic events, another defined band, BWRes, resulted in best differentiation between sleep stages. The clinical usefulness of segment-based HRV characterization was then confirmed by two ensemble-learning models aimed at estimating apnea-hypopnea index and classifying sleep stages, respectively. We surmise that basal sympathetic activity during REMS may mask apneic events-induced sympathetic excitation, thus highlighting the importance of incorporating sleep stages as well as apneic events when evaluating HRV in pediatric OSA.

Genomic and immune landscape Of metastatic pheochromocytoma and paraganglioma.

The mechanisms triggering metastasis in pheochromocytoma/paraganglioma are unknown, hindering therapeutic options for patients with metastatic tumors (mPPGL). Herein we show by genomic profiling of a large cohort of mPPGLs that high mutational load, microsatellite instability and somatic copy-number alteration burden are associated with ATRX/TERT alterations and are suitable prognostic markers. Transcriptomic analysis defines the signaling networks involved in the acquisition of metastatic competence and establishes a gene signature related to mPPGLs, highlighting CDK1 as an additional mPPGL marker. Immunogenomics accompanied by immunohistochemistry identifies a heterogeneous ecosystem at the tumor microenvironment level, linked to the genomic subtype and tumor behavior. Specifically, we define a general immunosuppressive microenvironment in mPPGLs, the exception being PD-L1 expressing MAML3-related tumors. Our study reveals canonical markers for risk of metastasis, and suggests the usefulness of including immune parameters in clinical management for PPGL prognostication and identification of patients who might benefit from immunotherapy.

The 2023 wearable photoplethysmography roadmap.

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.

Impact of the PPG Sampling Rate in the Pulse Rate Variability Indices Evaluating Several Fiducial Points in Different Pulse Waveforms.

The main aim of this work is to study the effect of the sampling rate of the photoplethysmographic (PPG) signal for pulse rate variability (PRV) analysis. Forehead and finger PPG signals were recorded at 1000 Hz during a rest state, with red and infrared wavelengths, simultaneously with the electrocardiogram (ECG). The PPG sampling rate has been reduced by decimation, obtaining signals at 500 Hz, 250 Hz, 125 Hz, 100 Hz, 50 Hz and 25 Hz. Five fiducial points were computed: apex, up-slope, medium, line-medium and medium interpolate point. The medium point is located in the middle of the up-slope of the pulse. The medium interpolate point is a new proposal as fiducial point that consider the abrupt up-slope of the PPG pulse, so it can be recovered by linear interpolation when the sampling rate is reduced. The error performed in the temporal location of the fiducial points was computed. Pulse period time interval series were obtained from all PPG signals and fiducial points, and compared with the RR intervals obtained from the ECG. Heart rate variability and PRV signals were estimated and classical time and frequency domain indices were computed. The results showed that the medium interpolate point of the PPG pulse was the most accurate fiducial point under different PPG morphologies and sensor locations, when sampling rate was reduced. Being able to reduce the sampling rate to 50 Hz without causing significant changes in time and frequency indices, when medium interpolate point was used as fiducial point.