Real-Time Evaluation of Time-Domain Pulse Rate Variability Parameters in Different Postures and Breathing Patterns Using Wireless Photoplethysmography Sensor: Towards Remote Healthcare in Low-Resource Communities.

Photoplethysmography (PPG) signals have been widely used in evaluating cardiovascular biomarkers, however, there is a lack of in-depth understanding of the remote usage of this technology and its viability for underdeveloped countries. This study aims to quantitatively evaluate the performance of a low-cost wireless PPG device in detecting ultra-short-term time-domain pulse rate variability (PRV) parameters in different postures and breathing patterns. A total of 30 healthy subjects were recruited. ECG and PPG signals were simultaneously recorded in 3 min using miniaturized wearable sensors. Four heart rate variability (HRV) and PRV parameters were extracted from ECG and PPG signals, respectively, and compared using analysis of variance (ANOVA) or Scheirer-Ray-Hare test with post hoc analysis. In addition, the data loss was calculated as the percentage of missing sampling points. Posture did not present statistical differences across the PRV parameters but a statistical difference between indicators was found. Strong variation was found for the RMSSD indicator in the standing posture. The sitting position in both breathing patterns demonstrated the lowest data loss (1.0 ± 0.6 and 1.0 ± 0.7) and the lowest percentage of different factors for all indicators. The usage of commercial PPG and BLE devices can allow the reliable extraction of the PPG signal and PRV indicators in real time.

Measuring Heart Rate Variability Using Facial Video.

Heart Rate Variability (HRV) has become an important risk assessment tool when diagnosing illnesses related to heart health. HRV is typically measured with an electrocardiogram; however, there are multiple studies that use Photoplethysmography (PPG) instead. Measuring HRV with video is beneficial as a non-invasive, hands-free alternative and represents a more accessible approach. We developed a methodology to extract HRV from video based on face detection algorithms and color augmentation. We applied this methodology to 45 samples. Signals obtained from PPG and video recorded an average mean error of less than 1 bpm when measuring the heart rate of all subjects. Furthermore, utilizing PPG and video, we computed 61 variables related to HRV. We compared each of them with three correlation metrics (i.e., Kendall, Pearson, and Spearman), adjusting them for multiple comparisons with the Benjamini-Hochberg method to control the false discovery rate and to retrieve the q-value when considering statistical significance lower than 0.5. Using these methods, we found significant correlations for 38 variables (e.g., Heart Rate, 0.991; Mean NN Interval, 0.990; and NN Interval Count, 0.955) using time-domain, frequency-domain, and non-linear methods.

Analysis of Relevant Features from Photoplethysmographic Signals for Atrial Fibrillation Classification.

Atrial Fibrillation (AF) is the most common cardiac arrhythmia found in clinical practice. It affects an estimated 33.5 million people, representing approximately 0.5% of the world's population. Electrocardiogram (ECG) is the main diagnostic criterion for AF. Recently, photoplethysmography (PPG) has emerged as a simple and portable alternative for AF detection. However, it is not completely clear which are the most important features of the PPG signal to perform this process. The objective of this paper is to determine which are the most relevant features for PPG signal analysis in the detection of AF. This study is divided into two stages: (a) a systematic review carried out following the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) statement in six databases, in order to identify the features of the PPG signal reported in the literature for the detection of AF, and (b) an experimental evaluation of them, using machine learning, in order to determine which have the greatest influence on the process of detecting AF. Forty-four features were found when analyzing the signal in the time, frequency, or time-frequency domains. From those 44 features, 27 were implemented, and through machine learning, it was found that only 11 are relevant in the detection process. An algorithm was developed for the detection of AF based on these 11 features, which obtained an optimal performance in terms of sensitivity (98.43%), specificity (99.52%), and accuracy (98.97%).

Systematic Review on Features Extracted from PPG Signals for the Detection of Atrial Fibrillation.

PROBLEM: Atrial Fibrillation (AF) is the most common sustained cardiac arrhythmia. It constitutes one of the leading cardiovascular health problems, affecting 33.5 million people of the world's population. AF detection is commonly made by an Electrocardiogram (EEG). Nevertheless, with the advances in biomedical sensors, innovative approaches have emerged on detecting AF based on the analysis of signals acquired by photoplethysmography (PPG) sensors. OBJECTIVE: This paper aims to provide a systematic review to determine the features that have been used to detect Atrial Fibrillation in PPG signals. METHODS: A systematic review of six databases (Pubmed, Science Direct, Scopus, IEEE Xplore, Engineering Village y Mendeley) was carried out following the PRISMA-DTA statement (Preferred Reporting Items for Systematic Reviews and Meta-Analyses on Diagnostic Test Accuracy). RESULTS: This article provides an analysis of the features extracted for the detection of Atrial Fibrillation in photoplethysmography signals from 16 studies. It was found 44 features: 29 were extracted from the signal analyzed in the time domain, 12 from the signal analyzed in the frequency domain, and 3 from the signal analyzed in the time-frequency domain. CONCLUSIONS: The systematic review allowed obtaining the features reported in the literature with higher performance in the detection of AF in terms of sensitivity, specificity, and accuracy. It was possible to observe a clear tendency to analyze the PPG signal in the time domain, although some studies have obtained better performance in the classification of AF when analyzing features in the frequency and time-frequency domains.

Relación entre las dimensiones de personalidad según el P-IPG y la calidad de vida laboral percibida / Relação das dimensões de personalidade segundo o P-IPG e a qualidade de vida profissional percebida / The relation between personality dimensions according to P-IPG and the perceived labor life quality

Resumen La calidad de vida laboral (CVL) y la personalidad constituyen dos de los tópicos de mayor interés en la investigación del comportamiento humano en la organización. La presente investigación tuvo como objetivo identificar si es posible predecir la CVL a partir de algunas dimensiones de personalidad. Para su desarrollo, se utilizó un diseño descriptivo correlacional con una muestra conformada por 145 trabajadores de cinco empresas del sector privado de la ciudad de Bogotá. La personalidad se evaluó por medio de la prueba PPG-IPG, de Gordon (1993), y para la calidad de vida se utilizó el PCVL, de Gómez-Rada (2010). Se analizaron los resultados por medio estadísticos descriptivos y de carácter correlacional entre las variables con los coeficientes producto momento de Pearson y los rangos de Spearman. Los resultados muestran que la valoración de la CVL se encuentra relacionada positivamente con el hecho de que el trabajador muestre una personalidad más positiva, en términos de mayor autoestima, cautela, originalidad, comprensión y vitalidad.

Resumo A qualidade de vida profissional (QVP) e a personalidade constituem dois dos tópicos de maior interesse na pesquisa do comportamento humano na organização. Esta pesquisa teve como objetivo identificar se é possível predizer a QVP a partir de algumas dimensões de personalidade. Para seu desenvolvimento, foi utilizado um desenho descritivo correlacional com uma amostra conformada por 145 trabalhadores de cinco empresas do setor privado da cidade de Bogotá, Colômbia. A personalidade foi avaliada por meio do teste PPG-IPG, de Gordon (1993), e para a qualidade de vida foi utilizado o PCVL, de Gómez-Rada e Ponce de León (2010). Foram analisados os resultados por meios estatísticos descritivos e de caráter correlacional entre as variáveis com os coeficientes produto momento de Pearson e as categorias de Spearman. Os resultados mostram que a avaliação da QVP se encontra relacionada positivamente com o fato de o trabalhador mostrar uma personalidade mais positiva, em termos de mais autoestima, cautela, originalidade, compreensão e vitalidade.

Abstract Labor life quality (CVL, for its Spanish acronym) and personality conform two of the most interesting topics in human behavior research within the organization. The aim of this research was to identify whether it was possible to predict CVL as of some personality dimensions. To do so a correlational descriptive design was used. The sampling was made up of 145 workers at 5 private sector companies in the city of Bogotá. Personality was evaluated through the Gordon PPG-IPG test, and for life quality, Gómez PCVL (2010) was used. The results were analyzed by means of descriptive statistics and the relation between variables was analyzed through Pearson moment-product coefficients and Spearman ranges. Results show that CVL valuation is positively related to the fact that the worker shows a more positive personality in terms of greater self-steem, caution, originality, understanding, and vitality.

A novel and low-complexity peak detection algorithm for heart rate estimation from low-amplitude photoplethysmographic (PPG) signals.

Low-amplitude PPG signals are more affected by noise contamination and other undesirable effects because the signal strength is comparable to noise power. Although several authors claim that decreases in the amplitude of the PPG wave should be addressed from signal acquisition and conditioning stages such decreases can also be associated with changes in the patient condition. In that instance, it is important to ensure continuous and reliable HR monitoring which, in turn, depends on how robust is the peak detection method. Numerous efforts have been made to develop algorithms for accurate PPG peak detection under high motion artefact conditions. However, little has been done regarding peak detection in low-amplitude PPG signals. In an attempt to address this issue, a novel and simple peak detection algorithm for PPG signals was proposed. Results show that our method could be a good contribution for robust strategies that can dynamically adapt their peak detection method to circumstances in which a decrease in the amplitude of the PPG signal is expected. Still, more extensive testing under a wide range of conditions (e.g. intensive physical exercise) is needed to perform a rigorous validation.

Prolonged activation of human islet cannabinoid receptors in vitro induces adaptation but not dysfunction.

BACKGROUND: Although in vivo studies have implicated endocannabinoids in metabolic dysfunction, little is known about direct, chronic activation of the endocannabinoid system (ECS) in human islets. Therefore, this study investigated the effects of prolonged exposure to cannabinoid agonists on human islet gene expression and function. METHODS: Human islets were maintained for 2 and 5 days in the absence or presence of CB1r (ACEA) or CB2r (JWH015) agonists. Gene expression was quantified by RT-PCR, hormone levels by radioimmunoassay and apoptosis by caspase activities. RESULTS: Human islets express an ECS, with mRNAs encoding the biosynthetic and degrading enzymes NAPE-PLD, FAAH and MAGL being considerably more abundant than DAGLα, an enzyme involved in 2-AG synthesis, or CB1 and CB2 receptor mRNAs. Prolonged activation of CB1r and CB2r altered expression of mRNAs encoding ECS components, but did not have major effects on islet hormone secretion. JWH015 enhanced insulin and glucagon content at 2 days, but had no effect after 5 days. Treatment with ACEA or JWH015 for up to 5 days did not have marked effects on islet viability, as assessed by morphology and caspase activities. CONCLUSIONS: Maintenance of human islets for up to 5 days in the presence of CB1 and CB2 receptor agonists causes modifications in ECS element gene expression, but does not have any major impact on islet function or viability. GENERAL SIGNIFICANCE: These data suggest that the metabolic dysfunction associated with over-activation of the ECS in obesity and diabetes in humans is unlikely to be secondary to impaired islet function.

Polydiacetylene/triblock copolymer nanoblend applied as a sensor for micellar casein: A thermodynamic approach.

Polydiacetylene (PDA) and triblock copolymer nanoblends were synthesized to detect micellar casein (MC), the main milk protein and an indicator of milk quality. UV-Vis spectrum showed that MC induced blue-to-red transition in nanoblends. When nanoblends and MC were separated by dialysis membrane colorimetric response (CR) was similar, whereas a remarkable CR reduction was noticed after addition of dialyzed-MC, suggesting that small molecules present in MC (salts) caused PDA color change. Interaction enthalpy variation between nanoblends and MC showed an abrupt increase that coincided with MC concentration when colorimetric transition occurred. Copolymer hydrophobic/hydrophilic balance and presence of other molecules in the system affected nanoblends CR. MC salts were found to interact with nanoblends leading to color changes. MC concentration, MC salt release, copolymer hydrophobic/hydrophilic balance, and presence of other molecules in the system affected responses of the sensors. These results contribute to future applications of PDA/copolymer nanosensors to dairy models.

Heart Rate Variability Analysis Based on Photoplethysmographic Signals

An algorithm for extracting tachograms for Heart Rate Variability (HRV) analysis on the basis of Photoplethysmographic (PPG) signals (instead of electro cardiograms) has been proposed. The main feature of this proposal is to detect peaks from correlograms between a pattern waveform and a sliding time window in the PPG signal. Analysis was carried out with a set of two groups of patients (young and elderly).HRV variables were estimated using the publicly available Kubios HRV package. Results showed that both the sympathetic component of the autonomous nervous system (assessed by LF/HF) and the cardiovascular complexity (assessed by correlation dimension) are reduced with age. These results are supported by literature and may be taken as a support for the validity of the proposed algorithm. Since oximeters for getting PPG signals are affordable even in poor settings, this allows extending autonomic nervous system studies into remote areas of developing countries(AU)

Se propone un algoritmo para obtener tacogramas con la finalidad de realizar estudios de variabilidad de la frecuencia cardiaca, partiendo de registros de señales fotopletismográficas (PPG). La principal peculiaridad de esta propuesta lo es la detección de los picos en las ondas de la señal PPG a partir de un correlograma obtenido como una secuencia de correlaciones entre una onda patrón y una ventana deslizante de la señal PPG. Se realizó un análisis de variabilidad de frecuencia cardiaca sobre dos grupos de pacientes (jóvenes y de avanzada edad). Las variables de variabilidad de frecuencia cardiaca seleccionadas se obtuvieron a partir del programa Kubios HRV, de acceso público y gratuito. Los resultados mostraron que tanto el componente simpático del Sistema Nervioso Autónomo (evaluado a través de la variable LF/HF) como la complejidad cardiovascular (evaluada a través de la dimensión de correlación) disminuyeron con la edad. Estos resultados encuentran apoyo en datos de la literatura que apoyan así la validez del algoritmo propuesto. Por cuanto el oxímetro utilizado para obtener las señales PPG está al alcance de instituciones primarias de salud se hace posible de esta manera extender estudios del sistema nervioso autónomo hacia áreas remotas de países en desarrollo(AU)

Role of hydrogen sulfide in the pain processing of non-diabetic and diabetic rats.

Hydrogen sulfide (H2S) is a gasotransmitter endogenously generated from the metabolism of L-cysteine by action of two main enzymes called cystathionine ß-synthase (CBS) and cystathionine γ-lyase (CSE). This gas has been involved in the pain processing and insulin resistance produced during diabetes development. However, there is no evidence about its participation in the peripheral neuropathy induced by this metabolic disorder. Experimental diabetes was induced by streptozotocin (50mg/kg, i.p.) in female Wistar rats. Streptozotocin injection increased formalin-evoked flinching in diabetic rats as compared to non-diabetic rats after 2 weeks. Peripheral administration of NaHS (an exogenous donor of H2S) and L-cysteine (an endogenous donor of H2S) dose-dependently increased flinching behavior in diabetic and non-diabetic rats. Contrariwise, hydroxylamine (HA, a CBS inhibitor) and DL-propargylglycine (PPG, a CSE inhibitor) decreased formalin-induced nociceptive behavior in both experimental groups. In addition, an ineffective dose of HA and PPG partially prevented the L-cysteine-induced hyperalgesia in diabetic and non-diabetic rats. Interestingly, HA and PPG were three order of magnitude more potent in diabetic rats respect to non-diabetic rats, whereas NaHS was ten times more potent in the streptozotocin-diabetic group. Nine to 11 weeks after diabetes induction, tactile allodynia was observed in the streptozotocin-injected rats. On this condition, subcutaneous administration of PPG or HA reduced tactile allodynia in diabetic rats. Paradoxically, H2S levels were decreased in nerve sciatic, dorsal root ganglion and spinal cord, but not paw nor blood plasma, during diabetes-associated peripheral neuropathy development. Collectively, results suggest that H2S synthesized by CBS and CSE participate in formalin-induced nociception in diabetic and non-diabetic rats, as well as; in tactile allodynia in streptozotocin-injected rats. In addition, data seems to indicate that diabetic rats are more sensible to H2S-induced hyperalgesia than normoglycemic rats.