scholarly journals DETECÇÃO EM TEMPO REAL DA FREQUÊNCIA CARDÍACA DE PESSOAS POR MEIO DA ANÁLISE DE VARIAÇÕES TEMPORAIS EM VÍDEOS

e-xacta ◽  
2016 ◽  
Vol 9 (1) ◽  
pp. 49 ◽  
Author(s):  
Kessiler Almeida Silveira Rodrigues ◽  
Moisés Henrique Ramos Pereira ◽  
Flávio Luis Cardeal Pádua
Keyword(s):  
Heart Rate ◽  
Continuous Monitoring ◽  
Vital Signs ◽  
Computational Method ◽  
Burn Victims ◽  
Non Invasive ◽  
Statistical Confidence ◽  
Common Causes ◽  
Supportive Environments

<p>As doenças cardiovasculares são, atualmente, as causas mais comuns de morbimortalidade no mundo. Na perspectiva da prevenção de doenças e agravos, tornam-se fundamentais ações que criem ambientes favoráveis à saúde e favoreçam escolhas saudáveis. Medidas de prevenção e monitoramento contínuo de sinais vitais são necessários, sendo a frequência cardíaca um sinal promissor. No entanto, tal monitoramento pode ser difícil e pouco eficiente, quando não impossível, em determinados casos, como por exemplo, vítimas de queimaduras. Este artigo propõe uma aplicação para monitoramento da frequência cardíaca não invasivo e sem a necessidade de contato, podendo ser manuseado por qualquer pessoa. Para a determinação da frequência cardíaca, a aplicação combina técnicas de processamento de imagens, tratamento de sinais fotopletismográficos e análise de variações temporais em vídeos. Os resultados obtidos demonstram que, considerando 95% de confiança estatística e um erro padrão de 1,08 batimentos por minuto, a aplicação desenvolvida possui a mesma média para aferições de batimentos cardíacos em relação a um dispositivo já consolidado no mercado para essa finalidade, mostrando-se como um método computacional promissor para medições em repouso.</p><p>Abstract </p><p>Cardiovascular diseases are currently the most common causes of morbidity and mortality worldwide. From the perspective of prevention of diseases and disorders, become fundamental actions that create supportive environments for health and promote healthy choices. Prevention and continuous monitoring of vital signs are necessary, and the heart rate a promising sign. However, such monitoring can be difficult and inefficient, if not impossible, in certain cases, such as burn victims. This paper proposes an application for monitoring heart rate non-invasive and without the need to touch and can be handled by anyone. For the determination of heart rate the application combines techniques of image processing, processing and analysis of signals photo-plethysmography temporal changes in video. The obtained results show that, considering a 95% statistical confidence and a standard error of 1.08 beats per minute, the developed application has the same average heartbeats' measurements in relation to a consolidated device on the market used for the same purpose, showing itself as a promising computational method for rest measurements.</p>

Continuous Auscultation of Heart and Bilateral Breath Sounds

PEDIATRICS ◽  
1988 ◽  
Vol 81 (5) ◽  
pp. 745-746
Author(s):  
NATHAN SCHWARTZ ◽  
JAMES B. EISENKRAFT
Keyword(s):  
Heart Rate ◽  
Critically Ill ◽  
Vital Signs ◽  
Sleep Pattern ◽  
Monitoring Device ◽  
Challenging Problem ◽  
Breath Sounds ◽  
Increased Risk ◽  
Risk Of Exposure

To the Editor.— The frequent determination of vital signs, such as heart rate and bilateral breath sounds, is a mainstay in the care of critically ill infants. Unfortunately, the routine determination of such vital signs involves the manipulation and disturbance of the infant, unnecessary risk of exposure to cold, increased risk of apnea, and infection.1,2 In addition, the frequent disruption of the infant's sleep pattern may take an unaccountable physiologic and psychologic toll. To deal with this common and challenging problem we have devised a simple and inexpensive monitoring device, using readily available supplies, which facilitates the continuous or intermittent evaluation of heart rate and bilateral breath sounds.

scholarly journals Extraction of Fetal Heart Rate from Maternal ECG—Non Invasive Approach for Continuous Monitoring during Labor

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 1009 ◽  
Author(s):  
Tashreque Mohammed Haq ◽  
Safkat Arefin ◽  
Shamiur Rahman ◽  
Tanzilur Rahman
Keyword(s):  
Heart Rate ◽  
Fetal Heart Rate ◽  
Continuous Monitoring ◽  
Good Accuracy ◽  
Fetal Heart ◽  
Signal Separation ◽  
Invasive Approach ◽  
Non Invasive ◽  
Proposed Model ◽  
Fetal Scalp

Here, we propose a signal processing based approach for the extraction of the fetal heart rate (FHR) from Maternal Abdominal ECG (MAECG) in a non-invasive way. Datasets from a Physionet database has been used in this study for evaluating the performance of the proposed model that performs three major tasks; preprocessing of the MAECG signal, separation of Fetal QRS complexes from that of maternal and estimation of Fetal R peak positions. The MAECG signal is first preprocessed with improved multistep filtering techniques to detect the Maternal QRS (MQRS) complexes, which are dominant in the MAECG. A reference template is then reconstructed based on MQRS locations and removed from the preprocessed signal resulting in the raw FECG. This extracted FECG is further corrected and enhanced before obtaining the Fetal R peaks. The detection of FQRS and calculation of FHR has been compared against the reference Fetal Scalp ECG. Results indicate that the approach achieved good accuracy.

scholarly journals A dataset of clinically recorded radar vital signs with synchronised reference sensor signals

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Sven Schellenberger ◽  
Kilin Shi ◽  
Tobias Steigleder ◽  
Anke Malessa ◽  
Fabian Michler ◽  
...  
Keyword(s):  
Continuous Monitoring ◽  
Continuous Wave ◽  
Vital Signs ◽  
Radar System ◽  
Tilt Table ◽  
Non Invasive ◽  
Impedance Cardiogram ◽  
Wave Radar ◽  
Reference Device ◽  
Sensor Signals

Abstract Using Radar it is possible to measure vital signs through clothing or a mattress from the distance. This allows for a very comfortable way of continuous monitoring in hospitals or home environments. The dataset presented in this article consists of 24 h of synchronised data from a radar and a reference device. The implemented continuous wave radar system is based on the Six-Port technology and operates at 24 GHz in the ISM band. The reference device simultaneously measures electrocardiogram, impedance cardiogram and non-invasive continuous blood pressure. 30 healthy subjects were measured by physicians according to a predefined protocol. The radar was focused on the chest while the subjects were lying on a tilt table wired to the reference monitoring device. In this manner five scenarios were conducted, the majority of them aimed to trigger hemodynamics and the autonomic nervous system of the subjects. Using the database, algorithms for respiratory or cardiovascular analysis can be developed and a better understanding of the characteristics of the radar-recorded vital signs can be gained.

Longitudinal Analysis of Continuous Pulse Oximetry as Prognostic Factor in Neonatal Respiratory Distress

2020 ◽  
Author(s):  
Gonzalo Solís-García ◽  
Elena Maderuelo-Rodríguez ◽  
Teresa Perez-Pérez ◽  
Laura Torres-Soblechero ◽  
Ana Gutiérrez-Vélez ◽  
...  
Keyword(s):  
Heart Rate ◽  
Intensive Care ◽  
Respiratory Distress ◽  
Oxygen Saturation ◽  
Continuous Monitoring ◽  
Vital Signs ◽  
Epidemiological Data ◽  
Monitoring Data ◽  
Joint Models ◽  
Neonatal Icu

Objective Analysis of longitudinal data can provide neonatologists with tools that can help predict clinical deterioration and improve outcomes. The aim of this study is to analyze continuous monitoring data in newborns, using vital signs to develop predictive models for intensive care admission and time to discharge. Study Design We conducted a retrospective cohort study, including term and preterm newborns with respiratory distress patients admitted to the neonatal ward. Clinical and epidemiological data, as well as mean heart rate and saturation, at every minute for the first 12 hours of admission were collected. Multivariate mixed, survival and joint models were developed. Results A total of 56,377 heart rate and 56,412 oxygen saturation data were analyzed from 80 admitted patients. Of them, 73 were discharged home and 7 required transfer to the intensive care unit (ICU). Longitudinal evolution of heart rate (p < 0.01) and oxygen saturation (p = 0.01) were associated with time to discharge, as well as birth weight (p < 0.01) and type of delivery (p < 0.01). Longitudinal heart rate evolution (p < 0.01) and fraction of inspired oxygen at admission at the ward (p < 0.01) predicted neonatal ICU (NICU) admission. Conclusion Longitudinal evolution of heart rate can help predict time to transfer to intensive care, and both heart rate and oxygen saturation can help predict time to discharge. Analysis of continuous monitoring data in patients admitted to neonatal wards provides useful tools to stratify risks and helps in taking medical decisions. Key Points

scholarly journals Reliability of heart rate and respiration rate measurements with a wireless accelerometer in postbariatric recovery

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0247903
Author(s):  
Fleur Jacobs ◽  
Jai Scheerhoorn ◽  
Eveline Mestrom ◽  
Jonna van der Stam ◽  
R. Arthur Bouwman ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiration Rate ◽  
Gold Standard ◽  
Continuous Monitoring ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Patient Monitor ◽  
Standard Patient ◽  
Bariatric Patients ◽  
Vital Parameters

Recognition of early signs of deterioration in postoperative course could be improved by continuous monitoring of vital parameters. Wearable sensors could enable this by wireless transmission of vital signs. A novel accelerometer-based device, called Healthdot, has been designed to be worn on the skin to measure the two key vital parameters respiration rate (RespR) and heart rate (HeartR). The goal of this study is to assess the reliability of heart rate and respiration rate measured by the Healthdot in comparison to the gold standard, the bedside patient monitor, during the postoperative period in bariatric patients. Data were collected in a consecutive group of 30 patients who agreed to wear the device after their primary bariatric procedure. Directly after surgery, a Healthdot was attached on the patients’ left lower rib. Vital signs measured by the accelerometer based Healthdot were compared to vital signs collected with the gold standard patient monitor for the period that the patient stayed at the post-anesthesia care unit. Over all patients, a total of 22 hours of vital signs obtained by the Healthdot were recorded simultaneously with the bedside patient monitor data. 87.5% of the data met the pre-defined bias of 5 beats per minute for HeartR and 92.3% of the data met the pre-defined bias of 5 respirations per minute for RespR. The Healthdot can be used to accurately derive heart rate and respiration rate in postbariatric patients. Wireless continuous monitoring of key vital signs has the potential to contribute to earlier recognition of complications in postoperative patients. Future studies should focus on the ability to detect patient deterioration in low-care environments and at home after discharge from the hospital.

Auricall®. A new device for a non-invasive, wireless, continuous monitoring of oxygen saturation and heart rate in patients with heart failure

2008 ◽  
Vol 129 (1) ◽  
pp. 141-143 ◽  
Author(s):  
Isabella Sudano ◽  
Andreas J. Flammer ◽  
Frank Hermann ◽  
Thomas Syburra ◽  
Priska Kaiser ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Oxygen Saturation ◽  
Continuous Monitoring ◽  
New Device ◽  
Non Invasive ◽  
Patients With Heart Failure

scholarly journals A Novel Unsupervised Computational Method for Ventricular and Supraventricular Origin Beats Classification

2021 ◽  
Vol 11 (15) ◽  
pp. 6711
Author(s):  
Manuel M. Casas ◽  
Roberto L. Avitia ◽  
Jose Antonio Cardenas-Haro ◽  
Jugal Kalita ◽  
Francisco J. Torres-Reyes ◽  
...  
Keyword(s):  
Heart Rate ◽  
Scientific Community ◽  
Continuous Monitoring ◽  
Automatic Detection ◽  
Morphological Features ◽  
Computational Method ◽  
Historic Data ◽  
General Classifier ◽  
Ecg Data

Arrhythmias are the most common events tracked by a physician. The need for continuous monitoring of such events in the ECG has opened the opportunity for automatic detection. Intra- and inter-patient paradigms are the two approaches currently followed by the scientific community. The intra-patient approach seems to resolve the problem with a high classification percentage but requires a physician to label key samples. The inter-patient makes use of historic data of different patients to build a general classifier, but the inherent variability in the ECG’s signal among patients leads to lower classification percentages compared to the intra-patient approach. In this work, we propose a new unsupervised algorithm that adapts to every patient using the heart rate and morphological features of the ECG beats to classify beats between supraventricular origin and ventricular origin. The results of our work in terms of F-score are 0.88, 0.89, and 0.93 for the ventricular origin beats for three popular ECG databases, and around 0.99 for the supraventricular origin for the same databases, comparable to supervised approaches presented in other works. This paper presents a new path to make use of ECG data to classify heartbeats without the assistance of a physician despite the needed improvements.

scholarly journals New Device for Noninvasive Telemetric Monitoring of Vital Signs in Healthy and Newly Operated Piglets

2020 ◽  
Vol 59 (1) ◽  
pp. 90-93
Author(s):  
Nikolaj Bøgh ◽  
Peter Agger ◽  
Camilla Omann ◽  
Martin N Skov ◽  
Christoffer laustsen ◽  
...  
Keyword(s):  
Heart Rate ◽  
Data Quality ◽  
Respiration Rate ◽  
Medical Practice ◽  
Vital Signs ◽  
Interquartile Range ◽  
Laboratory Animals ◽  
New Device ◽  
Noninvasive Monitor

Measuring vital signs is central to medical practice, but they are difficult to monitor in awake laboratory animals. We examined the feasibility of a noninvasive device for telemetric assessment of respiration rate, heart rate, temperature and movement in pigs. Awake piglets were monitored continuously for 31 h (interquartile range, 7) before (n = 4) and after (n = 3) surgery. Data quality was sufficient for determination of all parameters. We conclude that continuous, noninvasive monitor- ing of pigs is possible by using the evaluated device.

scholarly journals Vital Signs Prediction and Early Warning Score Calculation Based on Continuous Monitoring of Hospitalised Patients Using Wearable Technology

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6593
Author(s):  
Ahmed Youssef Ali Amer ◽  
Femke Wouters ◽  
Julie Vranken ◽  
Dianne de Korte-de Boer ◽  
Valérie Smit-Fun ◽  
...  
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Real Time ◽  
Early Warning ◽  
Continuous Monitoring ◽  
Time Series Prediction ◽  
Vital Signs ◽  
Wearable Technology ◽  
High Rate ◽  
Hospitalised Patients

In this prospective, interventional, international study, we investigate continuous monitoring of hospitalised patients’ vital signs using wearable technology as a basis for real-time early warning scores (EWS) estimation and vital signs time-series prediction. The collected continuous monitored vital signs are heart rate, blood pressure, respiration rate, and oxygen saturation of a heterogeneous patient population hospitalised in cardiology, postsurgical, and dialysis wards. Two aspects are elaborated in this study. The first is the high-rate (every minute) estimation of the statistical values (e.g., minimum and mean) of the vital signs components of the EWS for one-minute segments in contrast with the conventional routine of 2 to 3 times per day. The second aspect explores the use of a hybrid machine learning algorithm of kNN-LS-SVM for predicting future values of monitored vital signs. It is demonstrated that a real-time implementation of EWS in clinical practice is possible. Furthermore, we showed a promising prediction performance of vital signs compared to the most recent state of the art of a boosted approach of LSTM. The reported mean absolute percentage errors of predicting one-hour averaged heart rate are 4.1, 4.5, and 5% for the upcoming one, two, and three hours respectively for cardiology patients. The obtained results in this study show the potential of using wearable technology to continuously monitor the vital signs of hospitalised patients as the real-time estimation of EWS in addition to a reliable prediction of the future values of these vital signs is presented. Ultimately, both approaches of high-rate EWS computation and vital signs time-series prediction is promising to provide efficient cost-utility, ease of mobility and portability, streaming analytics, and early warning for vital signs deterioration.

Sign in / Sign up

Export Citation Format

Share Document