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

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.

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Continuous Auscultation of Heart and Bilateral Breath Sounds

PEDIATRICS ◽

10.1542/peds.81.5.745b ◽

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.

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

PLoS ONE ◽

10.1371/journal.pone.0247903 ◽

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.

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Contactless Vital Signs Measurement System Using RGB-Thermal Image Sensors and Its Clinical Screening Test on Patients with Seasonal Influenza

Sensors ◽

10.3390/s20082171 ◽

2020 ◽

Vol 20 (8) ◽

pp. 2171 ◽

Cited By ~ 6

Author(s):

Toshiaki Negishi ◽

Shigeto Abe ◽

Takemi Matsui ◽

He Liu ◽

Masaki Kurosawa ◽

...

Keyword(s):

Heart Rate ◽

Body Temperature ◽

Respiration Rate ◽

Vital Sign ◽

Seasonal Influenza ◽

Estimation Method ◽

Vital Signs ◽

Thermal Image ◽

Image Sensors ◽

Music Algorithm

Background: In the last two decades, infrared thermography (IRT) has been applied in quarantine stations for the screening of patients with suspected infectious disease. However, the fever-based screening procedure employing IRT suffers from low sensitivity, because monitoring body temperature alone is insufficient for detecting infected patients. To overcome the drawbacks of fever-based screening, this study aims to develop and evaluate a multiple vital sign (i.e., body temperature, heart rate and respiration rate) measurement system using RGB-thermal image sensors. Methods: The RGB camera measures blood volume pulse (BVP) through variations in the light absorption from human facial areas. IRT is used to estimate the respiration rate by measuring the change in temperature near the nostrils or mouth accompanying respiration. To enable a stable and reliable system, the following image and signal processing methods were proposed and implemented: (1) an RGB-thermal image fusion approach to achieve highly reliable facial region-of-interest tracking, (2) a heart rate estimation method including a tapered window for reducing noise caused by the face tracker, reconstruction of a BVP signal with three RGB channels to optimize a linear function, thereby improving the signal-to-noise ratio and multiple signal classification (MUSIC) algorithm for estimating the pseudo-spectrum from limited time-domain BVP signals within 15 s and (3) a respiration rate estimation method implementing nasal or oral breathing signal selection based on signal quality index for stable measurement and MUSIC algorithm for rapid measurement. We tested the system on 22 healthy subjects and 28 patients with seasonal influenza, using the support vector machine (SVM) classification method. Results: The body temperature, heart rate and respiration rate measured in a non-contact manner were highly similarity to those measured via contact-type reference devices (i.e., thermometer, ECG and respiration belt), with Pearson correlation coefficients of 0.71, 0.87 and 0.87, respectively. Moreover, the optimized SVM model with three vital signs yielded sensitivity and specificity values of 85.7% and 90.1%, respectively. Conclusion: For contactless vital sign measurement, the system achieved a performance similar to that of the reference devices. The multiple vital sign-based screening achieved higher sensitivity than fever-based screening. Thus, this system represents a promising alternative for further quarantine procedures to prevent the spread of infectious diseases.

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

e-xacta ◽

10.18674/exacta.v9i1.1666 ◽

2016 ◽

Vol 9 (1) ◽

pp. 49 ◽

Cited By ~ 1

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

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.Abstract 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.

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A Comparison of Reflective Photoplethysmography for Detection of Heart Rate, Blood Oxygen Saturation, and Respiration Rate at Various Anatomical Locations

Sensors ◽

10.3390/s19081874 ◽

2019 ◽

Vol 19 (8) ◽

pp. 1874 ◽

Cited By ~ 10

Author(s):

Sally K. Longmore ◽

Gough Y. Lui ◽

Ganesh Naik ◽

Paul P. Breen ◽

Bin Jalaludin ◽

...

Keyword(s):

Heart Rate ◽

Oxygen Saturation ◽

Respiration Rate ◽

Vital Signs ◽

Ground Truth ◽

Human Anatomy ◽

Anatomical Location ◽

Blood Oxygen ◽

Blood Oxygen Saturation ◽

Multiple Sensors

Monitoring of vital signs is critical for patient triage and management. Principal assessments of patient conditions include respiratory rate heart/pulse rate and blood oxygen saturation. However, these assessments are usually carried out with multiple sensors placed in different body locations. The aim of this paper is to identify a single location on the human anatomy whereby a single 1 cm × 1 cm non-invasive sensor could simultaneously measure heart rate (HR), blood oxygen saturation (SpO2), and respiration rate (RR), at rest and while walking. To evaluate the best anatomical location, we analytically compared eight anatomical locations for photoplethysmography (PPG) sensors simultaneously acquired by a single microprocessor at rest and while walking, with a comparison to a commercial pulse oximeter and respiration rate ground truth. Our results show that the forehead produced the most accurate results for HR and SpO2 both at rest and walking, however, it had poor RR results. The finger recorded similar results for HR and SpO2, however, it had more accurate RR results. Overall, we found the finger to be the best location for measurement of all three parameters at rest; however, no site was identified as capable of measuring all parameters while walking.

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An exploratory data quality analysis of time series physiologic signals using a large-scale intensive care unit database

JAMIA Open ◽

10.1093/jamiaopen/ooab057 ◽

2021 ◽

Vol 4 (3) ◽

Author(s):

Ali S Afshar ◽

Yijun Li ◽

Zixu Chen ◽

Yuxuan Chen ◽

Jae Hun Lee ◽

...

Keyword(s):

Blood Pressure ◽

Intensive Care Unit ◽

Heart Rate ◽

Time Series ◽

Intensive Care ◽

Data Quality ◽

Vital Signs ◽

Data Set ◽

Mimic Iii

Abstract Physiological data, such as heart rate and blood pressure, are critical to clinical decision-making in the intensive care unit (ICU). Vital signs data, which are available from electronic health records, can be used to diagnose and predict important clinical outcomes; While there have been some reports on the data quality of nurse-verified vital sign data, little has been reported on the data quality of higher frequency time-series vital signs acquired in ICUs, that would enable such predictive modeling. In this study, we assessed the data quality issues, defined as the completeness, accuracy, and timeliness, of minute-by-minute time series vital signs data within the MIMIC-III data set, captured from 16009 patient-ICU stays and corresponding to 9410 unique adult patients. We measured data quality of four time-series vital signs data streams in the MIMIC-III data set: heart rate (HR), respiratory rate (RR), blood oxygen saturation (SpO2), and arterial blood pressure (ABP). Approximately, 30% of patient-ICU stays did not have at least 1 min of data during the time-frame of the ICU stay for HR, RR, and SpO2. The percentage of patient-ICU stays that did not have at least 1 min of ABP data was ∼56%. We observed ∼80% coverage of the total duration of the ICU stay for HR, RR, and SpO2. Finally, only 12.5%%, 9.9%, 7.5%, and 4.4% of ICU lengths of stay had ≥ 99% data available for HR, RR, SpO2, and ABP, respectively, that would meet the three data quality requirements we looked into in this study. Our findings on data completeness, accuracy, and timeliness have important implications for data scientists and informatics researchers who use time series vital signs data to develop predictive models of ICU outcomes.

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Accurate Heart Rate and Respiration Rate Detection Based on a Higher-Order Harmonics Peak Selection Method Using Radar Non-Contact Sensors

Sensors ◽

10.3390/s22010083 ◽

2021 ◽

Vol 22 (1) ◽

pp. 83

Author(s):

Hongqiang Xu ◽

Malikeh P. Ebrahim ◽

Kareeb Hasan ◽

Fatemeh Heydari ◽

Paul Howley ◽

...

Keyword(s):

Heart Rate ◽

Signal Processing ◽

Respiration Rate ◽

Body Position ◽

Random Noise ◽

Vital Signs ◽

Ultra Wideband ◽

Spectrum Estimation ◽

Respiration Activity ◽

Uwb Radar

Vital signs such as heart rate and respiration rate are among the most important physiological signals for health monitoring and medical applications. Impulse radio (IR) ultra-wideband (UWB) radar becomes one of the essential sensors in non-contact vital signs detection. The heart pulse wave is easily corrupted by noise and respiration activity since the heartbeat signal has less power compared with the breathing signal and its harmonics. In this paper, a signal processing technique for a UWB radar system was developed to detect the heart rate and respiration rate. There are four main stages of signal processing: (1) clutter removal to reduce the static random noise from the environment; (2) independent component analysis (ICA) to do dimension reduction and remove noise; (3) using low-pass and high-pass filters to eliminate the out of band noise; (4) modified covariance method for spectrum estimation. Furthermore, higher harmonics of heart rate were used to estimate heart rate and minimize respiration interference. The experiments in this article contain different scenarios including bed angle, body position, as well as interference from the visitor near the bed and away from the bed. The results were compared with the ECG sensor and respiration belt. The average mean absolute error (MAE) of heart rate results is 1.32 for the proposed algorithm.

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Tingkat Kecemasan dan Stabilitas Tanda Vital pada Pasien Pra Operasi Paska Sensory Motor Body Therapy

Critical Medical and Surgical Nursing Journal ◽

10.20473/cmsnj.v1i1.11974 ◽

2019 ◽

Vol 1 (1) ◽

Author(s):

Cipta Perdana Wijaya ◽

Nursalam Nursalam ◽

Setho Hadisuyatmana

Keyword(s):

Heart Rate ◽

Respiration Rate ◽

Elective Surgery ◽

Vital Signs ◽

T Test ◽

Anxiety Level ◽

Rank Test ◽

Control Group ◽

Sensory Motor ◽

Body Therapy

Introduction:.Anxiety arises from physical, psychological and other pressure of threats. Anxiety may occure in patients who are planned for surgery, from mild untill severe anxiety, that also involving changes in vital signs. One of the techniques used to reduce the anxiety is sensory motor body therapy. Nevertheless, this therapy has not been proven yet reduce an anxiety of elective surgery patients. Therefore, this study was aimed to investigate the effect of sensory motor body therapy on anxiety level and vital sign of pra operation patients.Method:The research was`used a quasy experiment (pre and post with control group). Sample on this study were 26 respondents which divided into 2 groups, the control and treatment group. The independent variable was sensory motor body therapy whereas the dependent variables were blood pressure, heart rate and respiration rate. The data were collected using Zung self-rating anxiety scale (SAS/ SRAS) and vital signs observation and were then tested using Wilcoxon Signed Rank Test, Mann Whitney Test, Paired t-Test and Independent t-Test with significant level of p<0.05.Result:Sensory motor body therapy has been an effect in anxiety level (p=0.001), systole pressure (p=0.020) and respiration rate (p=0.001). But, it has not been an effect in diastole pressure (p=0.316) and heart rate (p=0.481) because of most patients were in the normal boundary.Discussion:Based on the reseach results, we can conclude that sensory motor body therapy in pra operation have a significant role in controling patients anxiety level, systole pressure and respiration rate. For further study, next researcher can improve a new method of sensory motor body therapy on anxiety in pra operation patient.

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Design rationale and performance evaluation of Wavelet Health Wristband: bench-top validation of a wrist-worn physiological signal recorder (Preprint)

10.2196/preprints.11040 ◽

2018 ◽

Author(s):

Onur Dur ◽

Colleen Rhoades ◽

Sally Man Suen Ng ◽

Ragwa Elsayed ◽

Reinier van Mourik ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Respiration Rate ◽

Vital Signs ◽

High Signal ◽

Signal Quality ◽

Absolute Deviation ◽

Physiological Signal ◽

And Performance

BACKGROUND Wearable and connected health devices along with the recent advances in mobile and cloud computing provide a continuous, convenient-to-patient and scalable way to collect personal health data remotely. The Wavelet Health Platform and the Wavelet Wristband have been developed to capture multiple physiological signals and to derive biometrics from these signals including resting heart rate, heart rate variability, and respiration rate. OBJECTIVE This study aims to evaluate the accuracy of the biometrics estimates and signal quality of the wristband. METHODS Measurements collected from 35 subjects using the Wavelet Wristband were compared with simultaneously recorded electrocardiogram and spirometry measurements. RESULTS The heart rate, heart rate variability (SDNN) and respiration rate estimates matched within 0.6 ± 0.9 bpm, 7 ± 10 ms and 1 ± 1 brpm mean absolute deviation of the reference measurements, respectively. The quality of the raw plethysmography signal collected by the wristband, as determined by the harmonic-to-noise ratio, was comparable to that obtained from measurements from a finger-clip plethysmography device. CONCLUSIONS The accuracy of the biometrics estimates and high signal quality indicate that the Wristband PPG device is suitable for performing pulse wave analysis and measuring vital signs.

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Vital Signs Prediction for COVID-19 Patients in ICU

Sensors ◽

10.3390/s21238131 ◽

2021 ◽

Vol 21 (23) ◽

pp. 8131

Author(s):

Ahmed Youssef Ali Amer ◽

Femke Wouters ◽

Julie Vranken ◽

Pauline Dreesen ◽

Dianne de Korte-de Boer ◽

...

Keyword(s):

Heart Rate ◽

Oxygen Saturation ◽

Predictive Model ◽

Respiration Rate ◽

Predictive Models ◽

Vital Sign ◽

Vital Signs ◽

Prediction Performance ◽

Percentage Error ◽

Icu Patients

This study introduces machine learning predictive models to predict the future values of the monitored vital signs of COVID-19 ICU patients. The main vital sign predictors include heart rate, respiration rate, and oxygen saturation. We investigated the performances of the developed predictive models by considering different approaches. The first predictive model was developed by considering the following vital signs: heart rate, blood pressure (systolic, diastolic and mean arterial, pulse pressure), respiration rate, and oxygen saturation. Similar to the first approach, the second model was developed using the same vital signs, but it was trained and tested based on a leave-one-subject-out approach. The third predictive model was developed by considering three vital signs: heart rate (HR), respiration rate (RR), and oxygen saturation (SpO2). The fourth model was a leave-one-subject-out model for the three vital signs. Finally, the fifth predictive model was developed based on the same three vital signs, but with a five-minute observation rate, in contrast with the aforementioned four models, where the observation rate was hourly to bi-hourly. For the five models, the predicted measurements were those of the three upcoming observations (on average, three hours ahead). Based on the obtained results, we observed that by limiting the number of vital sign predictors (i.e., three vital signs), the prediction performance was still acceptable, with the average mean absolute percentage error (MAPE) being 12%,5%, and 21.4% for heart rate, oxygen saturation, and respiration rate, respectively. Moreover, increasing the observation rate could enhance the prediction performance to be, on average, 8%,4.8%, and 17.8% for heart rate, oxygen saturation, and respiration rate, respectively. It is envisioned that such models could be integrated with monitoring systems that could, using a limited number of vital signs, predict the health conditions of COVID-19 ICU patients in real-time.

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