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

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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Continuous In-Bed Monitoring of Vital Signs Using a Multi Radar Setup for Freely Moving Patients

Sensors ◽

10.3390/s20205827 ◽

2020 ◽

Vol 20 (20) ◽

pp. 5827 ◽

Cited By ~ 1

Author(s):

Sven Schellenberger ◽

Kilin Shi ◽

Fabian Michler ◽

Fabian Lurz ◽

Robert Weigel ◽

...

Keyword(s):

Early Warning ◽

Gold Standard ◽

Continuous Monitoring ◽

Vital Signs ◽

Radar Data ◽

Radar System ◽

Freedom Of Movement ◽

Freely Moving ◽

The Individual ◽

Vital Parameters

In hospitals, continuous monitoring of vital parameters can provide valuable information about the course of a patient’s illness and allows early warning of emergencies. To enable such monitoring without restricting the patient’s freedom of movement and comfort, a radar system is attached under the mattress which consists of four individual radar modules to cover the entire width of the bed. Using radar, heartbeat and respiration can be measured without contact and through clothing. By processing the raw radar data, the presence of a patient can be determined and movements are categorized into the classes “bed exit”, “bed entry”, and “on bed movement”. Using this information, the vital parameters can be assessed in sections where the patient lies calmly in bed. In the first step, the presence and movement classification is demonstrated using recorded training and test data. Next, the radar was modified to perform vital sign measurements synchronized to a gold standard device. The evaluation of the individual radar modules shows that, regardless of the lying position of the test person, at least one of the radar modules delivers accurate results for continuous monitoring.

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

American Journal of Perinatology ◽

10.1055/s-0040-1718877 ◽

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

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

Journal of the American Association for Laboratory Animal Science ◽

10.30802/aalas-jaalas-19-000052 ◽

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.

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Validation of heart rate extracted from wrist-based photoplethysmography (PPG) in the perioperative setting: a prospective observational study. (Preprint)

10.2196/preprints.27765 ◽

2021 ◽

Author(s):

Eveline Mestrom ◽

Ruben Deneer ◽

Alberto G Bonomi ◽

Jenny Margarito ◽

Jos Gelissen ◽

...

Keyword(s):

Heart Rate ◽

Recovery Period ◽

Patient Deterioration ◽

Patient Monitor ◽

Quality Signals ◽

Standard Patient ◽

Golden Standard ◽

The Difference ◽

Electrocardiogram Ecg ◽

Difference Test

BACKGROUND Measurement of heartrate (HR) through an unobtrusive, wrist-worn optical HR monitor (OHRM) in the form of a wristband could enable earlier recognition of patient deterioration and timely intervention. OBJECTIVE The goal of this study is to assess the agreement between HR extracted from an OHRM and the golden standard patient monitor during surgery and in the recovery period. METHODS The agreement in beats per minute (bpm) was evaluated between the gold standard electrocardiogram (ECG) from the patient monitor and the HR extracted from the photoplethysmography (PPG) sensor by the OHRM. RESULTS A total of 271.8 hours of data in 99 patients was recorded simultaneously by the OHRM and patient monitor. Median coverage was 86% (interquartile range: 65% to 95%) and did not differ significantly between surgery and recovery (Wilcoxon paired difference test P .17). Agreement analysis showed the limits of agreement (LoA) of the difference between the OHRM and the ECG HR were within the range ± 5 bpm. The mean bias was -0.14 bpm (LoA between -3.08 and 2.79) and -0.19 % (LoA between -4.79 and 4.39) for the PPG measured HR compared to the ECG measured HR during surgery and -0.11 bpm (LoA between -2.79 and 2.59) and -0.15 % (LoA between -3.92 and 3.64) during recovery. CONCLUSIONS An OHRM can obtain good quality signals for HR in the majority of the patients for most of the time in the perioperative setting. OHRM HR monitoring is within the acceptable range compared to ECG derived heartrate, which implies that an OHRM can be considered clinically acceptable for heart rate monitoring in low acuity hospitalized patients. CLINICALTRIAL This non-randomized trial was not registered in a trial registration.

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

Sensors ◽

10.3390/s20226593 ◽

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.

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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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FPGA Based Health Monitoring System

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.e4952.018520 ◽

2020 ◽

Vol 8 (5) ◽

pp. 5573-5575

Keyword(s):

Heart Rate ◽

Body Temperature ◽

Monitoring System ◽

Health Monitoring ◽

Wearable Sensors ◽

Vital Signs ◽

The Body ◽

Health Report ◽

Reduced Physical Activity ◽

Healthcare Monitoring

In present days, Health issues are occurring more frequently. Because of climatic changes, industrialization and technical advancement which led to reduced physical activity. Saving lives requires monitoring the health conditions of people who have chronic diseases or heart related problems. Decrease in morbidity from disease and extend lives can be achieved by earlier detection of problems. When we reach a certain age we have to keep monitoring the three vital signs of the body to extend our lives. In this paper, we are designing a healthcare monitoring system which can either monitor or measure three vital signs i.e. heart rate, respiratory rate and body temperature of human body. The developed system uses wearable sensors to measure body temperature, heart rate and breathing rate. In order to minimize human involvement and respond at an appropriate time a health monitoring designed FGPA system will take the data from the sensors and analyze the date. It will give the health report, health status and alerts the concerned whenrequired.

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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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