scholarly journals Heart Rate monitor based on IP networking

2018 ◽  
Vol 210 ◽  
pp. 01006
Author(s):  
Miguel G. Molina ◽  
Priscila E. Garzón ◽  
Carolina J. Molina ◽  
Juan X. Nicola
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Electronic Devices ◽  
Vital Signs ◽  
Well Being ◽  
Heart Rate Monitor ◽  
Ip Address ◽  
Health Concept ◽  
New Applications ◽  
Threat Situation

With the uprising of Internet of Things (IoT) networks, new applications have taken advantage of this new concept. Having all devices and all people connected 24/7 have several advantages in a variated amount of disciplines. One of them is medicine and the e-health concept. The possibility of having a real time lecture of the vital signs of people can prevent a live threat situation. This paper describes the realization of a device capable of measuring the heart rate of a person and checking for abnormalities that may negatively affect the patient’s well-being. This project will make use of electronic devices known as microcontrollers, specifically from the Arduino family, enabling us to capture data, and, with the help of a network card and a RJ-45 cable, transfer it to a PC and visualize the heart rate in real time over its assigned IP address.

scholarly journals Non-intrusive vital sign monitoring using an intelligent pillow based on a piezoelectric ceramic sensor

2020 ◽  
Vol 15 ◽  
pp. 155892502097726
Author(s):  
Wei Wang ◽  
Zhiqiang Pang ◽  
Ling Peng ◽  
Fei Hu
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Piezoelectric Ceramic ◽  
Low Cost ◽  
Body Movement ◽  
Vital Signs ◽  
High Heart Rate ◽  
Detection Accuracy ◽  
Processing Unit ◽  
Real Time Monitoring

Performing real-time monitoring for human vital signs during sleep at home is of vital importance to achieve timely detection and rescue. However, the existing smart equipment for monitoring human vital signs suffers the drawbacks of high complexity, high cost, and intrusiveness, or low accuracy. Thus, it is of great need to develop a simplified, nonintrusive, comfortable and low cost real-time monitoring system during sleep. In this study, a novel intelligent pillow was developed based on a low-cost piezoelectric ceramic sensor. It was manufactured by locating a smart system (consisting of a sensing unit i.e. a piezoelectric ceramic sensor, a data processing unit and a GPRS communication module) in the cavity of the pillow made of shape memory foam. The sampling frequency of the intelligent pillow was set at 1000 Hz to capture the signals more accurately, and vital signs including heart rate, respiratory rate and body movement were derived through series of well established algorithms, which were sent to the user’s app. Validation experimental results demonstrate that high heart-rate detection accuracy (i.e. 99.18%) was achieved in using the intelligent pillow. Besides, human tests were conducted by detecting vital signs of six elder participants at their home, and results showed that the detected vital signs may well predicate their health conditions. In addition, no contact discomfort was reported by the participants. With further studies in terms of validity of the intelligent pillow and large-scale human trials, the proposed intelligent pillow was expected to play an important role in daily sleep monitoring.

scholarly journals Developing An Improved Heart Rate Monitor With Work-Out Training Android Application And Real Time Audio Coaching

2018 ◽  
Author(s):  
Perlie John Dy ◽  
◽  
Terence Joy Lareche ◽  
Dave Daniel Coles ◽  
Meljohn Aborde
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Android Application ◽  
Heart Rate Monitor

scholarly journals VitaFALL: NXTGeUH System for Well-Being Monitoring with Fall Recognition and Real-Time Vital Sign Monitoring

2020 ◽  
Vol 8 (5) ◽  
pp. 5139-5145
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Vital Signs ◽  
Initial Step ◽  
Fall Detection ◽  
Well Being ◽  
Motion Data ◽  
Detection Model ◽  
Vital Signs Monitoring ◽  
Research Problems

The blend of computerized data processing with the existing engineering and medic techniques has enabled explorers in the betterment of controlling of patients concerning the two at homes along with at clinics. In this work, numerous fall assessment for fall prediction and detection with vital signs monitoring techniques and methods particularly to establish a research gap and its allied research problems has been reviewed and incorporated using a triple-axis accelerometer and Vital Signs Parameters (Heartrate, Heartbeat, and Temperature monitoring) for the ancient people with a Internet of Medical Things based Vital Signs and Fall Detection (VitaFALL) is proposed which is well-timed and gives an effective judgment of the fall. The four layers comprise sensing, network, data processing and application layer. A caretaker and doctor can be notified by sending alert using a GSM and GPRS module in order that elder can be helped on time, however, a delay in the time is noticed when comparing the gradient and minimum value to predetermine the state of the old person. From a few decades, vital signs have been important parameters to find out the patient’s health level. Vital signs estimation has always been the initial step for the evaluation of the patient and this is also possible by checking the pulse rate or checking the palpation of their forehead for high temperature. ADXL335 Three-Axis Accelerometer Module, tri-axial 14-bit ± 8g accelerometer collects motion information in the VitaFall device. The basic idea is to avoid falls and not to detect them after the loss is done. Walking, stumbling, sitting, falling (right, forward, backward and left) and all other normal motion data patters in the daily life of an older adult (who did no longer have any records or walking issues) are collected. The proposed VitaFall Fall detection model has achieved 85% accuracy, specificity of 100%, and sensitivity of 96% when detecting directional falls. The model uses motion data, real-time vital signs values, falls history to foresee the lows, medians and the highs of falls risks in hospitalized elderly people. When compared with the manual falls risk tools known as the Morse Falls scale, the system got an accuracy of 85%, predictability of 100%, and a sensitivity of 100% too.

Remote Monitoring of Patients with Hematologic Malignancies at High-Risk of Febrile Neutropenia (Preprint)

2021 ◽  
Author(s):  
Maxwell Jared Kroloff ◽  
Ramin Ramezani ◽  
Holly Wilhalme ◽  
Arash Naeim
Keyword(s):  
Heart Rate ◽  
High Risk ◽  
Febrile Neutropenia ◽  
Oxygen Saturation ◽  
Real Time ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Vital Signs ◽  
Hematologic Malignancies ◽  
Remote Monitoring System

BACKGROUND Febrile neutropenia represents one of the most common oncologic emergencies and is associated with significant, preventable morbidity and mortality. The vast majority of patients suffering a febrile neutropenia episode are hospitalized, resulting in significant economic cost. OBJECTIVE This exploratory study implemented a remote monitoring platform including a digital infrared thermometer and a pulse oximeter with the capability to notify providers in real-time of vital signs abnormalities that could suggest early clinical deterioration, and thereby improve upon clinical outcomes. METHODS The remote monitoring system was implemented versus standard of care vital signs monitoring in hospitalized patients with underlying hematologic malignancies complicated by a febrile neutropenia episode in order to assess both feasibility and validity of the system. RESULTS Intraclass correlation coefficient analysis (ICC), confirmed the high repeatability and accuracy of heart rate assessment (ICC= 0.856), acting as a supplement to sole, remote temperature assessment. While the sensitivity and specificity for capturing tachycardia above a rate of 100 was excellent (88% and 97% respectively), the sensitivity of the remote monitoring system capturing temperature greater than 100 degrees Fahrenheit and oxygen saturation less than 92% was 45% and 50% respectively. CONCLUSIONS Overall, this novel approach including temperature, heart rate and oxygen saturation assessment successfully provides real-time, clinically valuable feedback to providers. While the temperature and oxygen saturation lags in terms of sensitivity when compared to a standard in-hospital system, the heart rate data helps overcome some of this deficit, and as a whole, the system provides additional information that can be applied to a clinically vulnerable population. By transitioning its application to the high-risk patients in the outpatient setting, the novel system can help prevent additional healthcare utilization through early provider intervention and potentially improve outcomes.

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.

scholarly journals Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network

2021 ◽  
pp. bjsports-2020-103148
Author(s):  
Jan M Mühlen ◽  
Julie Stang ◽  
Esben Lykke Skovgaard ◽  
Pedro B Judice ◽  
Pablo Molina-Garcia ◽  
...  
Keyword(s):  
Heart Rate ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Best Practice ◽  
Healthcare Providers ◽  
Vital Signs ◽  
Well Being ◽  
Wearable Devices ◽  
Full Potential ◽  
Expert Opinions

Assessing vital signs such as heart rate (HR) by wearable devices in a lifestyle-related environment provides widespread opportunities for public health related research and applications. Commonly, consumer wearable devices assessing HR are based on photoplethysmography (PPG), where HR is determined by absorption and reflection of emitted light by the blood. However, methodological differences and shortcomings in the validation process hamper the comparability of the validity of various wearable devices assessing HR. Towards Intelligent Health and Well-Being: Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives towards developing best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice validation protocol for consumer wearables assessing HR by PPG. The recommendations were developed through the following multi-stage process: (1) a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, (2) an unstructured review of the wider literature pertaining to factors that may introduce bias during the validation of these devices and (3) evidence-informed expert opinions of the INTERLIVE Network. A total of 44 articles were deemed eligible and retrieved through our systematic literature review. Based on these studies, a wider literature review and our evidence-informed expert opinions, we propose a validation framework with standardised recommendations using six domains: considerations for the target population, criterion measure, index measure, testing conditions, data processing and the statistical analysis. As such, this paper presents recommendations to standardise the validity testing and reporting of PPG-based HR wearables used by consumers. Moreover, checklists are provided to guide the validation protocol development and reporting. This will ensure that manufacturers, consumers, healthcare providers and researchers use wearables safely and to its full potential.

scholarly journals An IoMT system for health monitoring in athletes

2020 ◽  
pp. 62
Author(s):  
Eduardo García Michel ◽  
Pedro C Santana-Mancilla ◽  
Silvia B Fajardo-Flores ◽  
Laura S Gaytan-Lugo ◽  
Víctor H Pérez Andrade ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Heart Rate ◽  
Real Time ◽  
Health Monitoring ◽  
Mobile Application ◽  
Vital Signs ◽  
Personal Control ◽  
Breathing Patterns ◽  
Medical Prescription

Continuous health monitoring in real-time has become essential to improve people's quality of life through medical prescription or personal control. Our goal is to develop a wearable IoMT device with real-time monitoring of heart rate and breathing patterns while an athlete performs physical exercise at high-intensity intervals. The wearable IoMT device incorporates vital signs sensors to record and display information in a mobile application, allowing users to track their health and receive an alert if the data exceeds normal parameters.

Sign in / Sign up

Export Citation Format

Share Document