Fast Acquisition of Heart Rate in Noncontact Vital Sign Radar Measurement Using Time-Window-Variation Technique

2016 ◽  
Vol 65 (1) ◽  
pp. 112-122 ◽  
Author(s):  
Jianxuan Tu ◽  
Jenshan Lin
Keyword(s):  
Heart Rate ◽  
Vital Sign ◽  
Time Window ◽  
Radar Measurement ◽  
Fast Acquisition ◽  
Variation Technique

scholarly journals Accuracy of real-time delivery room resuscitation documentation

2018 ◽  
Vol 105 (2) ◽  
pp. 222-224 ◽  
Author(s):  
Claire E Fishman ◽  
Danielle D Weinberg ◽  
Ashley Murray ◽  
Elizabeth E Foglia
Keyword(s):  
Heart Rate ◽  
Oxygen Saturation ◽  
Real Time ◽  
Vital Sign ◽  
Gold Standard ◽  
Neonatal Intensive Care ◽  
Video Recording ◽  
Neonatal Resuscitation ◽  
Delivery Room ◽  
Level 3

ObjectiveTo assess the accuracy of real-time delivery room resuscitation documentation.DesignRetrospective observational study.SettingLevel 3 academic neonatal intensive care unit.ParticipantsFifty infants with video recording of neonatal resuscitation.Main outcome measuresVital sign assessments and interventions performed during resuscitation. The accuracy of written documentation was compared with video gold standard.ResultsTiming of initial heart rate assessment agreed with video in 44/50 (88%) records; the documented heart rate was correct in 34/44 (77%) of these. Heart rate and oxygen saturation were documented at 5 min of life in 90% of resuscitations. Of these, 100% of heart rate and 93% of oxygen saturation values were correctly recorded. Written records accurately reflected the mode(s) of respiratory support for 89%–100%, procedures for 91%–100% and medications for 100% of events.ConclusionReal-time documentation correctly reflects interventions performed during delivery room resuscitation but is less accurate for early vital sign assessments.

scholarly journals A Novel Real-Time Human Heart Rate Estimation Method for Noncontact Vital Sign Radar Detection

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 88689-88699
Author(s):  
Yipeng Ding ◽  
Xiali Yu ◽  
Chengxi Lei ◽  
Yinhua Sun ◽  
Xuemei Xu ◽  
...  
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Vital Sign ◽  
Human Heart ◽  
Estimation Method ◽  
Radar Detection ◽  
Rate Estimation ◽  
Heart Rate Estimation

scholarly journals Internet of things–based vital sign monitoring system

2020 ◽  
Vol 10 (6) ◽  
pp. 5891
Author(s):  
Alamsyah Alamsyah ◽  
Mery Subito ◽  
Mohammad Ikhlayel ◽  
Eko Setijadi
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Body Temperature ◽  
Internet Of Things ◽  
Monitoring System ◽  
Vital Sign ◽  
Data Retrieval ◽  
Medical Personnel ◽  
Raspberry Pi ◽  
Medical Diagnoses

Wireless network technology-based internet of things (IoT) has increased significantly and exciting to study, especially vital sign monitoring (body temperature, heart rate, and blood pressure). Vital sign monitoring is crucial to carry out to strengthen medical diagnoses and the continuity of patient health. Vital sign monitoring conducted by medical personnel to diagnose the patient's health condition is still manual. Medical staff must visit patients in each room, and the equipment used is still cable-based. Vital sign examination like this is certainly not practical because it requires a long time in the process of diagnosis. The proposed vital sign monitoring system design aims to assist medical personnel in diagnosing the patient's illness. Vital sign monitoring system uses HRM-2511E sensor for heart detection, DS18b20 sensor for body temperature detection, and MPX5050DP sensor for blood pressure detection. Vital sign data processing uses a raspberry pi as a data delivery media-based internet of things (IoT). Based on the results of the vital sign data retrieval shows that the tool designed functioning correctly. The accuracy of the proposed device for body temperature is 99.51%, heart rate is 97.90%, and blood pressure is 97.69%.

scholarly journals The Association of Extreme Tachycardia and Sustained Return of Spontaneous Circulation after Nontraumatic Out-of-Hospital Cardiac Arrest

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Dong Keon Lee ◽  
Eugi Jung ◽  
You Hwan Jo ◽  
Joonghee Kim ◽  
Jae Hyuk Lee ◽  
...  
Keyword(s):  
Heart Rate ◽  
Logistic Regression ◽  
Cardiac Arrest ◽  
Regression Model ◽  
Vital Sign ◽  
High Probability ◽  
Logistic Regression Model ◽  
Spontaneous Circulation ◽  
Return Of Spontaneous Circulation ◽  
Hospital Cardiac Arrest

Objective. Heart rate (HR), an essential vital sign that reflects hemodynamic stability, is influenced by myocardial oxygen demand, coronary blood flow, and myocardial performance. HR at the time of the return of spontaneous circulation (ROSC) could be influenced by the β1-adrenergic effect of the epinephrine administered during cardiopulmonary resuscitation (CPR), and its effect could be decreased in patients who have the failing heart. We aimed to investigate the association between HR at the time of ROSC and the outcomes of adult out-of-hospital cardiac arrest (OHCA) patients. Methods. This study was a secondary analysis of a cardiac arrest registry from a single institution from January 2008 to July 2014. The OHCA patients who achieved ROSC at the emergency department (ED) were included, and HR was retrieved from an electrocardiogram or vital sign at the time of ROSC. The patients were categorized into four groups according to the HR (bradycardia (HR < 60), normal HR (60 ≤ HR ≤ 100), tachycardia (100 < HR < 150), and extreme tachycardia (HR ≥ 150)). The primary outcome was the rate of sustained ROSC and the secondary outcomes were the rate of one-month survival and six-month good neurologic outcome. Results. A total of 330 patients were included. In the univariate logistic regression model, the rate of sustained ROSC increased by 17% as HR increased by every 10 beats per minute (bpm) (odds ratio (OR), 1.171; 95% confidence interval (CI), 1.077–1.274, p<0.001). In the multivariate logistic regression model, extreme tachycardia was independently associated with a high probability of sustained ROSC compared to normal heart rate (OR, 15.96; 95% CI, 2.04–124.93, p=0.008). Conclusion. Extreme tachycardia (HR ≥ 150) at the time of ROSC is independently associated with a high probability of sustained ROSC in nontraumatic adult OHCA patients.

scholarly journals Validation of a wearable biosensor device for vital sign monitoring in septic emergency department patients in Rwanda

2019 ◽  
Vol 5 ◽  
pp. 205520761987934
Author(s):  
Stephanie C Garbern ◽  
Gabin Mbanjumucyo ◽  
Christian Umuhoza ◽  
Vinay K Sharma ◽  
James Mackey ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Vital Sign ◽  
Vital Signs ◽  
University Teaching ◽  
Suspected Sepsis ◽  
Middle Income ◽  
Radiologic Study ◽  
Emergency Department Patients ◽  
Biosensor Device

Objective Critical care capabilities needed for the management of septic patients, such as continuous vital sign monitoring, are largely unavailable in most emergency departments (EDs) in low- and middle-income country (LMIC) settings. This study aimed to assess the feasibility and accuracy of using a wireless wearable biosensor device for continuous vital sign monitoring in ED patients with suspected sepsis in an LMIC setting. Methods This was a prospective observational study of pediatric (≥2 mon) and adult patients with suspected sepsis at the Kigali University Teaching Hospital ED. Heart rate, respiratory rate and temperature measurements were continuously recorded using a wearable biosensor device for the duration of the patients’ ED course and compared to intermittent manually collected vital signs. Results A total of 42 patients had sufficient data for analysis. Mean duration of monitoring was 32.8 h per patient. Biosensor measurements were strongly correlated with manual measurements for heart rate (r = 0.87, p <  0.001) and respiratory rate (r = 0.75, p <  0.001), although were less strong for temperature (r = 0.61, p <  0.001). Mean (SD) differences between biosensor and manual measurements were 1.2 (11.4) beats/min, 2.5 (5.5) breaths/min and 1.4 (1.0)°C. Technical or practical feasibility issues occurred in 12 patients (28.6%) although were minor and included biosensor detachment, connectivity problems, removal for a radiologic study or exam, and patient/parent desire to remove the device. Conclusions Wearable biosensor devices can be feasibly implemented and provide accurate continuous heart rate and respiratory rate monitoring in acutely ill pediatric and adult ED patients with sepsis in an LMIC setting.

scholarly journals Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6505
Author(s):  
Emmi Turppa ◽  
Juha M. Kortelainen ◽  
Oleg Antropov ◽  
Tero Kiuru
Keyword(s):  
Heart Rate ◽  
Remote Monitoring ◽  
Vital Sign ◽  
Continuous Wave ◽  
Real Life ◽  
Vital Signs ◽  
Absolute Error ◽  
Physical Contact ◽  
Radar Signal ◽  
Fmcw Radar

Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of 3.6% (86% correlation) and 9.1% (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.

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