IoT Health Monitoring Device of Oxygen Saturation (SpO2) and Heart Rate Level

2020 ◽  
Author(s):  
O.Y. Tham ◽  
M.A. Markom ◽  
A.H. Abu Bakar ◽  
E.S. Mohd Muslim Tan ◽  
A.M. Markom
Keyword(s):  
Heart Rate ◽  
Oxygen Saturation ◽  
Health Monitoring ◽  
Monitoring Device ◽  
Rate Level ◽  
Heart Rate Level

Factors Affecting Heart Rate Variability in Preterm Infants

PEDIATRICS ◽  
1980 ◽  
Vol 65 (1) ◽  
pp. 50-56 ◽  
Author(s):  
Luis A. Cabal ◽  
Bijan Siassi ◽  
Bernardino Zanini ◽  
Joan E. Hodgman ◽  
Edward E. Hon
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Birth Weight ◽  
Preterm Infants ◽  
Gestational Age ◽  
Distress Syndrome ◽  
Good Prognosis ◽  
Factors Affecting ◽  
Rate Level ◽  
Heart Rate Level

Neonatal heart rate variability (NHRV) was studied in 92 preterm infants (birth weight, 750 to 2,500 gm; gestational age, 28 to 36 weeks). Each infant was monitored continuously during the first 6 hours and for one hour at 24, 48, and 168 hours of life. During each hour NHRV was quantified and related to the following parameters: sex, gestational age, postnatal age, heart rate, and the presence and severity of respiratory distress syndrome (RDS). NHRV in healthy preterm infants was inversely related to heart rate level and directly related to the infant's postnatal age. In healthy babies with gestations of 30 to 36 weeks there was no significant correlation between NHRV and gestation. Decrease in NHRV was significantly related to the severity of RDS, and the reappearance of NHRV in infants with RDS was associated with a good prognosis. Decreased NHRV significantly differentiated the infants with RDS who survived after the fifth hour of life. The data reveal that NHRV (1) should be corrected for heart rate level and postnatal age; (2) is decreased in RDS; and (3) can be used as an indicator of morbidity and mortality in preterm infants with RDS.

scholarly journals Mean Heart Rate Level Does Not Affect All Heart Rate Variability Indices

Hypertension ◽  
2017 ◽  
Vol 69 (5) ◽  
Author(s):  
Luiz Eduardo Virgilio Silva ◽  
Helio Cesar Salgado ◽  
Rubens Fazan
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Rate Level ◽  
Heart Rate Level ◽  
Mean Heart Rate

Short-Latency Acceleration of Human Heart Rate as a Function of Stimulus Intensity

1977 ◽  
Vol 45 (2) ◽  
pp. 579-583 ◽  
Author(s):  
J. G. O'Gorman ◽  
R. D. Jamieson
Keyword(s):  
Heart Rate ◽  
White Noise ◽  
Stimulus Intensity ◽  
Human Heart ◽  
Short Latency ◽  
Rate Level ◽  
Initial Values ◽  
Heart Rate Level ◽  
The Mean ◽  
Female Subjects

The study examined the effectiveness of three intensities of white noise in evoking short-latency acceleration of human heart rate. 3 groups of 10 female subjects were presented with 1-sec. bursts of white noise with virtually instantaneous rise times at intensities of 100 db (re 20 μN/m2), 90 db, or 80 db SPL as measured at the headset. 5 bursts were presented at intervals of 45 sec. while the EKG was recorded. An increase in heart rate during poststimulus beats 3 and 4 compared with the mean rate of the three beats prestimulus was reliably evoked on the first two trials in the 100-db and 90-db groups but not in the 80-db group. Apart from a recovery of acceleration on Trial 5 for the 100-db group, the 100-db and 90-db groups did not differ in amplitude or rate of habituation of the response. Poststimulus heart-rate level was not significantly related to prestimulus level as expected in terms of the law of initial values. The results were interpreted as consistent with F. K. Graham's interpretation of short-latency cardiac acceleration as a component of startle.

Effects of triazolam on heart rate level and on phasic cardiac response to noise during sleep

1988 ◽  
Vol 96 (2) ◽  
pp. 188-193 ◽  
Author(s):  
J. P. Libert ◽  
C. Amoros ◽  
A. Muzet ◽  
J. Ehrhart ◽  
J. Di Nisi
Keyword(s):  
Heart Rate ◽  
Cardiac Response ◽  
Rate Level ◽  
Heart Rate Level

scholarly journals Fitness-Tracker Assisted Frailty-Assessment Before Transcatheter Aortic Valve Implantation: Proof-of-Concept Study

10.2196/19227 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e19227
Author(s):  
Markus Mach ◽  
Victoria Watzal ◽  
Waseem Hasan ◽  
Martin Andreas ◽  
Bernhard Winkler ◽  
...  
Keyword(s):  
Heart Rate ◽  
Aortic Valve ◽  
Hospital Mortality ◽  
Health Monitoring ◽  
Monitoring Device ◽  
Proof Of Concept ◽  
Concept Study ◽  
Transcatheter Aortic Valve ◽  
Frailty Assessment ◽  
Fitness Tracker

Background While transcatheter aortic valve replacement (TAVR) has revolutionized the treatment of aortic valve stenosis, wearable health-monitoring devices are gradually transforming digital patient care. Objective The aim of this study was to develop a simple, efficient, and economical method for preprocedural frailty assessment based on parameters measured by a wearable health-monitoring device. Methods In this prospective study, we analyzed data of 50 consecutive patients with mean (SD) age of 77.5 (5.1) years and a median (IQR) European system for cardiac operative risk evaluation (EuroSCORE) II of 3.3 (4.1) undergoing either transfemoral or transapical TAVR between 2017 and 2018. Every patient was fitted with a wrist-worn health-monitoring device (Garmin Vivosmart 3) for 1 week prior to the procedure. Twenty different parameters were measured, and threshold levels for the 3 most predictive categories (ie, step count, heart rate, and preprocedural stress) were calculated. Patients were assigned 1 point per category for exceeding the cut-off value and were then classified into 4 stages (no, borderline, moderate, and severe frailty). Furthermore, the FItness-tracker assisted Frailty-Assessment Score (FIFA score) was compared with the scores of the preprocedural gait speed category derived from the 6-minute walk test (GSC-6MWT) and the Edmonton Frail Scale classification (EFS-C). The primary study endpoint was hospital mortality. Results The overall preprocedural stress level (P=.02), minutes of high stress per day (P=.02), minutes of rest per day (P=.045), and daily heart rate maximum (P=.048) as single parameters were the strongest predictors of hospital mortality. When comparing the different frailty scores, the FIFA score demonstrated the greatest predictive power for hospital mortality (FIFA area under the curve [AUC] 0.844, CI 0.656-1.000; P=.048; GSC-6MWT AUC 0.671, CI 0.487-0.855; P=.42; EFS-C AUC 0.636, CI 0.254-1.000; P=.44). Conclusions This proof-of-concept study demonstrates the strong predictive performance of the FIFA score compared to that of the conventional frailty assessments.

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