scholarly journals Evaluation of a technique to measure heart rate variability in anaesthetised cats

2014 ◽  
Vol 199 (2) ◽  
pp. 229-235 ◽  
Author(s):  
Kuan Hua Khor ◽  
Ian A. Shiels ◽  
Fiona E. Campbell ◽  
Ristan M. Greer ◽  
Annie Rose ◽  
...  
Biofeedback ◽  
2016 ◽  
Vol 44 (4) ◽  
pp. 229-233 ◽  
Author(s):  
Fredric Shaffer ◽  
Steven Shearman ◽  
Zachary M. Meehan

Researchers have investigated whether ultra-short-term (UST) heart rate variability values can replace traditional 5-minute values in clinical and optimal performance settings. Concurrent validity is the extent to which the results of a measurement correspond to a previously validated assessment of the same construct. Several studies either failed to specify their concurrent validity criteria or used an inappropriate statistical test. The authors proposed a rigorous standard and demonstrated that artifacted resting ultra-short-term heart rate variability values can achieve strong concurrent validity for diverse time-domain, frequency-domain, and nonlinear measurements in healthy undergraduates. Based on these findings, resting baselines as brief as 1 minute should be sufficient to measure heart rate, the standard deviation of the interbeat interval for normal beats (SDNN), and the square root of the mean squared difference of adjacent NN intervals (RMSSD) in clinical, optimal performance, and personal health assessment with individuals who resemble Truman State University undergraduates.


2021 ◽  
Author(s):  
Minjung Kim ◽  
Jungsook Kim ◽  
Kyounghyun Park ◽  
HyunSuk Kim ◽  
Daesub Yoon

2020 ◽  
Vol 44 (11) ◽  
Author(s):  
Angela A. T. Schuurmans ◽  
Peter de Looff ◽  
Karin S. Nijhof ◽  
Catarina Rosada ◽  
Ron H. J. Scholte ◽  
...  

Abstract Wearable monitoring devices are an innovative way to measure heart rate (HR) and heart rate variability (HRV), however, there is still debate about the validity of these wearables. This study aimed to validate the accuracy and predictive value of the Empatica E4 wristband against the VU University Ambulatory Monitoring System (VU-AMS) in a clinical population of traumatized adolescents in residential care. A sample of 345 recordings of both the Empatica E4 wristband and the VU-AMS was derived from a feasibility study that included fifteen participants. They wore both devices during two experimental testing and twelve intervention sessions. We used correlations, cross-correlations, Mann-Whitney tests, difference factors, Bland-Altman plots, and Limits of Agreement to evaluate differences in outcomes between devices. Significant correlations were found between Empatica E4 and VU-AMS recordings for HR, SDNN, RMSSD, and HF recordings. There was a significant difference between the devices for all parameters but HR, although effect sizes were small for SDNN, LF, and HF. For all parameters but RMSSD, testing outcomes of the two devices led to the same conclusions regarding significance. The Empatica E4 wristband provides a new opportunity to measure HRV in an unobtrusive way. Results of this study indicate the potential of the Empatica E4 as a practical and valid tool for research on HR and HRV under non-movement conditions. While more research needs to be conducted, this study could be considered as a first step to support the use of HRV recordings provided by wearables.


Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 137
Author(s):  
Olli-Pekka Nuuttila ◽  
Elisa Korhonen ◽  
Jari Laukkanen ◽  
Heikki Kyröläinen

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11340 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (bias −0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (bias 0.20 ms, p < 0.001) and nocturnal recordings (bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.


2017 ◽  
Vol 15 (2) ◽  
pp. 141-147 ◽  
Author(s):  
Julia Silva-e-Oliveira ◽  
Pâmela Marina Amélio ◽  
Isabela Lopes Laguardia Abranches ◽  
Dênis Derly Damasceno ◽  
Fabianne Furtado

ABSTRACT Objective To evaluate heart rate variability among adults with different risk levels for type 2 diabetes mellitus. Methods The risk for type 2 diabetes mellitus was assessed in 130 participants (89 females) based on the questionnaire Finnish Diabetes Risk Score and was classified as low risk (n=26), slightly elevated risk (n=41), moderate risk (n=27) and high risk (n=32). To measure heart rate variability, a heart-rate monitor Polar S810i® was employed to obtain RR series for each individual, at rest, for 5 minutes, followed by analysis of linear and nonlinear indexes. Results The groups at higher risk of type 2 diabetes mellitus had significantly lower linear and nonlinear heart rate variability indexes. Conclusion The individuals at high risk for type 2 diabetes mellitus have lower heart rate variability.


Author(s):  
Kelvin K.F. Tsoi ◽  
Janet Y.H. Wong ◽  
Michael P.F. Wong ◽  
Gary K.S. Leung ◽  
Baker K.K. Bat ◽  
...  

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