Classic electrocardiogram-based and mobile technology derived approaches to heart rate variability are not equivalent

Guzik, Przemysław; Piekos, Caroline; Pierog, O.; Fenech, N.; Krauze, Tomasz; Piskorski, Jarosław; Wykrętowicz, Andrzej

doi:10.1016/j.ijcard.2018.01.056

Cited by 16 publications

(24 citation statements)

References 19 publications

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“…It is important to note that there are nuances and complexities when collecting and analyzing HRV data. For example, ECG data is required as pulse and heart rate monitors are not able to determine if all beats are of a sinus origin [2,20] and how ectopic beats are dealt with [32]. The reader is advised to review the literature for a better understanding of HRV [43].…”

Section: Measures and Physiological Assessment Equipmentmentioning

confidence: 99%

“…General cerebral metabolism can be monitored using non-invasive equipment, such as near-infrared spectroscopy (NIRS) [21], to measure cerebral oxygenation, while beat-to-beat blood pressure can be measured using photoplethysmography [2,5,30], cerebral blood flow velocity can be determined with a transcranial Doppler [22,31], and heart rate can be measured with an electrocardiogram (ECG) to record electrical and temporal cardiac dynamics. HRV analysis is best done using software programs that can deconstruct and measure each component of the raw ECG waveform [32]. Furthermore, there are several simple tasks that can evoke a response specific to a certain subsection of physiology, such as “Where’s Waldo” [33], which can allow for neurovascular coupling measurements, head postural changes and breath holds, providing insight to cerebrovascular autoregulation [22,31], controlled breathing protocols which can show HRV changes [34], and squat-stand holds which can provide a baroreflex measure and autoregulatory control [2,35].…”

Section: Introductionmentioning

confidence: 99%

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An Evidence-Based Objective Study Protocol for Evaluating Cardiovascular and Cerebrovascular Indices Following Concussion: The Neary Protocol

Neary

Singh

Bishop

et al. 2019

MPs

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Introduction: The prevalence and incidence of sport-related concussion have continued to increase over the past decade, and researchers from various backgrounds strive for evidenced-based clinical assessment and management. When diagnosing and managing a concussion, a battery of tests from several domains (e.g., symptom reporting, neurocognitive, physiology) must be used. In this study, we propose and develop an objective, evidence-based protocol to assess the pathophysiology of the brain by using non-invasive methods. Methods: Contact sport athletes (n = 300) will be assessed at the beginning of the season in a healthy state to establish baseline values, and then prospectively followed if a mild traumatic brain injury (mTBI) occurs on approximately days 1–2, 3–5, 7–10, 21, 30, and subsequently thereafter, depending on the severity of injury. The protocol includes spontaneous measurements at rest, during head postural change, controlled breathing maneuvers for cerebrovascular reactivity, a neurovascular coupling stimuli, and a baroreflex/autoregulation maneuver. Physiological data collection will include cerebral blood flow velocity, cerebral oxygenation, respiratory gases for end-tidal oxygen and carbon dioxide, finger photoplethysmography for blood pressure, seismocardiography for cardiac mechanics, and electrocardiography. Conclusion, Limitations, and Ethics: The protocol will provide an objective, physiological evidence-based approach in an attempt to better diagnose concussion to aid in return-to-play or -learn. Ethics approval has been granted by the University Research Ethics Board.

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Section: Measures and Physiological Assessment Equipmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Evidence-Based Objective Study Protocol for Evaluating Cardiovascular and Cerebrovascular Indices Following Concussion: The Neary Protocol

Neary

Singh

Bishop

et al. 2019

MPs

View full text Add to dashboard Cite

show abstract

“…Sometimes coined as the RR interval , HRV is the measure of the variation in time intervals between heartbeats, usually with reference to ventricular contraction. Classically, HRV is measured using the ECG using mainly the time-domain and frequency-domain approaches introduced in 1996 [69,70].…”

Section: Resultsmentioning

confidence: 99%

The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review

Li¹,

White²,

Tipoe³

et al. 2019

JMIR Mhealth Uhealth

139

100

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Background Mobile phone apps capable of monitoring arrhythmias and heart rate (HR) are increasingly used for screening, diagnosis, and monitoring of HR and rhythm disorders such as atrial fibrillation (AF). These apps involve either the use of (1) photoplethysmographic recording or (2) a handheld external electrocardiographic recording device attached to the mobile phone or wristband. Objective This review seeks to explore the current state of mobile phone apps in cardiac rhythmology while highlighting shortcomings for further research. Methods We conducted a narrative review of the use of mobile phone devices by searching PubMed and EMBASE from their inception to October 2018. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) mobile phone monitoring, (2) AF, (3) HR, and (4) HR variability (HRV). Results The findings of this narrative review suggest that there is a role for mobile phone apps in the diagnosis, monitoring, and screening for arrhythmias and HR. Photoplethysmography and handheld electrocardiograph recorders are the 2 main techniques adopted in monitoring HR, HRV, and AF. Conclusions A number of studies have demonstrated high accuracy of a number of different mobile devices for the detection of AF. However, further studies are warranted to validate their use for large scale AF screening.

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“…Lu and Yang [ 5 ] found that in laboratory conditions ECG and PPG give highly correlated HRV measures, but in more naturalistic conditions the PPG technology was vulnerable to motion artifacts. Guzik et al [ 6 ] found statistically significant differences in HRV measures calculated form ECG records and mobile device data. In contrast, Vovkanych et al [ 7 ] found good agreement between ECGs as did Huang et al [ 3 ] in a study that included a self-selected walking velocity task.…”

Section: Introductionmentioning

confidence: 99%

Alternative Devices for Heart Rate Variability Measures: A Comparative Test–Retest Reliability Study

Killian

Radin

Gardner

et al. 2021

Behavioral Sciences

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Using healthy adult participants, seven measures of heart rate variability were obtained simultaneously from four devices in five behavioral conditions. Two devices were ECG-based and two utilized photoplethysmography. The 140 numerical values (measure, condition, device) are presented. The comparative operational reliability of the four devices was assessed, and it was found that the two ECG-base devices were more reliable than the photoplethysmographic devices. The interchangeability of devices was assessed by determining the between-device Limits of Agreement. Intraclass correlation coefficients were determined and used to calculate the standard error of measurement and the Minimal Detectable Difference. The Minimal Detectable Difference, MDD, quantifies the smallest statistically significant change in a measure and is therefore critical when HRV measures are used longitudinally to assess treatment response or disease progression.

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Classic electrocardiogram-based and mobile technology derived approaches to heart rate variability are not equivalent

Cited by 16 publications

References 19 publications

An Evidence-Based Objective Study Protocol for Evaluating Cardiovascular and Cerebrovascular Indices Following Concussion: The Neary Protocol

An Evidence-Based Objective Study Protocol for Evaluating Cardiovascular and Cerebrovascular Indices Following Concussion: The Neary Protocol

The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review

Alternative Devices for Heart Rate Variability Measures: A Comparative Test–Retest Reliability Study

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