Heart Rate Variability and Pulse Rate Variability: Do Anatomical Location and Sampling Rate Matter?

Wearable technology and neuroimaging equipment using photoplethysmography (PPG) have become increasingly popularized in recent years. Several investigations deriving pulse rate variability (PRV) from PPG have demonstrated that a slight bias exists compared to concurrent heart rate variability (HRV) estimates. PPG devices commonly sample at ~20-100 Hz, where the minimum sampling frequency to derive valid PRV metrics is unknown. Further, due to different autonomic innervation, it is unknown if PRV metrics are harmonious between the cerebral and peripheral vasculature. Cardiac activity via electrocardiography (ECG) and PPG were obtained concurrently in 54 participants (29 females) in an upright orthostatic position. PPG data were collected at three anatomical locations: left third phalanx, middle cerebral artery, and posterior cerebral artery using a Finapres NOVA device and transcranial Doppler ultrasound. Data were sampled for five minutes at 1000 Hz and downsampled to frequencies ranging from 20 to 500 Hz. HRV (via ECG) and PRV (via PPG) were quantified and compared at 1000 Hz using Bland-Altman plots and coefficient of variation (CoV). A sampling frequency of ~100-200 Hz was required to produce PRV metrics with a bias of less than 2%, while a sampling rate of ~40-50 Hz elicited a bias smaller than 20%. At 1000 Hz, time- and frequency-domain PRV measures were slightly elevated compared to those derived from HRV (mean bias: ~1-8%). In conjunction with previous reports, PRV and HRV were not surrogate biomarkers due to the different nature of the collected waveforms. Nevertheless, PRV estimates displayed greater validity at a lower sampling rate compared to HRV estimates.

Insufficient sampling frequencies skew heart rate variability estimates: Implications for extracting heart rate metrics from neuroimaging and physiological data.

BACKGROUND: While cardiac pulsations are widely present within physiological and neuroimaging data, it is unknown the extent this information can provide valid and reliable heart rate and heart rate variability (HRV) estimates. The objective of this study was to demonstrate how a slight temporal shift due to an insufficient sampling frequency can impact the validity/accuracy of deriving cardiac metrics. METHODS: Twenty-two participants were instrumented with valid/reliable industry-standard or open-source electrocardiograms. Five-minute lead II recordings were collected at 1000 Hz in an upright orthostatic position. Following artifact removal, the 1000 Hz recording for each participant was downsampled to frequencies ranging 2-500 Hz. The validity of each participant's downsampled recording was compared against their 1000 Hz recording ("reference-standard") using Bland-Altman plots with 95 % limits of agreement (LOA), coefficient of variation (CoV), intraclass correlation coefficients, and adjusted r-squared values. RESULTS: Downsampled frequencies of ≥ 50 and ≥ 90 Hz produced highly robust measures with narrow log-transformed 95 % LOA (<±0.01) and low CoV values (≤3.5 %) for heart rate and HRV metrics, respectively. Below these thresholds, the log-transformed 95 % LOA became wider (LOA range: ±0.1-1.9) and more variable (CoV range: 1.5-111.6 %). CONCLUSION: These results provide an important consideration for obtaining cardiac information from physiological data. Compared to the "reference-standard" ECG, a seemingly negligible temporal shift of the systolic contraction (R wave) greater than 11-milliseconds (90 Hz) away from its true value, lessened the validity of the HRV. Further research is warranted to determine the minimum sampling frequency required to obtain valid heart rate/HRV metrics from pulsatile waveforms.

Impact of averaging fNIRS regional coherence data when monitoring people with long term post-concussion symptoms.

Significance: Functional near-infrared spectroscopy (fNIRS), with its measure of delta hemoglobin concentration, has shown promise as a monitoring tool for the functional assessment of neurological disorders and brain injury. Analysis of fNIRS data often involves averaging data from several channel pairs in a region. Although this greatly reduces the processing time, it is uncertain how it affects the ability to detect changes post injury. Aim: We aimed to determine how averaging data within regions impacts the ability to differentiate between post-concussion and healthy controls. Approach: We compared interhemispheric coherence data from 16 channel pairs across the left and right dorsolateral prefrontal cortex during a task and a rest period. We compared the statistical power for differentiating groups that was obtained when undertaking no averaging, vs. averaging data from 2, 4, or 8 source detector pairs. Results: Coherence was significantly reduced in the concussion group compared with controls when no averaging was undertaken. Averaging all 8 channel pairs before undertaking the coherence analysis resulted in no group differences. Conclusions: Averaging between fiber pairs may eliminate the ability to detect group differences. It is proposed that even adjacent fiber pairs may have unique information, so averaging must be done with caution when monitoring brain disorders or injury.

The temporal neurovascular coupling response remains intact during sinusoidal hypotensive and hypertensive challenges.

Introduction. Neurovascular coupling (NVC) describes the coupling of neuronal metabolic demand to blood supply, which has shown to be impaired with chronic hypertension, as well as with prolonged hypotension. However, it is unknown the extent the NVC response remains intact during transient hypo- and hyper-tensive challenges.Methods. Fifteen healthy participants (9 females/6 males) completed a visual NVC task ('Where's Waldo?') over two testing sessions, consisting of cyclical 30 s eyes closed and opened portions. The Waldo task was completed at rest (8 min) and concurrently during squat-stand maneuvers (SSMs; 5 min) at 0.05 Hz (10 s squat/stand) and 0.10 Hz (5 s squat-stand). SSMs induce 30-50 mmHg blood pressure oscillations, resulting in cyclical hypo- and hyper-tensive swings within the cerebrovasculature, allowing for the quantification of the NVC response during transient hypo- and hyper-tension. Outcome NVC metrics included baseline, peak, relative increase in cerebral blood velocity (CBv), and area-under-the-curve (AUC30) within the posterior and middle cerebral arteries indexed via transcranial Doppler ultrasound. Within-subject, between-task comparisons were conducted using analysis of variance with effect size calculations.Results. Differences were noted between rest and SSM conditions in both vessels for peak CBv (allp< 0.045) and the relative increase in CBv (allp <0.049) with small-to-large effect sizes. AUC30 metrics were similar between all tasks (allp> 0.090) with negligible-to-small effect sizes.Conclusions. Despite the SSMs eliciting ∼30-50 mmHg blood pressure oscillations, similar levels of activation occurred within the neurovascular unit across all conditions. This demonstrated the signaling of the NVC response remained intact during cyclical blood pressure challenges.

Neurovascular coupling on trial: How the number of trials completed impacts the accuracy and precision of temporally derived neurovascular coupling estimates.

Standard practices for quantifying neurovascular coupling (NVC) with transcranial Doppler ultrasound (TCD) require participants to complete one-to-ten repetitive trials. However, limited empirical evidence exists regarding how the number of trials completed influences the validity and reliability of temporally derived NVC metrics. Secondary analyses was performed on 60 young healthy participants (30 females/30 males) who completed eight cyclical eyes-closed (20-seconds), eyes-open (40-seconds) NVC trials, using the "Where's Waldo?" visual paradigm. TCD data was obtained in posterior and middle cerebral arteries (PCA and MCA, respectively). The within-day (n = 11) and between-day (n = 17) reliability were assessed at seven- and three-time points, respectively. Repeat testing from the reliability aims were also used for the concurrent validity analysis (n = 160). PCA metrics (i.e., baseline, peak, percent increase, and area-under-the-curve) demonstrated five trials produced excellent intraclass correlation coefficient (ICC) 95% confidence intervals for validity and within-day reliability (>0.900), whereas between-day reliability was good-to-excellent (>0.750). Likewise, 95% confidence intervals for coefficient of variation (CoV) measures ranged from acceptable (<20%) to excellent (<5%) with five-or-more trials. Employing fewer than five trials produced poor/unacceptable ICC and CoV metrics. Future NVC, TCD-based research should therefore have participants complete a minimum of five trials when quantifying the NVC response with TCD via a "Where's Waldo?" paradigm.

Treatment of Persistent Postconcussion Syndrome With Repetitive Transcranial Magnetic Stimulation Using Functional Near-Infrared Spectroscopy as a Biomarker of Response: Protocol for a Randomized Controlled Clinical Trial.

BACKGROUND: Approximately one-third of all concussions lead to persistent postconcussion syndrome (PPCS). Repetitive transcranial magnetic stimulation (rTMS) is a form of noninvasive brain stimulation that has been extensively used to treat refractory major depressive disorder and has a strong potential to be used as a treatment for patients with PPCS. Functional near-infrared spectroscopy (fNIRS) has already been used as a tool to assess patients with PPCS and may provide insight into the pathophysiology of rTMS treatment in patients with PPCS. OBJECTIVE: The primary objective of this research is to determine whether rTMS treatment improves symptom burden in patients with PPCS compared to sham treatment using the Rivermead postconcussion symptom questionnaire. The secondary objective is to explore the neuropathophysiological changes that occur following rTMS in participants with PPCS using fNIRS. Exploratory objectives include determining whether rTMS treatment in participants with PPCS will also improve quality of life, anxiety, depressive symptoms, cognition, posttraumatic stress, and function secondary to headaches. METHODS: A total of 44 adults (18-65 years old) with PPCS (>3 months to 5 years) will participate in a double-blind, sham-controlled, concealed allocation, randomized clinical trial. The participants will engage in either a 4-week rTMS treatment protocol or sham rTMS protocol (20 treatments). The left dorsolateral prefrontal cortex will be located through Montreal Neurologic Institute coordinates. The intensity of the rTMS treatment over the left dorsolateral prefrontal cortex will be 120% of resting motor threshold, with a frequency of 10 Hz, 10 trains of 60 pulses per train (total of 600 pulses), and intertrain interval of 45 seconds. Prior to starting the rTMS treatment, participant and injury characteristics, questionnaires (symptom burden, quality of life, depression, anxiety, cognition, and headache), and fNIRS assessment will be collected. Repeat questionnaires and fNIRS will occur immediately after rTMS treatment and at 1 month and 3 months post rTMS. Outcome parameters will be analyzed by a 2-way (treatment × time) mixed analysis of variance. RESULTS: As of May 6, 2021, 5 participants have been recruited for the study, and 3 have completed the rTMS protocol. The estimated completion date of the trial is May 2022. CONCLUSIONS: This trial will expand our knowledge of how rTMS can be used as a treatment option of PPCS and will explore the neuropathophysiological response of rTMS through fNIRS analysis. TRIAL REGISTRATION: ClinicalTrials.gov NCT04568369; https://clinicaltrials.gov/ct2/show/NCT04568369. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/31308.

The validity and reliability of an open source biosensing board to quantify heart rate variability.

BACKGROUND: Heart rate variability (HRV) is a popular tool to quantify autonomic function. However, this typically requires an expensive 3-12 lead electrocardiogram (ECG) and BioAmp system. This investigation sought to determine the validity and reliability of an OpenBCI cyton biosensing board (open source) for accurately quantifying HRV. NEW METHOD: A cyton board with a 3-lead ECG was employed to acquire heart rate waveform data, which was processed to obtain HRV within both time- and frequency-domains. The concurrent validity was compared to a simultaneous recording from an industry-standard 3-lead ECG (ADInstruments) (n = 15). The reliability of the cyton board was compared between three days within a 7-day timespan (n = 10). Upright quiet-stance short-term HRV metrics were quantified in time- and frequency-domains. RESULTS: The two devices displayed excellent limits of agreements (all log mean differences ±0.4) and very high between-device variable associations (all r 2 > 0.98). Between the three time points in the same subjects, no differences were noted within time- (all p > 0.71) or frequency-domains (all p > 0.88) across testing points. Finally, all HRV metrics exhibited excellent levels of reliability through high Cronbach's Alpha (all ≥0.916) and intraclass correlation coefficients (all ≥0.930); and small standard error of the measurement (all ≤0.7) and typical error of the measurement (all ≤0.1) metrics. COMPARISON WITH EXISTING METHODS: The cyton board with 3-lead ECG was compared with an industry-standard ADInstruments ECG during HRV assessments. There were no significant differences between devices with respect to time- and frequency-domains. The cyton board displayed high-levels of between-day reliability and provided values harmonious to previous ECG literature highlighting the applicability for longitudinal studies. CONCLUSION: With proper background knowledge regarding ECG principles and a small degree of set-up complexity, an open source cyton board can be created and employed to perform multimodal HRV assessments at a fraction of the cost (~4%) of an industry-standard ECG setup.

Automated Processing of fNIRS Data-A Visual Guide to the Pitfalls and Consequences.

With the rapid increase in new fNIRS users employing commercial software, there is a concern that many studies are biased by suboptimal processing methods. The purpose of this study is to provide a visual reference showing the effects of different processing methods, to help inform researchers in setting up and evaluating a processing pipeline. We show the significant impact of pre- and post-processing choices and stress again how important it is to combine data from both hemoglobin species in order to make accurate inferences about the activation site.