An external telemetry system for recording resting heart rate variability and heart rate in free-ranging large wild mammals

Measures of heart rate variability (and heart rate more generally) are providing powerful insights into the physiological drivers of behaviour. Resting heart rate variability (HRV) can be used as an indicator of individual differences in temperament and reactivity to physical and psychological stress. There is increasing interest in deriving such measures from free ranging wild animals, where individuals are exposed to the natural and anthropogenic stressors of life. We describe a robust, externally mounted heart rate monitor for use in wild mammals, deployed here on wild breeding adult female grey seals (Halichoerus grypus), that delivers millisecond precise measures of inter beat intervals (IBIs), allowing computation of resting HRV parameters. Based on Firstbeat™ heart rate belts, our system allows for remote, continuous recording of IBI data from over 30 individuals simultaneously at ranges of up to 200m. We assessed the accuracy of the IBI data provided by the Firstbeat™ system using concurrent IBI data derived from in-field electrocardiogram (ECG) recordings. Bland-Altmann analyses demonstrated high correspondence between the two sets of IBI data, with a mean difference of 0.87±0.16ms. We used generalized additive mixed-effects models to examine the impact of the default Firstbeat™ software artefact correction procedure upon the generation of anomalous data (flats and stairs). Artefact correction and individual activity were major causes of flats and stairs. We used simulations and models to assess the impact of these errors on estimates of resting HRV and to inform criteria for subsampling relatively error free IBI traces. These analyses allowed us to establish stringent filtering procedures to remove traces with excessive numbers of artefacts, including flats and stairs. Even with strict criteria for removing potentially erroneous data, the abundance of data yielded by the Firstbeat™ system provides the potential to extract robust estimates of resting HRV. We discuss the advantages and limitations of our system for applications beyond the study system described here.

Flexor digitorum superficialis muscular activity is more reliable than mentalis muscular activity for rapid eye movement sleep without atonia quantification

Study objectives To evaluate interrater reliability for artefact correction in the context of semi-automated quantification of rapid eye movement (REM) sleep without atonia (RWA) in the mentalis and flexor digitorum superficialis (FDS) muscles. Methods We included video-polysomnographies of 14 subjects with apnea-hypopnea-index in REM sleep (AHIREM)<15/h and 11 subjects with AHIREM≥15/h. Eight subjects had isolated REM sleep behavior disorder. A validated algorithm (www.osg.be) automatically scored phasic and “any” EMG activity in the mentalis muscle, and phasic EMG activity in the FDS muscles. Four independent expert scorers performed artefact correction according to the SINBAR (Sleep Innsbruck Barcelona) recommendations. Interrater reliability for artefact correction was computed with B-statistics. The variability across scorers of four RWA indices (phasic mentalis, “any” mentalis, phasic FDS and SINBAR – i.e. “any” mentalis and/or phasic FDS – EMG activity indices) was computed. With Friedman tests we compared B-statistics obtained for mentalis and FDS muscles, and the variability of the RWA indices. Influence of AHIREM and RBD diagnosis on the RWA indices variability was evaluated with linear regressions. Results Interrater reliability for artefact correction was higher in the FDS than in the mentalis muscle (p<0.001). Phasic FDS activity was minimally affected by artefacts. Accordingly, the phasic FDS EMG activity index had the lowest variability across scorers (p<0.001). Variability across scorers of the RWA indices including the mentalis muscle increased with AHIREM and was independent from RBD diagnosis. Conclusions Due to the consistently found low number of artefacts, phasic FDS activity is a reliable measure of RWA.

Influence of Artefact Correction and Recording Device Type on the Practical Application of a Non-Linear Heart Rate Variability Biomarker for Aerobic Threshold Determination

Recent study points to the value of a non-linear heart rate variability (HRV) biomarker using detrended fluctuation analysis (DFA a1) for aerobic threshold determination (HRVT). Significance of recording artefact, correction methods and device bias on DFA a1 during exercise and HRVT is unclear. Gas exchange and HRV data were obtained from 17 participants during an incremental treadmill run using both ECG and Polar H7 as recording devices. First, artefacts were randomly placed in the ECG time series to equal 1, 3 and 6% missed beats with correction by Kubios software’s automatic and medium threshold method. Based on linear regression, Bland Altman analysis and Wilcoxon paired testing, there was bias present with increasing artefact quantity. Regardless of artefact correction method, 1 to 3% missed beat artefact introduced small but discernible bias in raw DFA a1 measurements. At 6% artefact using medium correction, proportional bias was found (maximum 19%). Despite this bias, the mean HRVT determination was within 1 bpm across all artefact levels and correction modalities. Second, the HRVT ascertained from synchronous ECG vs. Polar H7 recordings did show an average bias of minus 4 bpm. Polar H7 results suggest that device related bias is possible but in the reverse direction as artefact related bias.

Impact of Using Different Levels of Threshold-Based Artefact Correction on the Quantification of Heart Rate Variability in Three Independent Human Cohorts

Heart rate variability (HRV) is a non-invasive indicator of autonomic nervous system function. HRV recordings show artefacts due to technical and/or biological issues. The Kubios software is one of the most used software to process HRV recordings, offering different levels of threshold-based artefact correction (i.e., Kubios filters). The aim of the study was to analyze the impact of different Kubios filters on the quantification of HRV derived parameters from short-term recordings in three independent human cohorts. A total of 312 participants were included: 107 children with overweight/obesity (10.0 ± 1.1 years, 58% men), 132 young adults (22.2 ± 2.2 years, 33% men) and 73 middle-aged adults (53.6 ± 5.2 years, 48% men). HRV was assessed using a heart rate monitor during 10–15 min, and the Kubios software was used for HRV data processing using all the Kubios filters available (i.e., 6). Repeated-measures analysis of variance indicated significant differences in HRV derived parameters in the time-domain (all p < 0.001) across the Kubios filters in all cohorts, moreover similar results were observed in the frequency-domain. When comparing two extreme Kubios filters, these statistical differences could be clinically relevant, e.g. more than 10 ms in the standard deviation of all normal R-R intervals (SDNN). In conclusion, the results of the present study suggest that the application of different Kubios filters had a significant impact on HRV derived parameters obtained from short-term recordings in both time and frequency-domains.

Impact of movement and motion-artefact correction on image quality and interpretability in CBCT units with aligned and lateral-offset detectors

Objectives: To evaluate the impact of movement and motion-artefact correction systems on CBCT image quality and interpretability of simulated diagnostic tasks for aligned and lateral-offset detectors. Methods: A human skull simulating three diagnostic tasks (implant planning in the anterior maxilla, implant planning in the left-side-mandible and mandibular molar furcation assessment in the right-side-mandible) was mounted on a robot performing six movement types. Four CBCT units were used: Cranex 3Dx (CRA), Ortophos SL (ORT), Promax 3D Mid (PRO), and X1. Protocols were tested with aligned (CRA, ORT, PRO, and X1) and lateral-offset (CRA and PRO) detectors and two motion-artefact correction systems (PRO and X1). Movements were performed at one moment-in-time (t1), for units with an aligned detector, and three moments-in-time (t1-first-half of the acquisition, t2-second-half, t3-both) for the units with a lateral-offset detector. 98 volumes were acquired. Images were scored by three observers, blinded to the unit and presence of movement, for motion-related stripe artefacts, overall unsharpness, and interpretability. Fleiss’ κ was used to assess interobserver agreement. Results: Interobserver agreement was substantial for all parameters (0.66–0.68). For aligned detectors, in all diagnostic tasks a motion-artefact correction system influenced image interpretability. For lateral-offset detectors, the interpretability varied according to the unit and moment-in-time, in which the movement was performed. PRO motion-artefact correction system was less effective for the offset detector than its aligned counterpart. Conclusion: Motion-artefact correction systems enhanced image quality and interpretability for units with aligned detectors but were less effective for those with lateral-offset detectors.

Effect of micro-computed tomography reconstruction protocols on bone fractal dimension analysis

Objectives: To evaluate the influence of the level of three micro-CT reconstruction tools: beam-hardening correction (BHC), smoothing filter (SF), and ring artefact correction (RAC) on the fractal dimension (FD) analysis of trabecular bone. Methods: Five Wistar rats’ maxillae were individually scanned in a SkyScan 1174 micro-CT device, under the following settings: 50 kV, 800 µA, 10.2 µm voxel size, 0.5 mm Al filter, rotation step 0.5°, two frames average, 180° rotation and scan time of 35 min. The raw images were reconstructed under the standard protocol (SP) recommended by the manufacturer, a protocol without any artefact correction tools (P0) and 35 additional protocols with different combinations of SF, RAC and BHC levels. The same volume of interest was established in all reconstructions for each maxilla and the FD was calculated using the Kolmogorov (box counting) method. One-way ANOVA with Dunnet’s post-hoc test was used to compare the FD of each reconstruction protocol (P0–P35) with the SP (α = 5%). Multiple linear regression verified the dependency of reconstruction tools in FD. Results: Overall, FD values are not dependent on RAC (p = 0.965), but increased significantly when the level of BHC and SF increased (p < 0.001). FD values from protocols with BHC at 45% combined with SF of 2, and BHC at 30% combined with SF of 4 or 6 had no statistical difference compared to SP. Conclusions: BHC and SF tools affect the FD values of micro-CT images of the trabecular bone. Therefore, these reconstruction parameters should be standardized when the FD is analyzed.