Abstract
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.
Highlights
Resting heart rate variability (HRV; variation in the intervals between heartbeats) has proven to be an informative physiological measure, integrating a wide range of processes linked to sympathovagal balance into a metric that is indicative of an individual’s temperament or coping style [1,2,3] and reactivity to stress, whether psychological or physical [3,4,5,6]
Comparison of FirstBeatTM artefact detection with manual flats and stairs detection Our comparison of the classification of inter beat intervals (IBIs) as artefacts by the FirstbeatTM Sports software (v.4.5.0.2) with our own classification of IBIs as flats or stairs illustrates that the vast majority of flats and stairs occurred in IBIs that had been corrected by the FirstbeatTM Sports software (Table 1). 40.7% of the IBIs identified as artefacts and corrected by the FirstbeatTM Sports software were subsequently identified as flats by our algorithm (Table 1A)
2.2% of IBIs were identified as flats by us and not identified as artefacts by the FirstbeatTM Sports software
Summary
Resting heart rate variability (HRV; variation in the intervals between heartbeats) has proven to be an informative physiological measure, integrating a wide range of processes linked to sympathovagal balance into a metric that is indicative of an individual’s temperament or coping style [1,2,3] and reactivity to stress, whether psychological or physical [3,4,5,6]. Even non-invasive portable ECG devices, such as Holter monitors [9, 10], are typically only capable of short-term recordings making them more suitable for captive or laboratory animals and livestock. This places constraints upon the ability of researchers to incorporate the potentially useful HRV metrics in studies of free-ranging wild animals. There is a need for affordable robust devices that can provide reliable IBI data at the required millisecond precision on free-ranging wild animals Such devices would allow for long-term and remote recording of data across multiple individuals to minimise disturbance from the number of interventions required, allowing the study animals to behave normally in their natural environment. We describe and assess a system that has the potential to fulfil this role even in a challenging situation
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