Almost done with edits for reviewers!

Author: Max Czapanskiy

analysis/paper/.gitignore

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+Response to reviewers.docx

analysis/paper/paper.Rmd

@@ -64,7 +64,7 @@ Recent advances in physio-logging (recording physiological variables using anima
 
 The ballistocardiogram (BCG) has potential applications to using accelerometers as heartrate monitors in both the wild and in managed care [@giovangrandi2011ballistocardiography; @sadekBallistocardiogramSignalProcessing2019; @inanBallistocardiographySeismocardiographyReview2015]. Ballistocardiography is a noninvasive method for measuring cardiac function based on the ballistic forces involved in the heart ejecting blood into the major vessels. The BCG originated as a clinical tool in the first half of the 20th century [@starrStudiesEstimationCardiac1939], but was largely superseded by electro- and echocardiography. However, potential novel applications like passive monitoring of heart function in at-risk populations [@giovangrandi2011ballistocardiography] has led to a recent resurgence of ballistocardiography research, with advances in hardware [@andreozzi2021] and signal processing methodology [@sadekBallistocardiogramSignalProcessing2019]. While the BCG is a three-dimensional phenomenon, it is strongest in the cranio-caudal axis [@inanBallistocardiographySeismocardiographyReview2015]. Along this axis, the waveform is composed of multiple peaks and valleys; most prominent of these is the so-called IJK complex [@pinheiroTheoryDevelopmentsUnobtrusive2010]. The precise physiological mechanism underlying the BCG waveform has not been fully resolved [@kim2016], but it has been established that the IJK complex occurs during systole and, in humans, occurs at approximately the same time as the T-wave in an electrocardiogram (ECG) [@inanBallistocardiographySeismocardiographyReview2015]. The BCG J wave is the most robust feature in the waveform and is typically used for detecting heart beats [@inanBallistocardiographySeismocardiographyReview2015].
 
-Here we present a method for generating a BCG from bio-logger accelerometry. We validated our method with a simultaneously recorded ECG on an adult killer whale in managed care (*Orcinus orca*) and applied it to detect heartrate in a blue whale. The relative orientation of the tag on the body is often uncertain when bio-loggers are deployed in the wild [@johnsonDigitalAcousticRecording2003], so in addition to a one-dimensional BCG based solely on cranio-caudal acceleration, we also generated a three-dimensional BCG, which we expected would be more robust in a field setting. Specifically, we tested three hypotheses to validate our method. First, a one-dimensional BCG would, in a controlled setting, produce instantaneous heartrates that are statistically equivalent to ECG instantaneous heartrates. Second, a three-dimensional BCG would, in a field setting, produce a more robust signal than a one-dimensional BCG. Third, BCG-derived heartrates would increase during the latter phases of dives, consistent with the progressive increase in heartrate routinely observed prior to and during ascent [@goldbogenExtremeBradycardiaTachycardia2019; @mcdonaldDeepdivingSeaLions2014].
+Here we present a method for generating a BCG from bio-logger cranio-caudal acceleration. We validated our method with a simultaneously recorded ECG on an adult killer whale in managed care (*Orcinus orca*) and applied it to detect heartrate in a blue whale. The relative orientation of a tag on a cetacean's body is often uncertain when bio-loggers are deployed in the wild [@johnsonDigitalAcousticRecording2003], so isolating acceleration along the cranio-caudal axis is subject to error. Therefore, we also compared a tri-axial BCG to the cranio-caudal BCG. Specifically, we tested three hypotheses to validate our method. First, a cranio-caudal (1D) BCG would, in a controlled setting, produce instantaneous heartrates that are statistically equivalent to ECG instantaneous heartrates. Second, a tri-axial (3D) BCG would, in a field setting, produce a more robust signal than a 1D BCG. Third, BCG-derived heartrates would increase during the latter phases of dives, consistent with the progressive increase in heartrate routinely observed prior to and during ascent [@goldbogenExtremeBradycardiaTachycardia2019; @mcdonaldDeepdivingSeaLions2014].
 
 # Materials and methods
 
@@ -287,7 +287,7 @@ Future bio-logging BCG methodology research should address the limitations impos
 
 ## Conclusions
 
-Here we presented a ballistocardiogram method for detecting resting apneic heartrate in cetaceans using accelerometers. We validated the method in a controlled setting with simultaneous ECG and in a field setting by confirming expected physiological patterns. As accelerometer tags have been deployed on many cetacean species for multiple decades, this method may be applied to mine existing datasets and better understand how heartrate scales with body size and other biological factors. It may also provide additional data for conservation physiology applications. For example, BCGs extracted from gliding phases before and after controlled sonar exposure experiments could quantify the physiological response to anthropogenic disturbance [@southall2019]. Even as the field of physio-logging progresses with new hardware innovations, this method demonstrates that computational advances can derive new insights from traditional sensors.
+Here we presented a ballistocardiogram method for detecting resting apneic heartrate in cetaceans using accelerometers. We validated the method in a controlled setting with simultaneous ECG and in a field setting by confirming expected physiological patterns. As accelerometer tags have been deployed on many cetacean species for multiple decades, this method may be applied to mine existing datasets and better understand how heartrate scales with body size and other biological factors. It may also provide additional data for conservation physiology applications. For example, BCGs extracted from gliding phases before and after controlled sonar exposure experiments could quantify the physiological response to anthropogenic disturbance [@southall2019]. Even as the field of physio-logging progresses with new hardware innovations [@williams2021; @fahlman2021; @hawkesIntroductionThemeIssue2021], this method demonstrates that computational advances can derive new insights from traditional sensors.
 
 # Acknowledgements
 

analysis/paper/paper.docx

@@ -776,3 +776,30 @@ @article{savoca2021
 	url = {http://dx.doi.org/10.1038/s41586-021-03991-5},
 	langid = {en}
 }
+
+@article{williams2021a,
+	title = {Diving physiology of marine mammals and birds: the development of biologging techniques},
+	author = {{Williams}, {Cassondra L.} and {Ponganis}, {Paul J.}},
+	year = {2021},
+	month = {06},
+	date = {2021-06-14},
+	journal = {Philosophical Transactions of the Royal Society B: Biological Sciences},
+	pages = {20200211},
+	volume = {376},
+	number = {1830},
+	doi = {10.1098/rstb.2020.0211},
+	url = {http://dx.doi.org/10.1098/rstb.2020.0211},
+	langid = {en}
+}
+
+@article{fahlman2021,
+	title = {The New Era of Physio-Logging and Their Grand Challenges},
+	author = {{Fahlman}, {Andreas} and {Aoki}, {Kagari} and {Bale}, {Gemma} and {Brijs}, {Jeroen} and {Chon}, {Ki H.} and {Drummond}, {Colin K.} and {Føre}, {Martin} and {Manteca}, {Xavier} and {McDonald}, {Birgitte I.} and {McKnight}, {J. Chris} and {Sakamoto}, {Kentaro Q.} and {Suzuki}, {Ippei} and {Rivero}, {M. Jordana} and {Ropert-Coudert}, {Yan} and {Wisniewska}, {Danuta M.}},
+	year = {2021},
+	month = {03},
+	date = {2021-03-30},
+	journal = {Frontiers in Physiology},
+	volume = {12},
+	doi = {10.3389/fphys.2021.669158},
+	url = {http://dx.doi.org/10.3389/fphys.2021.669158}
+}