AEvD was supported by the Dutch Heart Foundation (DHF-2007B103). The authors would like to thank all mothers and children in the Amsterdam Born Children and their Development (ABCD) study, and the entire development and maintenance team of the VU-AMS system at the Division for Instrumentation - the Department of Psychophysiology (VU University, Amsterdam, the Netherlands).

1. Preparation: Starting Up
<ol>
	<li>You need:
	<ul>
		<li>a VU-AMS5fs ambulatory recording device (including an infrared interface cable that either connects to the RS232 serial port of a PC or to a USB port).</li>
		<li>7 electrodes (we used ConMed 1690-003).</li>
		<li>2 charged AA-batteries.</li>
		<li>an empty CompactFlash memory card (the VU-AMS5fs has been extensively tested with the 1GB 80x CF card from Transcend (TS1GCF80), but other CF cards should work too).</li>
		<li>a laptop or PC with flash card reader and the Data Analysis Management Software (DAMS) suite installed.</li>
		<li>a stopwatch.</li>
		<li>music player with children's stories and headphones and a small self-inflatable air mattress are optional.</li>
	</ul>
	</li>
	<li>Check the time and date settings on the laptop/PC, since these will be recorded as metadata on your files. Put the empty memory card and full batteries in the VU-AMS device (successful placement is signalled by a triple beep). When the device is on standby, the green light will flash twice every ten seconds. This indicates it is ready, but not recording. Now connect the device to the laptop using the provided cable and start up the DAMS program. Initiate communication with the device (select the tab 'device' and choose the appropriate connection mode, infrared cable or bluetooth).</li>
	<li>Have the participant take off his/her upper body wear. In the places where the electrodes will be placed,clean the skin with alcohol-wipes, and place the seven electrodes on the chest and back (Figure 1). Then attach the lead wires following the color scheme, and connect them to the device.</li>
	<li>Check the battery type and battery voltage indication (this should be about 3.4 V for alkaline and about 2.4 V for rechargeable NiMH batteries). Fill out the identification field. The typical sampling frequencies are as shown in the figure (Figure 2).</li>
	<li>Measure the distance between the two chest electrodes in millimeters, and fill this out in the field 'ICG-V distance'. Then click 'send settings' to send the current settings/ID to the device.</li>
	<li>Now, the 'Online' option of the program should be used to display the ECG, &Delta;Z (this is the respiration) and dZ/dt (this is the ICG). The &Delta;Z signal reflects the base impedance across the thorax, which after appropriate filtering can be used to extract the respiration signal with high fidelity 7. The dZ/dt signal is the &Delta;Z differentiated over time and reflects rapid changes in &Delta;Z linked to the ejection of blood from the ventricle into the aorta.
	<ol>
		<li>A clear QRST-complex should be detectable in the ECG. The R-wave should be upward and it should be the peak with the largest (absolute) amplitude in either direction.</li>
		<li>The &Delta;Z should be within -0.5 and +0.5 &Omega; most of the time and dZ/dt between -1 and +1 &Omega;/sec.</li>
		<li>Z0 should always stay within an 8 to 20 &Omega; range. This variation reflects the fact that the thorax impedance signal depends on the distance between the measuring electrodes which is a function of the child's height, and the 'wetness' of the thorax column enclosed by the measuring electrodes, differences in body composition (e.g. BMI) can affect the amplitude of the dZ/dt signal (fat mass containing less water than muscle). Individual differences in absolute Z0 amplitude are also reflected in the &Delta;Z signal but this does not affect the determination of systolic time intervals, which are amplitude-independent.</li>
		<li>The &Delta;Z signal should reflect deep breathing of the subject clearly (instruct the child to take a slow deep breath and exhale slowly).</li>
		<li>In the ICG the typical upward waveform reflecting the cardiac ejection phase should be clearly detectable. Light movement of the subject should not distort the dZ/dt signal. If these criteria are not met, re-clean the skin and re-attach the electrodes until satisfactory signals are obtained.</li>
	</ol>
	</li>
	<li>When good signals are attained, start data recording by pressing the 'start' button. You will hear a beep acknowledging the start of the recording and the green light will start flashing once every three seconds. The registration has now started. Close the VU-DAMS program. You can now disconnect the device from the interface cable.</li>
</ol>
2. The Registration Period
<ol>
	<li>Once the registration has started, ask the child to lie down for the first experimental condition. When the child has been in the supine position (without head-up tilt) for two minutes, you shortly (&lt; 2 s) press the small black button on top of the device. Pressing this button marks a special event, and will later on help you identify the start of this condition in your data.</li>
	<li>After four minutes, press the event button again. This signals the end of the lying down condition. Now have the child sit up and repeat the procedure for this second condition. Press the button, wait four minutes and press the button again. The children are instructed to rest quietly during these conditions.</li>
	<li>To stop the measurement, press and hold down the button for at least 3 sec. The light will flash every 10 sec to indicate it has stopped and is in 'stand by' mode. Once the device has stopped, you may disconnect the lead wire plug from the connector and the lead wires from the electrodes.</li>
	<li>Remove the batteries and flash card form the VU-AMS device and place the flash card in the reader unit. Move the acquired files to a designated directory (typically the name of the directory will be identical to the subject identifier used in the identification field).</li>
</ol>
3. Processing the Data
<ol>
	<li>Upon opening the data with VU-DAMS program, the data will be automatically converted from raw data format (extension .5fs) to a new format (extension .amsdata). This is the data file that VU-DAMS will be using in the ensuing steps.</li>
	<li>First extract the Inter Beat Interval time series from the ECG signal. Select the Detect R-peaks tab. An automated algorithm will detect all R-peaks in the ECG signal and select (if present) periods with very low ECG quality for removal. In the upper left hand corner the number of Blue (correct), Yellow (medium suspicious) or RED (highly suspicious) is indicated. By pressing '.' (DOT) the cursor is moved to the next suspicious R-peak and the user can delete or add markers for R-waves by hand. It is recommended that at least all highly suspicious beats are visually inspected.</li>
	<li>The main aim is to obtain a mean value for the heart rate, the preejection period (PEP) and measures of respiratory sinus arrhythmia (RSA, HF, RMSSD) across the experimental conditions used. Therefore proceed by indicating which periods in the raw data correspond to these conditions. This process is called 'data labeling'. Select the Label Data tab. Two panels show the heart rate signal and movement signal respectively, as well as the actual time of the recording.</li>
	<li>Place the mouse cursor in the top bar where it says "click and drag to add labels" at around the start time of your first condition and drag the mouse to the end time of that condition. These times are either obtained from a written record of start and stop times (that you noted down during data collection) or you can use the start and stop markers obtained from pressing the button at the start and end of each condition, which are the vertical lines running across the HR and movement graphs.</li>
	<li>Each label can be given a (unique) identifier to signal a particular condition. In our case we have only one category for our labels: experimental condition. This category has two values: lying down and sitting up.</li>
	<li>VU-DAMS needs to be made aware of the experimental design by a so-called label configuration file (label.cfg). This is an ASCII file that can be opened with most text editors and, for example, looks like this: 
	# exp_condition 
	10 lying down 
	11 sitting up</li>
	<li>By placing the label.cfg file in the directory of the .amsdata files, it will be automatically loaded by the VU-DAMS program. Once a label has been made, a pop up screen will appear with the categories/values listed in the label.cfg file. Select 'lying down' for the first label and 'sitting up' for the second label.</li>
	<li>After labeling, select the 'Impedance scoring' tab to score the PEP in the impedance cardiogram. For each of the conditions an ensemble averaged dZ/dt waveform is displayed, time-locked to the ECG R-peak. An ensemble averaged ECG is presented below the dZ/dt waveform. Place the four vertical cursors in the correct positions: ECG Q-wave onset (start of electrical activity), ICG B-point (start of the ejection phase), ICG dZ/dt-min (maximal ejection speed), and ICG X-point (aortic valve closure - end of ejection phase).</li>
	<li>Next, select the 'Respiration Scoring' tab to score the peak-valley RSA using the respiratory and ECG signals. Automated breath-to-breath scoring of the respiratory interval and the shortest interbeat interval during inspiration and the longest interbeat interval during expiration can now be inspected. Typically the automated detection algorithm should not classify more than 15% of the breaths as deviant - otherwise inspect the respiration signal and tune the parameters of the detection algorithm as needed. 
	 
	Guidelines for visual inspection of the ECG, ICG and respiration signals and interactive PEP and RSA scoring can be found on the VU-AMS website, <a href="http://www.vu-ams.nl" target="_blank">www.vu-ams.nl</a>.</li>
</ol>
<ol start="10">
	<li>Finally, select the Label Information tab. A table with the results appears after calculation. Each row represents the average value of a series of physiological parameters (heart rate, PEP, RSA, RR) for each labeled time period. The first column has the subject identifier (Label_ID). The last column indicates the values of all categories used during labeling (here only a single category 'experimental condition' with two values, 'sitting up' and 'lying down'). Spectral powers of the interbeat interval times series are given only for labels with a minimum length of 4 min (otherwise the missing code is displayed). The spreadsheet in this display can be exported to ASCII or EXCEL for further statistical analyses.</li>
</ol>

<ol>
	<li>de Geus, E. J., Willemsen, G. H., Klaver, C. H., van Doornen, L. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ambulatory+measurement+of+respiratory+sinus+arrhythmia+and+respiration+rate.">Ambulatory measurement of respiratory sinus arrhythmia and respiration rate.</a> Biol. Psychol. 41, 205-227 (1995).</li><li>Goedhart, A. D., van der, S. S., Houtveen, J. H., Willemsen, G., de Geus, E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+time+and+frequency+domain+measures+of+RSA+in+ambulatory+recordings.">Comparison of time and frequency domain measures of RSA in ambulatory recordings.</a> Psychophysiology. 44, 203-215 (2007).</li><li>Goedhart, A. D., Kupper, N., Willemsen, G., Boomsma, D. I., de Geus, E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+stability+of+ambulatory+stroke+volume+and+cardiac+output+measured+by+impedance+cardiography.">Temporal stability of ambulatory stroke volume and cardiac output measured by impedance cardiography.</a> Biol. Psychol. 72, 110-117 (2006).</li><li>Riese, H., Groot, P. F. C., van den Berg, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Large-scale+ensemble+averaging+of+ambulatory+impedance+cardiograms.">Large-scale ensemble averaging of ambulatory impedance cardiograms.</a> Behavior Research Methods Instruments &amp; Computers. 35, 467-477 (2003).</li><li>Willemsen, G. H., de Geus, E. J., Klaver, C. H., van Doornen, L. J., Carroll, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ambulatory+monitoring+of+the+impedance+cardiogram.">Ambulatory monitoring of the impedance cardiogram.</a> Psychophysiology. 33, 184-193 (1996).</li><li>van Dijk, A. E., van Eijsden, M., Stronks, K., Gemke, R. J., Vrijkotte, T. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prenatal+stress+and+balance+of+the+child's+cardiac+autonomic+nervous+system+at+age+5-6+years.">Prenatal stress and balance of the child's cardiac autonomic nervous system at age 5-6 years.</a> PLoS ONE. 7, e30413 (2012).</li><li>Houtveen, J. H., de Groot, P. F., de Geus, E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+variation+in+posture+and+respiration+on+RSA+and+pre-ejection+period.">Effects of variation in posture and respiration on RSA and pre-ejection period.</a> Psychophysiology. 42, 713-719 (2005).</li><li>Goedhart, A. D., Willemsen, G., Houtveen, J. H., Boomsma, D. I., De Geus, E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparing+low+frequency+heart+rate+variability+and+preejection+period:+two+sides+of+a+different+coin.">Comparing low frequency heart rate variability and preejection period: two sides of a different coin.</a> Psychophysiology. 45, 1086-1090 (2008).</li><li>van Dijk, A. E., van Eijsden, M., Stronks, K., Gemke, R. J., Vrijkotte, T. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cardio-metabolic+risk+in+5-year-old+children+prenatally+exposed+to+maternal+psychosocial+stress:+the+ABCD+study.">Cardio-metabolic risk in 5-year-old children prenatally exposed to maternal psychosocial stress: the ABCD study.</a> BMC Public Health. 10, 251 (2010).</li><li>van Lien, R., Goedhart, A., Kupper, N., Boomsma, D., Willemsen, G., de Geus, E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Underestimation+of+cardiac+vagal+control+in+regular+exercisers+by+24-hour+heart+rate+variability+recordings.">Underestimation of cardiac vagal control in regular exercisers by 24-hour heart rate variability recordings.</a> Int. J. Psychophysiol. 81, 169-176 (2011).</li></ol>

We have nothing to disclose.

We used an ambulatory recording device to measure cardiac autonomic control in 3097 children, aged between 5 and 7 years. Seven electrodes sufficed to measure the ECG and ICG from which the heart rate, heart rate variability and the systolic time intervals were extracted. Heart rate variability in the respiratory frequency band (RSA) is a valid indicator of cardiac parasympathetic activity. The systolic time interval, PEP, by reflecting cardiac contractility, is a valid indicator of cardiac sympathetic activity. The mean values obtained for HR, PEP and RSA, the effects of posture changes and the differences between boys and girls were in line with what would be expected from the literature.
As ambulatory monitoring removed the necessity of assessment in a laboratory our recordings could be done in various locations (e.g. school, sports center, science museum) without differences in signal recording quality. However, it is of crucial importance to standardize within or between subject comparisons for posture and physical load, as afterload and preload effects can co-determine the PEP without any changes in cardiac sympathetic drive 7. We conclude that ambulatory recording of the ECG and ICG in large samples of children is highly feasible and propose the current standardized study design as a useful template for future assessments of cardiac autonomic control in children.

<table><tbody><tr><td>VU-AMS5fs ambulatory recording device &amp;amp; infrared interface cable</td><td>VU University Amsterdam</td><td>n/a</td><td>&lt;a href=&quot;http://www.vu-ams.nl&quot; target=&quot;_blank&quot;&gt;http://www.vu-ams.nl&lt;/a&gt;</td></tr><tr><td>Electrodes</td><td>ConMed</td><td>1690-003</td><td></td></tr><tr><td>AA-batteries</td><td></td><td></td><td></td></tr><tr><td>CompactFlash memory card</td><td></td><td></td><td></td></tr><tr><td>Laptop/pc with flash card reader</td><td></td><td></td><td></td></tr><tr><td>VU-DAMS software suite</td><td>VU University Amsterdam</td><td></td><td>free download, &lt;a href=&quot;http://www.vu-ams.nl&quot; target=&quot;_blank&quot;&gt;http://www.vu-ams.nl&lt;/a&gt;</td></tr><tr><td>Stopwatch</td><td></td><td></td><td></td></tr><tr><td>Music player &amp;amp; headphones</td><td></td><td></td><td>optional</td></tr><tr><td>Self-inflatable air mattress</td><td></td><td></td><td>optional</td></tr></tbody></table>

measuring cardiac autonomic nervous system (ans) activity in children

The autonomic nervous system (ANS) controls mainly automatic bodily functions that are engaged in homeostasis, like heart rate, digestion, respiratory rate, salivation, perspiration and renal function. The ANS has two main branches: the sympathetic nervous system, preparing the human body for action in times of danger and stress, and the parasympathetic nervous system, which regulates the resting state of the body.
ANS activity can be measured invasively, for instance by radiotracer techniques or microelectrode recording from superficial nerves, or it can be measured non-invasively by using changes in an organ's response as a proxy for changes in ANS activity, for instance of the sweat glands or the heart. Invasive measurements have the highest validity but are very poorly feasible in large scale samples where non-invasive measures are the preferred approach. Autonomic effects on the heart can be reliably quantified by the recording of the electrocardiogram (ECG) in combination with the impedance cardiogram (ICG), which reflects the changes in thorax impedance in response to respiration and the ejection of blood from the ventricle into the aorta. From the respiration and ECG signals, respiratory sinus arrhythmia can be extracted as a measure of cardiac parasympathetic control. From the ECG and the left ventricular ejection signals, the preejection period can be extracted as a measure of cardiac sympathetic control. ECG and ICG recording is mostly done in laboratory settings. However, having the subjects report to a laboratory greatly reduces ecological validity, is not always doable in large scale epidemiological studies, and can be intimidating for young children. An ambulatory device for ECG and ICG simultaneously resolves these three problems.
Here, we present a study design for a minimally invasive and rapid assessment of cardiac autonomic control in children, using a validated ambulatory device 1-5, the VU University Ambulatory Monitoring System (VU-AMS, Amsterdam, the Netherlands,<a href="http://www.vu-ams.nl" target="_blank"> www.vu-ams.nl</a>).

In the Amsterdam Born Children and their Development study, a Dutch prospective, longitudinal birth cohort, the measurement protocol was started in 3,097 children 6. Approval was obtained from the Academic Medical Center Medical Ethical Committee, the VU University Medical Center Medical Ethical Committee and the Registration Committee of Amsterdam. All participating mothers gave written informed consent for themselves and their children.
As the monitors are lightweight and unobtrusive, the children tolerated these measurements very well. We do not have data on the refusal rate, but experience taught us that only a few children resisted the placement of the electrodes and thereby obstructed further assessment. Of the 3,097 registrations, 0.7% were lost due to either equipment failure or misplacement of files. Out of the 3,074 registrations left, 98.7% were of children who completed the entire protocol (n = 3,056). Within each of the labelled time periods (we originally labelled four time periods, but later summarized these to two), we encountered unclear ICG signals, meaning PEP could not be determined. This led to a loss of 1.5% in the first out of four labelled periods, 2.4% in the second, 2.8% in the third and 4.1% in the fourth period. Complete data on PEP in all time periods was available in 2,797 cases (91.5%, thus 8.5% loss due to unclear ICG signals). Complete data on heart rate (HR), pre-ejection period (PEP) and respiratory sinus arrhythmia (RSA), as well as sex and age, was available from 2,761 children; in this final step, 1.3% data loss occurred, due to unknown reasons. Overall, 89.2% of the started registrations led to full subject data. The mean age of the children was 5.7 years (SD 0.5; interquartile range 5.0:6.5), and their BMI was 15.5 kg/m2 (SD 1.5; interquartile range 13.9:17.2).
The mean values of the major outcome variables HR, PEP, and RSA are given in Table 1 and graphically depicted in Figure 3, separately for boys and girls. HR (both lying down and sitting up) and PEP (only sitting up) were higher in girls than in boys (both postures). RSA was lower in girls than in boys (both postures). The higher values for HR in girls are likely to be caused by the lower vagal (parasympathetic) cardiac control. Their sympathetic cardiac control was not different or even lower than that in boys (sitting up).
In both sexes, HR was higher when sitting up compared to lying down, whereas RSA was lower when sitting up. This reflects the lower vagal control when sitting up. PEP was shorter lying down then sitting up. This effect was also as expected, and it reflects the outcome of opposite processes: lower sympathetic activity (lengthens PEP) while lying down with increased preload (shortens PEP)7.
<table border="1" class="jove_content_small" fo:keep-together.within-page="always">
 <tbody>
 <tr>
 <td rowspan="3"> </td>
 <td colspan="6">Boys</td>
 <td colspan="5">Girls</td>
 </tr>
 <tr>
 <td colspan="3">Lying down</td>
 <td colspan="3">Sitting up</td>
 <td colspan="2">Lying down</td>
 <td colspan="3">Sitting up</td>
 </tr>
 <tr>
 <td>Mean</td>
 <td colspan="2">SD</td>
 <td>Mean</td>
 <td>SD</td>
 <td>&nbsp;</td>
 <td>Mean</td>
 <td>SD</td>
 <td>Mean</td>
 <td>SD</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Heart rate (bpm)</td>
 <td>83.9</td>
 <td>9.5</td>
 <td>*</td>
 <td>89.1</td>
 <td>10</td>
 <td>*&dagger;</td>
 <td>86.9</td>
 <td>10.1</td>
 <td>92.4</td>
 <td>10.4</td>
 <td>&dagger;</td>
 </tr>
 <tr>
 <td>Pre-ejection period (msec)</td>
 <td>76.9</td>
 <td>11.8</td>
 <td>&nbsp;</td>
 <td>78.5</td>
 <td>12.2</td>
 <td>*&dagger;</td>
 <td>77.7</td>
 <td>10.3</td>
 <td>81</td>
 <td>11.7</td>
 <td>&dagger;</td>
 </tr>
 <tr>
 <td>Respiratory sinus arrythmia (msec)</td>
 <td>127.0</td>
 <td>60.4</td>
 <td>*</td>
 <td>115.7</td>
 <td>55.8</td>
 <td>*&dagger;</td>
 <td>121.7</td>
 <td>56.8</td>
 <td>108.7</td>
 <td>51.9</td>
 <td>&dagger;</td>
 </tr>
 </tbody>
</table>
Table 1. Cardiac autonomic nervous system measures in boys and girls, by posture on posture difference. p &lt; 0.05 for one sample T-test on sex difference. &dagger; p &lt; 0.05 for paired samples T-test.
<img alt="Figure 1" src="/files/ftp_upload/50073/50073fig1.jpg" /> 
 Figure 1. The seven electrodes should be placed on the participant's chest and back. The first ECG electrode (V-) is placed slightly below the right collar bone 4 cm to the right of the sternum. The second ECG electrode (V+) is placed at the apex of the heart over the ninth rib on the left lateral margin of the chest approximately at the level of the processus xiphodius. The third ECG electrode (GND) is a ground electrode and is placed on the right side, between the lower two ribs at the right abdomen. The first ICG measuring electrode (V1) is placed at the top end of the sternum, between the tips of the collar bones. The second ICG measuring electrode is placed at the xiphoid complex of the sternum, where the ribs meet. The two current electrodes are placed on the back: I- on the spine over the cervical vertebra C4, at least 3 cm (1 in) above the ICG measuring elec-trode V-, and I+ between thoracic vertebrae T8 and T9 on the spine, at least 3 cm (1") below the ICG measuring elec-trode V2. The ICG electrode placement takes into account that the largest part of the left ventricle driven change in thorax impedance is captured by the column between the suprasternal notch and the processus xiphoideus.
<img alt="Figure 2" fo:content-width="5in" fo:src="/files/ftp_upload/50073/50073fig2highres.jpg" src="/files/ftp_upload/50073/50073fig2.jpg" /> 
 Figure 2. The typical settings used for a recording as displayed by the DAMS software after connecting to the VU-AMS5fs device. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/50073/50073fig2large.jpg" target="_blank"> Click here to view larger figure</a>.
<img alt="Figure 3" src="/files/ftp_upload/50073/50073fig3.jpg" fo:content-width="3.5in" fo:src="/files/ftp_upload/50073/50073fig3highres.jpg"/> 
 Figure 3. Cardiac autonomic nervous system measures in boys and girls, by posture. * indicates p &lt; 0.05 for one sample T-test on sex difference. # indicates p &lt; 0.05 for paired samples T-test on posture difference.

Watch this Scientific Journal Video about Measuring Cardiac Autonomic Nervous System ANS Activity in Children at JoVE.com

Measuring Cardiac Autonomic Nervous System ANS Activity in Children

Measurement of autonomic nervous system activity usually confines the researcher and participant to the laboratory, which may provide an intimidating environment to children. The VU University Ambulatory Monitoring System (VU-AMS) device can record cardiac autonomic control in any setting. The VU-AMS proved very amenable to testing in children.

Measuring Cardiac Autonomic Nervous System (ANS) Activity in Children

The autonomic nervous system (ANS) controls mainly automatic bodily functions that are engaged in homeostasis, like heart rate, digestion, respiratory ...

measuring-cardiac-autonomic-nervous-system-ans-activity-in-children

Universidad de Cartagena UDEC

Research

JoVE Journal

Medicine

20.8K Views.  Academic Medical Center - University of Amsterdam. Measurement of autonomic nervous system activity usually confines the researcher and participant to the laboratory, which may provide an intimidating environment to children. The VU University Ambulatory Monitoring System (VU-AMS) device can record cardiac autonomic control in any setting. The VU-AMS proved very amenable to testing in children.

Video: Measuring Cardiac Autonomic Nervous System ANS Activity in Children

Quantitative Autonomic Testing

Disorders associated with dysfunction of autonomic nervous system are quite common yet frequently unrecognized. Quantitative autonomic testing can be invaluable tool for evaluation of these disorders, both in clinic and research. There are number of autonomic tests, however, only few were validated clinically or are quantitative. Here, fully quantitative and clinically validated protocol for testing of autonomic functions is presented. As a bare minimum the clinical autonomic laboratory should have a tilt table, ECG monitor, continuous noninvasive blood pressure monitor, respiratory monitor and a mean for evaluation of sudomotor domain. The software for recording and evaluation of autonomic tests is critical for correct evaluation of data. The presented protocol evaluates 3 major autonomic domains: cardiovagal, adrenergic and sudomotor. The tests include deep breathing, Valsalva maneuver, head-up tilt, and quantitative sudomotor axon test (QSART). The severity and distribution of dysautonomia is quantitated using Composite Autonomic Severity Scores (CASS). Detailed protocol is provided highlighting essential aspects of testing with emphasis on proper data acquisition, obtaining the relevant parameters and unbiased evaluation of autonomic signals. The normative data and CASS algorithm for interpretation of results are provided as well.

Standardized, comprehensive and fully quantitative testing of autonomic functions is described. The autonomic tests consist of evaluation of all three major autonomic domains including cardiovagal, adrenergic and sudomotor. The severity and distribution of dysautonomia is quantitated using Composite Autonomic Severity Scores.

Disorders associated with dysfunction of autonomic nervous system are quite common yet frequently unrecognized. Quantitative autonomic testing can be ...

Psychophysiological Assessment of the Effectiveness of Emotion Regulation Strategies in Childhood

Effective regulation of emotion is one of the most important skills that develops in childhood. Research interest in this area is expanding, but empirical work has been limited by predominantly correlational investigations of children's skills. Relatedly, a key conceptual challenge for emotion scientists is to distinguish between emotion responding and emotion regulatory processes. This paper presents a novel method to address these conceptual and methodological issues in child samples. An experimental paradigm that assesses the effectiveness with which children regulate emotion is described. Children are randomly assigned to use specific emotion regulation strategies, negative emotions are elicited with film clips, and changes in subsequent psychophysiology index the extent to which emotion regulation is effective. Children are instructed to simply watch the emotion-eliciting film (control), distract themselves from negative emotions (cognitive distraction), or reframe the situation in a way that downplays the importance of the emotional event (cognitive reappraisal). Cardiac physiology, continuously acquired before and during the emotional task, serves as an objective measure of children's unfolding emotional responding while viewing evocative films. Key comparisons in patterns of obtained physiological reactivity are between the control and emotion regulation strategy conditions. Representative results from this approach are described, and discussion focuses on the contribution of this methodological approach to developmental science.

A detailed protocol for an experimental paradigm to assess the effectiveness with which children regulate emotion is described. Children are randomly assigned to use specific emotion regulation strategies, negative emotions are elicited with film clips, and changes in subsequent psychophysiology index the extent to which emotion regulation is effective.

Effective regulation of emotion is one of the most important skills that develops in childhood. Research interest in this area is expanding, but empirical ...

Behavior

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children

We present a protocol designed to measure the neural correlates of reward in children. The protocol allows researchers to measure both reward anticipation and processing. Its purpose is to create a reward task that is appropriate for young children with and without autism while controlling reward properties between two conditions: social and nonsocial. The current protocol allows for comparisons of brain activity between social and nonsocial reward conditions while keeping the reward itself identical between conditions. Using this protocol, we found evidence that neurotypical children demonstrate enhanced anticipatory brain activity during the social condition. Furthermore, we found that neurotypical children anticipate social reward more robustly than children with autism diagnoses. As the task uses snacks as a reward, it is most appropriate for young children. However, the protocol may be adapted for use with adolescent or adult populations if snacks are replaced by monetary incentives. The protocol is designed to measure electrophysiological events (event-related potentials), but it may be customized for use with eye-tracking or fMRI.

This protocol is designed to measure reward anticipation and processing in young children with and without autism. Specifically, the protocol is designed to study the neural correlates of reward during social and nonsocial conditions while controlling for reward between conditions.

We present a protocol designed to measure the neural correlates of reward in children. The protocol allows researchers to measure both reward anticipation ...

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions

The aim of this study was to generate a method for calculating heart rate variability (HRV) from electrocardiogram (ECG) waveforms. The waveforms were recorded by a HR monitor that participants (youth with cerebral palsy (CP)) wore during active video game (AVG) sessions. The AVG sessions were designed to promote physical activity and fitness (aerobic performance) in participants. The goal was to evaluate the feasibility of AVGs as a physical therapy (PT) intervention strategy. The maximum HR (mHR) was determined for each participant and the Target Heart Rate Zone (THRZ) was calculated for each of three exercise phases in the 20 min AVG session: (warm-up at 40-60% mHR, conditioning at 60-80% mHR, and cool down at 40-60% mHR). Each participant played three 20 min games during the AVG session. All games were played while sitting on a bench because many youth with CP cannot stand for extended periods of time. Each game condition differed with participants using hand icons only, hand and feet icons together or feet icons only to collect objects. The objective of the game (called KOLLECT) is to collect objects to gain points and avoid hazards to not lose points. Hazards were used in the warm-up and cool down phases only to promote slower, controlled movement to maintain HR in the target heart rate zone (THRZ). There were no hazards in the conditioning phase to promote higher levels and more intense physical activity. Analytic methods were used to generate HRV (selected time-domain and frequency-domain measures) from ECG data to examine aerobic workload. Recent applications of HRV indicate that short-term measurements (5 min bouts) are appropriate and that HRV biofeedback may help improve symptoms and the quality of life in a variety of health conditions. Although HR is a well-accepted clinical measure to examine aerobic performance and intensity in PT interventions, HRV may provide information of the autonomic system functions, recovery and adaptation during AVG sessions.

This protocol describes a method for calculating Heart Rate Variability (HRV) from electrocardiogram (ECG) waveforms. Waveforms from continuous heart rate (HR) recordings during active video game (AVG) sessions were used to measure the aerobic performance of youth with cerebral palsy (CP).

The aim of this study was to generate a method for calculating heart rate variability (HRV) from electrocardiogram (ECG) waveforms. The waveforms were ...

Measuring Cardiac Autonomic Nervous System (ANS) Activity in Toddlers - Resting and Developmental Challenges

The autonomic nervous system (ANS) consists of two branches, the parasympathetic and sympathetic nervous systems, and controls the function of internal organs (e.g., heart rate, respiration, digestion) and responds to everyday and adverse experiences 1. ANS measures in children have been found to be related to behavior problems, emotion regulation, and health 2-7. Therefore, understanding the factors that affect ANS development during early childhood is important. Both branches of the ANS affect young children&#8217;s cardiovascular responses to stimuli and have been measured noninvasively, via external monitoring equipment, using valid and reliable measures of physiological change 8-11. However, there are few studies of very young children with simultaneous measures of the parasympathetic and sympathetic nervous systems, which limits understanding of the integrated functioning of the two systems. In addition, the majority of existing studies of young children report on infants&#8217; resting ANS measures or their reactivity to commonly used mother-child interaction paradigms, and less is known about ANS reactivity to other challenging conditions. We present a study design and standardized protocol for a non-invasive and rapid assessment of cardiac autonomic control in 18 month old children. We describe methods for continuous monitoring of the parasympathetic and sympathetic branches of the ANS under resting and challenge conditions during a home or laboratory visit and provide descriptive findings from our sample of 140 ethnically diverse toddlers using validated equipment and scoring software. Results revealed that this protocol can produce a range of&#160;physiological responses to both resting and developmentally challenging conditions, as indicated by changes in heart rate and indices of parasympathetic and sympathetic activity. Individuals demonstrated&#160;variability in resting levels, responses to challenges, and challenge reactivity, which provides additional evidence that this protocol is useful for the examination of ANS individual differences for toddlers.

Measuring Cardiac Autonomic Nervous System ANS Activity in Toddlers - Resting and Developmental Challenges

We describe the methods for continuous monitoring of the autonomic nervous system under resting and challenge conditions with 18 month old children. Results revealed that this protocol can produce meaningful physiological responses in both branches of the autonomic nervous system and elicit significant individual variability in patterns of responses.

The autonomic nervous system (ANS) consists of two branches, the parasympathetic and sympathetic nervous systems, and controls the function of internal ...

Novel Approach for Simultaneous Recording of Renal Sympathetic Nerve Activity and Blood Pressure with Intravenous Infusion in Conscious, Unrestrained Mice.

Renal sympathetic nerves contribute significantly to both physiological and pathophysiological phenomena. Evaluating renal sympathetic nerve activity (RSNA) is of great interest in many areas of research such as chronic kidney disease, hypertension, heart failure, diabetes and obesity. Unequivocal assessment of the role of the sympathetic nervous system is thus imperative for proper interpretation of experimental results and understanding of disease processes. RSNA has been traditionally measured in anesthetized rodents, including mice. However, mice usually exhibit very low systemic blood pressure and hemodynamic instability for several hours during anesthesia and surgery. Meaningful interpretation of RSNA is confounded by this non-physiological state, given the intimate relationship between sympathetic nervous tone and cardiovascular status. To address this limitation of traditional approaches, we developed a new method for measuring RSNA in conscious, freely-moving mice. Mice were chronically instrumented with radio-telemeters for continuous monitoring of blood pressure as well as a jugular venous infusion catheter and custom-designed bipolar electrode for direct recording of RSNA. Following a 48-72 hour recovery period, survival rate was 100% and all mice behaved normally. At this time-point, RSNA was successfully recorded in 80% of mice, with viable signals acquired up to 4 and 5 days post-surgery in 70% and 50% of mice, respectively. Physiological blood pressures were recorded in all mice (116&plusmn;2 mmHg; n=10). Recorded RSNA increased with eating and grooming, as well-established in the literature. Furthermore, RSNA was validated by ganglionic blockade and modulation of blood pressure with pharmacological agents. Herein, an effective and manageable method for clear recording of RSNA in conscious, freely-moving mice is described.

Anesthetized mice exhibit non-physiological systemic blood pressure, which precludes meaningful assessment of autonomic tone given the intimate relationship between blood pressure and the autonomic nervous system. Thus, a novel method to simultaneously record renal sympathetic nerve activity and blood pressure with intravenous infusion in conscious mice is outlined.

Renal sympathetic nerves contribute significantly to both physiological and pathophysiological phenomena. Evaluating renal sympathetic nerve activity ...

Impact of Intracardiac Neurons on Cardiac Electrophysiology and Arrhythmogenesis in an Ex Vivo Langendorff System

Since its invention in the late 19th century, the Langendorff ex vivo heart perfusion system continues to be a relevant tool for studying a broad spectrum of physiological, biochemical, morphological, and pharmacological parameters in centrally denervated hearts. Here, we describe a setup for the modulation of the intracardiac autonomic nervous system and the assessment of its influence on basic electrophysiology, arrhythmogenesis, and cyclic adenosine monophosphate (cAMP) dynamics. The intracardiac autonomic nervous system is modulated by the mechanical dissection of atrial fat pads-in which murine ganglia are located mainly&#8212;or by the usage of global as well as targeted pharmacological interventions. An octapolar electrophysiological catheter is introduced into the right atrium and the right ventricle, and epicardial-placed multi-electrode arrays (MEA) for high-resolution mapping are used to determine cardiac electrophysiology and arrhythmogenesis. F&#246;rster resonance energy transfer (FRET) imaging is performed for the real-time monitoring of cAMP levels in different cardiac regions. Neuromorphology is studied by means of antibody-based staining of whole hearts using neuronal markers to guide the identification and modulation of specific targets of the intracardiac autonomic nervous system in the performed studies. The ex vivo Langendorff setup allows for a high number of reproducible experiments in a short time. Nevertheless, the partly open nature of the setup (e.g., during MEA measurements) makes constant temperature control difficult and should be kept to a minimum. This described method makes it possible to analyze and modulate the intracardiac autonomic nervous system in decentralized hearts.

Impact of Intracardiac Neurons on Cardiac Electrophysiology and Arrhythmogenesis in an Ex Vivo Langendorff System

Here, we present a protocol for the modulation of the intracardiac autonomic nervous system and the assessment of its influence on basic electrophysiology, arrhythmogenesis, and cAMP dynamics using an ex vivo Langendorff setup.

Since its invention in the late 19th century, the Langendorff ex vivo heart perfusion system continues to be a relevant tool for studying a broad spectrum ...

Autonomic Function Following Concussion in Youth Athletes: An Exploration of Heart Rate Variability Using 24-hour Recording Methodology

Participation in organized sports makes a significant contribution to youth development, but places youth at a higher risk for sustaining a concussion. To date, return-to-activity decision-making has been anchored in the monitoring of self-reported concussion symptoms and neurocognitive testing. However, multi-modal assessments that corroborate objective physiological measures with traditional subjective symptom reporting are needed and can be valuable. Heart rate variability (HRV) is a non-invasive physiological indicator of the autonomic nervous system, capturing the reciprocal interplay between the sympathetic and parasympathetic nervous systems. There is a dearth of literature exploring the effect of concussion on HRV in youth athletes, and developmental differences preclude the application of adult findings to a pediatric population. Further, the current state of HRV methodology has primarily included short-term (5-15 min) recordings, by using resting state or short-term physical exertion testing to elucidate changes following concussion. The novelty in utilizing a 24 h&#160;recording methodology is that it has the potential to capture natural variation in autonomic function, directly related to the activities a youth athlete performs on a regular basis. Within a prospective, longitudinal research setting, this novel approach to quantifying autonomic function can provide important information regarding the recovery trajectory, alongside traditional self-report symptom measures. Our objectives regarding a 24 h recording methodology were to (1) evaluate the physiological effects of a concussion in youth athletes, and (2) describe the trajectory of physiological change, while considering the resolution of self-reported post-concussion symptoms. To achieve these objectives, non-invasive sensor technology was implemented. The raw beat-to-beat time intervals captured can be transformed to derive time domain and frequency domain measures, which reflect an individual&#39;s ability to adapt and be flexible to their ever-changing environment. By using non-invasive heart rate technology, autonomic function can be quantified outside of a traditional controlled research setting.

We demonstrate a 24 h heart rate recording methodology to evaluate the influence of concussion across the recovery trajectory in youth athletes, within an ecologically valid context.

Participation in organized sports makes a significant contribution to youth development, but places youth at a higher risk for sustaining a concussion. To ...

Microelectrode Array Recording of Sinoatrial Node Firing Rate to Identify Intrinsic Cardiac Pacemaking Defects in Mice

The sinoatrial node (SAN), located in the right atrium, contains the pacemaker cells of the heart, and dysfunction of this region can cause tachycardia or bradycardia. Reliable identification of cardiac pacemaking defects requires the measurement of intrinsic heart rates by largely preventing the influence of the autonomic nervous system, which can mask rate deficits. Traditional methods to analyze intrinsic cardiac pacemaker function include drug-induced autonomic blockade to measure in vivo heart rates, isolated heart recordings to measure intrinsic heart rates, and sinoatrial strip or single-cell patch-clamp recordings of sinoatrial pacemaker cells to measure spontaneous action potential firing rates. However, these more traditional techniques can be technically challenging and difficult to perform. Here, we present a new methodology to measure intrinsic cardiac firing rate by performing microelectrode array (MEA) recordings of whole-mount sinoatrial node preparations from mice. MEAs are composed of multiple microelectrodes arranged in a grid-like pattern for recording in vitro extracellular field potentials. The method described herein has the combined advantage of being relatively faster, simpler, and more precise than previous approaches for recording intrinsic heart rates, while also allowing easy pharmacological interrogation.

This protocol aims to describe a new methodology to measure intrinsic cardiac firing rate using microelectrode array recording of the whole sinoatrial node tissue to identify pacemaking defects in mice. Pharmacological agents can also be introduced in this method to study their effects on intrinsic pacemaking.

The sinoatrial node (SAN), located in the right atrium, contains the pacemaker cells of the heart, and dysfunction of this region can cause tachycardia or ...

Physiological Correlates of Emotion Recognition

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212;University of Southern California
The autonomic nervous system (ANS) controls the activity of the body's internal organs and regulates changes in their activity depending on the current environment. The vagus nerve, which innervates many of the internal organs, is an important part of the system. When our brain senses danger, vagal tone is inhibited, leading to a set of changes in the body designed to make us more prepared to fight or flee; for example, our heart rate increases, our pupils dilate, and we breath more quickly. Conversely, when the vagal system is activated, these physiological responses are inhibited, leading to a calmer state. The vagus nerve, then, acts as a kind of "brake" on our arousal. One interesting consequence of this calmer state is that it tends to promote social interaction-when we are not tensed and afraid of our immediate environment we are instead receptive to interacting with others. Poor functioning of this regulatory mechanism, therefore, may be associated with difficulties in social behavior.
One index of autonomic regulation is heart rate variability (HRV). HRV is a measure of how much the gap between one beat and the next varies over time. High HRV means there are continual fluctuations in the heart rate over time, a reflection of successful autonomic regulation. Low HRV means there is consistency of the heart rate over time, a condition associated with poor autonomic regulation. 
In this study we will test the hypothesis that increased HRV is associated with more accurate categorization of emotional stimuli.1,2 Following a study by Park et al., we will measure HRV and test its association on a task that measures skill at perceiving facial emotions.3

Correlating Heart Rate Variability with Emotion Recognition

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212;University of Southern California
The autonomic nervous system (ANS) controls the ...

Measuring Cardiac Autonomic Nervous System (ANS) Activity in Children

Summary

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Chapters in this video

Quantitative Autonomic Testing

Psychophysiological Assessment of the Effectiveness of Emotion Regulation Strategies in Childhood

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions

Measuring Cardiac Autonomic Nervous System (ANS) Activity in Toddlers - Resting and Developmental Challenges

Novel Approach for Simultaneous Recording of Renal Sympathetic Nerve Activity and Blood Pressure with Intravenous Infusion in Conscious, Unrestrained Mice.

Impact of Intracardiac Neurons on Cardiac Electrophysiology and Arrhythmogenesis in an Ex Vivo Langendorff System

Autonomic Function Following Concussion in Youth Athletes: An Exploration of Heart Rate Variability Using 24-hour Recording Methodology

Microelectrode Array Recording of Sinoatrial Node Firing Rate to Identify Intrinsic Cardiac Pacemaking Defects in Mice

Physiological Correlates of Emotion Recognition