Name: calculating heart rate variability from ecg data from youth with cerebral palsy during active video game sessions
Uploaded: 2019-06-05T13:00:00
Description: Watch this Scientific Journal Video about Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions at JoVE.com

The authors thank the participants and their families for their time and effort expended for participation in the study. As well, the authors acknowledge Dr. Yichuan Liu and Dr. Hasan Ayaz for their assistance with the timing calculation of the HR monitoring and Dr. Paul Diefenbach for development of the KOLLECT Active Video Gaming software. Funding for this work was provided by Coulter Foundation Grants #00006143 (O&#8217;Neil; Diefenbach, PIs) and #00008819 (O&#8217;Neil; Diefenbach, PIs).

&#160;&#160;Institutional Review Board approval was obtained. All youth provided written assent and parents provided consent prior to participation.
1.&#160;AVG data collection sessions
<ol>
	<li>The AVG game session
	<ol>
		<li>In this study, have youth with CP participate in an AVG session which is comprised of three 20 min games. See Table 5 for Youth Demographics. It was expected that a total of 30 games would be played; however, 29 games were completed because one subject only played 2 game...

<ol>
	<li>Winter, S., Autry, A., Boyle, C., Yeargin-Allsopp, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trends+in+the+prevalence+of+cerebral+palsy+in+a+population-based+study.">Trends in the prevalence of cerebral palsy in a population-based study.</a> Pediatrics. 110 (6), 1220-1225 (2002).</li><li>Fowler, E., 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=Promotion+of+physical+fitness+and+prevention+of+secondary+conditions+for+children+with+cerebral+palsy:+Section+on+Pediatrics+Research+Summit+Proceedings.">Promotion of physical fitness and prevention of secondary conditions for children with cerebral palsy: Section on Pediatrics Research Summit Proceedings.</a> Physical Therapy. 87 (11), 1495-1510 (2007).</li><li>Rosenbaum, P., Paneth, N., Leviton, A., Goldstein, M., Bax, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+report:+The+definition+and+classification+of+cerebral+palsy:+April+2006.">A report: The definition and classification of cerebral palsy: April 2006.</a> Developmental Medicine &amp; 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A focus on autonomic cardiac response.</a> Disability and Rehabilitation: An International Multidisciplinary Journal. 36 (2), 155-162 (2014).</li><li>Muralikrishnan, K., Balakrishnan, B., Balasubramanian, K., Visnegarawla, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+the+effect+of+Isha+Yoga+on+cardiac+autonomic+nervous+system+using+short-term+heart+rate+variability.">Measurement of the effect of Isha Yoga on cardiac autonomic nervous system using short-term heart rate variability.</a> Journal of Ayurveda and Integrative Medicine. 33 (2), 279-283 (2012).</li><li>Yadav, R. K., Gupta, R., Deepak, K. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+pilot+study+on+short+term+heart+rate+variability+&amp;+its+correlation+with+disease+activity+in+Indian+patients+with+rheumatoid+arthritis.">A pilot study on short term heart rate variability &amp; its correlation with disease activity in Indian patients with rheumatoid arthritis.</a> Indian Journal of Medical Research. 136 (4), 593-598 (2012).</li><li>Thuraisingham, R. 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R., Naveen, K. V., Manjunath, N. K., Kumar, S., Subramanya, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Changes+in+autonomic+variables+following+two+meditative+states+described+in+yoga+texts.">Changes in autonomic variables following two meditative states described in yoga texts.</a> Journal of Alternative and Complementary Medicine. 19 (1), 35-42 (2013).</li><li>Ki&#269;merov&#225;, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Methods for Detection and Classification in ECG Analysis. Doctoral thesis. , (2009).</li><li>Murai, K., Hayashi, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+mental+workload+for+ship+handling+using+physiological+indices.">Evaluation of mental workload for ship handling using physiological indices.</a> , 604-608 (2009).</li><li>Taelman, J., Vandeput, S., Spaepen, A., Van Huffel, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+mental+stress+on+heart+rate+and+heart+rate+variability.">Influence of mental stress on heart rate and heart rate variability.</a> Heart. 29 (1), 1366-1369 (2009).</li><li>Durantin, G., Gagnon, J. F., Tremblay, S., Dehais, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+near+infrared+spectroscopy+and+heart+rate+variability+to+detect+mental+overload.">Using near infrared spectroscopy and heart rate variability to detect mental overload.</a> Behavioural Brain Research. 259, 16-23 (2014).</li><li>Buchheit, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+training+status+with+HR+measures:+Do+all+roads+lead+to+Rome?.">Monitoring training status with HR measures: Do all roads lead to Rome?.</a> Frontiers in Physiology. 5, (2014).</li><li>Achten, J., Jeukendrup, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Heart+rate+monitoring:+Applications+and+limitations.">Heart rate monitoring: Applications and limitations.</a> Sports Medicine. 33 (8), 517-538 (2012).</li><li>Amichai, T., Katz-Leurer, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Heart+rate+variability+with+cerebral+palsy:+Review+of+literature+and+meta-analysis.">Heart rate variability with cerebral palsy: Review of literature and meta-analysis.</a> NeuroRehabilitation. 35, 113-122 (2014).</li><li>Billman, G., Haikuri, H., Sacha, J., Trimmel, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+introduction+to+heart+rate+variability:+Methodological+considerations+and+clinical+applications.">An introduction to heart rate variability: Methodological considerations and clinical applications.</a> Frontiers in Physiology. 6, (2015).</li><li>Beffara, B., Bret, A., Vermeulen, N., Mermillod, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Resting+high+frequency+heart+rate+variability+selectively+predicts+cooperative+behavior.">Resting high frequency heart rate variability selectively predicts cooperative behavior.</a> Physiology &amp; Behavior. 164, 417-428 (2016).</li><li>Fogt, D., Cooper, P., Freeman, C., Kalns, J., Cooke, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Heart+rate+variability+to+assess+combat+readiness.">Heart rate variability to assess combat readiness.</a> Military Medicine. 174, 491-495 (2009).</li><li>Kerppers, I. 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Ten youth with CP participated in this study (mean + SD) [ age (yrs) = 15.53 &#177; 3.57 ; height (cm) 154.8 &#177; 12.6; weight (kg) 50.69 &#177; 11.1; body mass index (BMI) 50.46 &#177; 29.2; mHR 9 bpm) = 186.8 &#177; 12.4]. Please see Table 5 for patient demographics.
There are some considerations for use of HR monitors and the associated measures of HR and HRV which relate to modifications and troubleshooting. Two issues that are apparent, regardless of the technology empl...

Cerebral palsy (CP) is the most common physical disability of childhood1. CP is caused by a neurologic insult to the developing brain and is associated with motor impairments such as muscle weakness, spasticity, deconditioning, and decreased motor control and balance2,3. CP is a non-progressive condition but with age, children become less physically active and more sedentary compared to their peers with typical development (TD) mostly because of the increased demands of growth on their compromised neuromuscular and musculoskeletal systems4.
Youth with CP usually receive physical therapy (PT) services to improve functional mobility and promote physical activity and fitness (e.g. aerobic and muscular endurance)2. Oftentimes, there is limited access to PT services and community resources to achieve and sustain these PT goals5,6.Active video games (AVGs) may be a feasible strategy in activity-based PT interventions in clinic, home or community settings7,8. Commercial AVGs have limited flexibility to adapt game play and meet the specific needs and PT goals for youth with CP9. However, customized AVGs provide flexible gaming parameters to challenge youth with CP while promoting physical activity and fitness10.
Our team has developed a customized AVG (called KOLLECT) to examine youth exercise responses (e.g., physical activity and aerobic fitness). The game uses a motion sensor to track youth motion during game play. The goal of the game is to &#39;collect&#39; as many objects as possible for a high score and to avoid the hazards to avoid losing points. Objects may be collected with hand and/or feet icons as determined by the therapist in the flexible game parameters.
Designing activity-based PT interventions that dose physical activity intensity to promote aerobic fitness is critical for youth with CP11. Custom AVGs may be an effective strategy to dose intensity and engage youth in physical activity to promote fitness10. Heart rate (HR) monitors are often used in clinical PT practice to determine aerobic performance and activity intensity. Therefore, HR monitors will help determine feasibility of AVGs in dosing physical activity intensity to promote aerobic fitness9.&#160;ECG data generated from a HR monitor can be used to calculate heart rate variability (HRV). Analytic methods were used to generate HRV 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 conditions32,33,34. The application of short-term HRV measures is an appropriate means of assessing cardiovascular function during AVG sessions. Given that HRV is derived from the R-R interval of an ECG, we used selected time-domain and frequency-domain measures. Time-domain measure of HRV quantify the amount of variablility in the interbeat intervals which represents the time between successive heartbeats. We used the AVNN (average NN interval), RMSSD (root mean square of successive differences), SDNN (standard deviation of NN interval), NN50 (number of NN intervals &#62;50 ms) and PNN50 (percentage of NN intervals). Frequency domain measures estimate the distributionof absolute or relative power into possibly four frequency bands, we specifically addressed on two bands, low frequency (LF) power and high frequency (HF) power along with the LF/HF ratio. Although HR is a well-accepted clinical measure, HRV may be useful because it provides information about autonomic system function, recovery, adaptation, and provides an estimate of aerobic workload during an AVG session28.
The purpose of this study was to examine the feasibility of using AVG strategies to promote physical activity and fitness. A second purpose was to present the AVG data collection protocol and the methodology to calculate HRV from ECG data obtained via a HR monitor. These measures and this protocol may prove relevant to clinicians to monitor and dose PT intervention sessions.

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	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:352px;">BioHarness Bluetooth Module (Electronics sensor)&#160;</td>
			<td style="width:81px;">Zephyr</td>
			<td align="right" style="width:159px;">9800.0189</td>
			<td style="width:475px;">Detects Heart Rate, Resiration Rate, Posture, and Skin Temperature.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:352px;">BioHarness Chest Strap</td>
			<td style="width:81px;">Zephyr</td>
			<td style="width:159px;">9600.0189, 9600.0190</td>
			<td>Sizes Small XS-M, Large M-XL</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:352px;">BioHarness Charge Cradle &#38; USB Cable</td>
			<td style="width:81px;">Zephyr</td>
			<td align="right" style="width:159px;">9600.0257</td>
			<td>Used to Transfer Data from the Module to a Computer for Analysis.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:352px;">BioHarness Echo Gateway</td>
			<td style="width:81px;">Zephyr</td>
			<td align="right" style="width:159px;">9600.0254</td>
			<td>Allows for Realtime Viewing of Subject&#39;s Heart Rate.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:352px;">MATLAB R2016a</td>
			<td style="width:81px;">Mathworks</td>
			<td style="width:159px;">1.7.0_.60</td>
			<td>Used for All Programming.</td>
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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 method provides data for use in analyzing the effect that a newly developed method has on the subject&#39;s Heart Rate Variability (HRV). It does this by locating the R portion of the QRS waveform of a subject&#39;s ECG data, as shown in Figure 6, and by calculating various HRV values from it. If the HR monitor is making proper contact with the subject, the data will be uniform, substantially reducing the need for corrections (as seen in <strong class="x...

Watch this Scientific Journal Video about Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions at JoVE.com

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

Protocol provides an analytical method for measuring heart rate variability using electrocardiogram data to determine aerobic function. And with this, it will help us gain insight into the autonomic system functions within physical therapy protocols. This technique may be used to measure aerobic workload, demands and physical therapy strategies for youth with cerebral palsy.For example, when in physical therapy, we're doing techniques to promote health and fitness using active video games. Heart rate variability measures aerobic workload and provides cardiovascular function measures in patients and allows us to dose physical therapy at the level that meets and challenges the patient most appropriately. The methodology is useful in cardiac care and cardio rehabilitation.And with that, the calculations could be integrated into cardiac monitoring devices where they would provide heart rate variability from ECG or electrocardiograms as an outcome. The calculations can be challenging at first. But by creating a training video, we can aid clinicians and researchers in better utilizing these measures for evaluating the effectiveness of cardiac care.For active video game data collection sessions, select active video games with hand icons only, feet icons only, or both hand and feet icons for object collection to determine which game is more effective in promoting physical activity and fitness without being too demanding and causing early undue fatigue. To equip the youth subjects with cerebral palsy with a heart rate monitor, first plug a fully charged Bluetooth module into the data computer, be it the charge cradle, and open the config tool. Use a wet hand to moisten the conductive areas on the heart rate monitor chest strap.Place the Bluetooth module into the chest strap with the conductive surfaces of the module lined up with those of the chest strap. The monitor will click into place. Then apply the heart rate monitor chest strap and Bluetooth module to the subject with the module aligned with the left mid axillary line and the strap just under the pectoral muscles.Once properly positioned, tighten the device so that it will not move during the session but is not uncomfortable for the subject. Have the subject sit on a bench with their feet flat on the floor and with their knees and hips flexed to 90 degrees for postural support and stability. Plug the connector into the USB port of the computer that will be used to view the data and use the live mode tab to monitor the heart rate, respiratory rate and posture of the subject in real time.Then record the subject for a period of rest to obtain a baseline recording of the subject's heart rate before starting the first active video game for the subject. At the end of the gaming session, download the electrocardiogram data from the heart rate monitor and remove the strap from the subject. To calculate the heart rate variability from the electrocardiogram data, open MATLAB and organize the data into five-minute intervals to ensure comparable data between phases.Calculate the rest period as the five minutes prior to the game start and the recovery phase as the five minutes after the end of the cool down phase to perform R peak detection on the raw electrocardiogram signal. Once these times have been obtained, identify the location of the game phase of interest within the ECG file and select the five-minute section of interest. Calculate a threshold for peak detection based upon the average and standard deviation of the waveform.And along with the minimum height for the R peak, assign a minimum distance of 0.3 seconds between the peaks to minimize the detection of incorrect peaks around the desired R.Once the threshold has been set, run peakdetection. m to process the waveform and attempt to discern all of the R peaks for the inter beat interval and heart rate variability calculations. Generate a preliminary plot so that it can be reviewed for irregularities as illustrated.Many data sessions are fairly uniform and will therefore only require a few corrections. Some cases however are fairly messy and require more time to review and obtain the proper R locations. To correct these irregularities, manually edit the detection variable that contains the microvolt reading of the peak in column one and the location in the current game session in column two.In most cases, the proper R peaks can easily be found by zooming in to the problem location. Obtain the matrix of intervals ignoring any interval greater than 1.5 seconds and save these inter beat intervals for further calculations in the verification of data. Then use these intervals to calculate the root mean square of the successive differences.Prior to calculating heart rate variability measures, open a waveform to check for correct peak detection. Use the magnifying tool to select an area of the plot that is output zooming in or out if the window is not easily inspected visually. Use the data tips tool to find the location of the missed peak as necessary.For peak correction, locate the detection variable and double-click in the workspace to correct the incorrectly detected or missing peaks. If the point is a false positive, remove the point from the array and change the values of any incorrectly marked peaks adjacent to unmarked peaks to that of the unmarked peaks. Then to obtain heart rate variability measure calculations, run hrvmeasures.m and open the heart rate variability variable from the workspace window. This method provides data for analyzing the effect that the newly developed active video gaming method has on the heart rate variability of a specific subject by locating the R portion of the QRS waveform in the subject's ECG data. If the heart rate monitor makes proper contact with the subject, the data will be uniform substantially reducing the need for corrections.If the data are sufficiently variable due to momentary changes in the heart rate monitor skin contact, the initial analysis may incorrectly label the peaks as indicated. Altering the threshold levels in the minimum time between the peaks can also help to clean up the detection values for the production and adjusted plot. It is important to pan through each waveform to ensure proper peak detection, remove false positives, and shift mislabeled peaks prior to calculating heart rate variability data.Other considerations and influences using heart rate variability measurements include physiological considerations, hydration status, and environmental influences. This method is useful in activity-based physical therapy interventions as in the past decade there's been a movement from disability-based interventions to more health promotion and fitness and this method allows us to measure fitness and function mobility. Before applying the heart rate monitor, you want to ensure that the skin is not irritated and that the device is in good repair to avoid skin abrasions.

Research

JoVE Journal

Behavior

Method for Simultaneous fMRI/EEG Data Collection during a Focused Attention Suggestion for Differential Thermal Sensation

In the present work, we demonstrate a method for concurrent collection of EEG/fMRI data. In our setup, EEG data are collected using a high-density ...

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

Simultaneous  EEG-fMRI allows the excellent temporal resolution of EEG to be combined with the  high spatial accuracy of fMRI. The data  from these two ...

Event-related Potentials During Target-response Tasks to Study Cognitive Processes of Upper Limb Use in Children with Unilateral Cerebral Palsy

Unilateral Cerebral Palsy (CP) is a neurodevelopmental disorder that is a very common cause of disability in childhood. It is characterized by unilateral ...

Reversible Cooling-induced Deactivations to Study Cortical Contributions to Obstacle Memory in the Walking Cat

On complex, naturalistic terrain, sensory information about an environmental obstacle can be used to rapidly adjust locomotor movements for avoidance. For ...

Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation

Stroke rehabilitation requires repetitive, intensive, goal-oriented therapy. Virtual reality (VR) has the potential to satisfy these requirements. ...

The (Spatial) Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

The memory game paradigm is a behavioral procedure to explore the relationship between language, spatial memory, and object knowledge. Using two different ...

Measuring Active and Passive Tameness Separately in Mice

Domesticated animals such as dogs and laboratory mice show a high level of tameness, which is important for humans to handle them easily. Tameness has two ...

Modified Blood Collection from Tail Veins of Non-anesthetized Mice with a Vacuum Blood Collection System and Eyeglass Magnifier

Blood sample collection is the basis of experimental animal research. It is of importance to obtain adequate blood samples for various research purposes. ...

Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback

The application of incongruent sensory signals that involves disrupted tactile feedback is rarely explored, specifically with the presence of vibrotactile ...

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

The need to understand trust in groups holistically has led to a surge in new approaches to measuring collective trust. However, this construct is often ...