Effect of Flute Musical Warm-up on Heart Rate



Effect of Flute Musical Warm-up on Heart Rate

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5 days a week for the past 7 school years, I have been a participant in some sort of band
class during school. During each class, each musician warms up for about 5 minutes ourselves
and another 10 minutes with the whole group, and with band being every day, I have figured I
have warmed up for about 18,900 minutes during my time in the band program. With this
information in mind, it is clear that warming up is an essential part of the musical performance. I
have already been able to witness these swings on my body like shortness of breath, and
exhaustion, so I sought to understand some of the less obvious effects. My goal of the
experiment, then, was to determine how my body’s physiology was affected by an instrument.
In my biology class we have discussed cellular respiration and how it related to the
human body. We learned that as cells preform living functions, they must undergo the process of
cellular respiration, which requires the intake of oxygen and yields carbon dioxide as a product.
As humans use their muscles, muscle cells undergo cellular respiration, which breaks glucose
into carbon dioxide and water, and allows oxygen into the blood stream. As a result, the heart
must work harder to pump oxygenated blood throughout the whole body, which causes an
increase in humans’ heart rates. While I had never considered warming up to be strenuous, I
figured it had to have some effect on my heart rate. With this consideration, I refined the focus of
my investigation to how warming up with scales affected a players’ heart rates.
Research Question:

How does warming up to the B flat scale on flute for increasing increments of time (0,
20, 40, 60, 80 seconds) affect the heart rate of female flutists 16 to 17 years old.
If the flutist has to play for increasing amounts of time, then their heart rates will increase
as the number of seconds increases because more strain will be placed on their lungs and
muscles, causing muscle cells to undergo cellular respiration, and their hearts will this have to
beat faster to replenish oxygen through their bodies.
Independent: Seconds spent warming up at one time (0, 20, 40, 60, 80 seconds)
Dependent: Heart rate of participants in beats per minute (bpm +
−2 bpm)
Control Variables:
Control Variables Manner in which CV was controlled
Strength of player All participants were females aged 16-17, active member
of the band program, and had between 3 to 5 years of
training and experience.
Instrument All of the participants were flutists, and they each used a
Gemeinhardt brand flute.
Warm-up Music Each participant played their B Flat scale, one octave on
flute for the duration of each period of time they had to
Music Tempo All of the participants played at the same tempo, which
was signaled by a metronome app from my phone. Each
participant played at quarter note equals 115.
Individual heart rate at the
beginning of each set of time
Each participant was allowed sufficient break time in
between trials to allow their heart to return to resting level.
Miscellaneous All data was taken on the same day to ensure that other
factors, such as sleep and nutrition, did not change each
individual between sets of playing.
• Five Gemeinhardt beginner flutes
• iPhone 6 stopwatch function
• Pencil
• Paper
• iPhone 6 calculator function
• iPhone 6 Metronome App
1. Each participant found their pulse on their neck or wrists and counted the total number of
heartbeats in a 30 seconds period.
2. Using the calculator on my phone, I multiplied each participant’s number of heartbeats by
two to calculate their resting heart rate in beats per minute (bpm +
−2 bpm) and recoded
the values.
3. All participants simultaneously began playing the B flat scale on a flute, at the same
tempo, which I directed them to begin by saying “Go”.
4. Immediately after finishing their warm up, I started the stopwatch for 30 seconds and the
participants again counted how many times their heart beat in the 30 second period.
5. Again using the calculator on my phone, I multiplied each participant’s number of
heartbeats by two to calculate their resting heart rate in beats per minute (bpm +
−2 bpm)
and recoded the values.
6. Participants were given a three-minute resting period so their heart rates could return to
resting level.
7. After the resting period, each participant counted the number of times their heart beat in a
thirty second period.
8. I multiplied each number by two to verify that the participants’ heart rate had returned to
resting level.
9. I repeated the same process outlines in steps 3 through 8 for the other four increments of
time (20, 40, 60, 80 seconds).
Because each participant was a member of the band program they knew how to properly
regulate their breathing, and knew when to breath in order to play for extended periods of time.
However, before conducting the experiment, I obtained verbal consent from all of my
participants, informing them of the possible risks of the experiment. The participants were made
aware that they were not in any way obligated to participate and that they were allowed to
withdraw from the experiment at any time if they wished to do so.
Heart Rates (bpm +
−2 bpm) of 16 to 17 year old Female Flutist Players after Increasing
Increments of Time
0 seconds 20 seconds 40 seconds 60 seconds 80 seconds
Flute #1 94bpm 70bpm 88bpm 72bpm 90bpm
Flute #2 90bpm 94bpm 72bpm 128bpm 110bpm
Flute #3 92bpm 84bpm 77bpm 110bpm 99bpm
Flute #4 95bpm 90bpm 81bpm 117bpm 105bpm
Flute #5 91bpm 88bpm 83bpm 98bpm 107bpm
Above is a table displaying the raw data collected. Units are in beats per minute (bpm +
In processing this data, I chose to find the average of the five participants’ heart rates
after each increment of time played, and the standard deviation of each set from its respective
values. To calculate average, I added all the values from a give degree of the independent value
and divided the value by 5, the total number of participants. For example, to calculate the resting
heart rate of the five participants, I added, 94+90+92+95+91 which equals 462, and then divided
that by 5 to find the average resting heart rate which was 92.4. To calculate standard deviation, I
used the following formula:
Where o represents standard deviation
X is the value in the set
U is the mean of the data set
And N is the number of values in the set
An example of this calculation would be the following:
94+90+92+95+91/ 5= 92.4 for the average, then the variance comes out to be 4.3, after you
subtract the difference between each number and square it and then add together, which we then
square root the variance total in order to reach the standard deviation of 1.816.
Average Heart Rates (bpm +
−2 bpm) of 16 to 17 year old Female Flutist Players after Increasing
Increments of Time
Number of Seconds Played Average Heart Rate of
Participants (bpm +
−2 bpm)
Standard Deviation for
Data Set (bpm +
−2 bpm)
0 92.4 1.816
20 85.2 9.23
40 80.2 6.058
60 105 21.42
80 102.2 7.9183
The above tables show processed values of the data collected in the investigation. Note
that the units are still in bpm +
−2 bpm. The data seems to reflect a general upwards trend in heart
rate as increment of time increases; however, a clearer representation of this data will be needed
to accurately determine whether the perceived increased in heart rate is statistically significant.
I noticed that none of my participants truly struggled with playing for each different
duration of time. Each participant all started the same, but differentiated as to when they needed
to take their next breath to continue playing. This could have possibly lead to disparities between
Average Heart Rates (bpm +
−2 bpm) of 16 to 17 year old Female Flutist Players after Increasing
Increments of Time
The above graph visually represents the processed data presented previously. The average
values of each data set are represented by columns, while the error bars depict one standard
deviation above and below the aver on each column.
To the untrained eye, it appears that, as the number of seconds playing increases by the
participant increases the heart rate changes moderately, however not always increasing. The
average heart rate of participant trends up and down as the increments of time increases, though
not at the same proportions. Upon statistical analysis, however, this conclusion becomes less
sound. To determine whether the findings of this experiment were statistically significant, I
included error bars on each column that extended one standard deviation above and below. When
error bars are included the increases in heart rate between each subsequent increment of time
become less convincing. For example, while the average heart rate between 20 seconds and 40
seconds decreases their standard deviation levels appear to be nearly the same as represented by
the error bars. However, on 20 second interval there is nearly a 20+ bpm difference in the top of
the standard deviation and the actual average, which is also visible in the 40 second interval.
These findings refute my hypothesis to an extent- they suggest significant difference in heart rate
achieved between each increment of time however, between 0 and 20, and 20 and 40, the heart
92.4 85.2 80.2
105 102.2
0 20 40 60 80
Heart Rate
Incements of seocnds played
rate drops from the average resting. But between 40 and 60, the average heart rate increases, and
between 60 and 80 the average heart rate remains nearly the same. It is possible that the change
in the resting heart rate drop lower after the 20 seconds and then again after the 40 seconds
because the participants are experienced players, so they felt very relaxed as they have been
playing the scale I had asked them to play for many years now. The jump up in heartrate average
between the resting heart rate and 60 seconds, as well as the jump between resting and 80
seconds could possibly be due to participants just wanting to get the trial over with, or personal
outside anxieties that were beyond my control. Each participant all started the same, but
differentiated as to when they needed to take their next breath to continue playing. This could
have possibly lead to disparities between heartrates. With this in mind, it can be determined that
there is no statistical significance in the change of heart rate between increments of time.
Evaluating Procedures:
A major limitation of my experiment design was an inevitable disparity in the amount of
rigorous training each flutist had. Despite my efforts to keep all of the participants in the same
bracket of experience, there was a considerable difference in heart rate between each participant
after each set. The drastic difference between indicial participants’ heart rate at any given
increment could have been caused by differences in each participants’ training, for example if
they learned by teaching themselves they may not be as technically advanced as someone who
took private lessons. Another flaw in my lab design was human error created by each participant
by each participant measuring their own pulse. While a clear-cut better way to measure their
heart rate wasn’t readily available, there was nonetheless a considerable amount of human error
involved when calculating the heart rate. My materials, and my procedural steps, were designed
with the goal of keeping the value between participants as close as possible. Overall the
procedure itself was not incredibly flawed- it was the innate differences in participants that
caused problems with my results. My experiment was also limited in that I only had 5
participants so my averages were not as accurate as to if I had a much larger group of people.
During the breaks in between each time, I let the girls walk, sit, and use their phones in the small
room we were in, and this could of lead to the disparities in heart rate as well.
Improving the Investigation
My goal of keeping the group of participants small ultimately limited my results, because
of the large disparities between members of a small group led to high standard deviation. To
improve my experiment, I could widen the range of experience and mass of participants, giving
me more participants thus more data to work with which hopefully would lead to a smaller
standard deviation and more reliable results. In repeating this experiment in the future I would
also take the heartrate of each participant myself, or use a heartrate monitor to have a more
accurate reading of each participant’s heartrate. This would allow for much more accurate
averages and better data. I could also more closely monitor what they did in between each time,
during their break, to make sure they aren’t being overly active, like walking around or pacing so
that they did not skew their heartrate.


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