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Adopting a music-to-heart rate
alignment strategy to measure
the impact of music and its tempo
on human heart rate
Edith van Dyck
Ghent University, Belgium
Ghent University, Belgium
Ghent University, Belgium
Ghent University, Belgium
Ghent University, Belgium
Ghent University, Belgium
Music is frequently used as a means of relaxation. Conversely, it is used as a means of arousal in sports
and exercise contexts. Previous research suggests that tempo is one of the most significant determinants
of music-related arousal and relaxation effects. Here we investigate the specific effect of music tempo, but
also more generally, the influence of music on human heart rate. We took the pulses of 32 participants
in silence, and then we played them non-vocal, ambient music at a tempo corresponding to their heart
rates. Finally, we played the same music again, either with the tempo increased or decreased by a factor
of 45%, 30%, or 15%; or maintaining the same tempo as in the first playing. Mixed-design ANOVA tests
revealed a significant increase in heart rate while listening to the music as compared with silence (p < .05).
Edith van Dyck, Department of Arts, Music and Theatre Sciences, IPEM, Ghent University, Technicum Blok 2,
Sint-Pietersnieuwstraat 41, 9000 Ghent, Belgium.
700706MSX0010.1177/1029864917700706Musicae Scientiaevan Dyck et al.
2 Musicae Scientiae
In addition, substantial decreases in tempo (-45% or -30%) could account for smaller subsequent heart
rate reductions (p < .05). We neither found links between increases in tempo (+15%, +30%, and +45%)
and heart rate change, nor small decreases (-15%). In addition, neither effects of gender, music training,
nor of musical preference were found. This indicates that during passive music listening, music exerts a
general arousal effect on human heart rate, which might be regulated by tempo. These results are a major
contribution to the way in which music may be used in everyday activities.
arousal, heart rate, music tempo, regulation, relaxation
How is music related to human heart rate? Particularly in music therapy, but also in sports and
exercise contexts, this question has puzzled many due to the implications of the answer. For
instance, the use of music has long been considered effective for enhancing exercise (Karageorghis
& Terry, 1997). Music reflects participants’ physiological arousal level (Berlyne, 1971; North &
Hargreaves, 1997), and it was established that, in everyday settings, people prefer to listen to
auditory stimuli with tempi in the range of the normal heart rate (i.e., 70–100 BPM) (Iwanaga,
1995a, 1995b). In moderate to high-intensity exercise, however, there is a preference for
medium- and fast-paced music (Karageorghis, Jones, & Low, 2006).
Listening to certain types of musical stimuli has also been shown to attenuate heart rate
after stressful tasks (Knight & Rickard, 2001). Slow music, for example classical or meditative
music, has often been demonstrated to initiate reductions in heart rate, resulting in greater
relaxation (Bernardi, Porta, & Sleight, 2006; Chlan, 1998; Hilz etal., 2014; Krumhansl, 1997;
Nomura, Yoshimura, & Kurosawa, 2003). Combined with evidence of decreases in blood pres-
sure, respiratory rate, and subjective anxiety levels (Hilz etal., 2014; Knight & Rickard, 2001;
Möckel etal., 1994), such findings support the claim that listening to certain music could serve
as an effective anxiolytic treatment, reducing stress levels and inducing relaxation. Based on
such results, it is apprehensible that the common use of music in therapeutic situations (White,
2000), cardiac care (Nilsson, 2011), and pre-surgical settings (Lee etal., 2012; Miluk-Kolasa,
Matejek, & Stupnicki, 1996) is effectively a non-invasive relaxation technique. Similarly, in the
sports and exercise domain, music is often employed for its relaxing properties, after intense
bouts of exercise, expediting recovery and preventing injuries and cardiac complications
(Karageorghis, 2015). Conversely, regarding arousal effects, research has also shown links
between the perception of certain aspects of musical stimuli and increases in cardiovascular
parameters (e.g., Lingham & Theorell, 2009). For instance, heart rate has been shown to
increase in association with crescendi and simple rhythmic structures (Bernardi et al., 2009;
Bernardi etal., 2006; Iwanaga, Kobayashi, & Kawasaki, 2005). Findings such as these are in
line with entrainment theory, substantiating the propensity of bodily pulses to entrain to musi-
cal rhythms without conscious effort (Thaut, 2008). Besides the effects of music itself, the
introduction of pauses between musical excerpts has been shown to exert an influence on
human heart rate: sudden silences demonstrably result in decreased pulse (Bernardi et al.,
Tempo has often been considered to be one of the most significant determinants of audio-
related effects on human heart rate (Bernardi etal., 2006; da Silva etal., 2014; Iwanaga etal.,
2005; Steelman, 1991; White & Shaw, 1991). Using audible clicks generated in a loudspeaker,
Bason and Celler (1972) indicated that the heart behaves as an oscillator whose period can be
varied over a certain range. Previous research also indicates that passive listening to music
van Dyck et al. 3
accelerates heart rate in proportion to the tempo of the rhythm (Bernardi etal., 2009; Bernardi
et al., 2006; Chlan, 1998; Iwanaga etal., 2005; Krumhansl, 1997; Nomura et al., 2003).
However, in the literature on human heart rate, the effect of musical tempo has rarely been a
specific focus for rigorous study. Some previous studies used only a single musical stimulus
(Knight & Rickard, 2001), thus preventing comparison between different tempi. Other studies
have used arrays of musical excerpts: the effects of stimuli with different tempi have been com-
pared across a range of music styles (such as raga, classical, dodecaphonic, rap, and techno
[Bernardi etal., 2006]; or classical, New Age, country western, religious, and easy listening
[Chlan, 1998]); and across different emotional loadings, for instance sad, fearful, happy, and
tense (Krumhansl, 1997), sedative versus excitative (Iwanaga etal., 2005) or relaxing and
aggressive (Hilz etal., 2014). In previous research, tempi have not usually been varied system-
atically, and musical stimuli have either been compared with each other or with a silent condi-
tion. In the present study, the tempo was modified while other parameters remained constant.
As such, although earlier studies provide valuable indications regarding the topic at hand, they
do not discriminate between the effects of musical style, tempo, other musical features, or
merely the introduction of the musical stimulus itself.
In the current study, the aim is to investigate the link between musical tempo and human
heart rate, adopting an experimental design that offers tight control over the relevant variables,
in order to enable better-substantiated conclusions. In addition, musical tempo is not selected
at random, but is manipulated in order to distinguish experimental conditions. By comparison,
as compared with stimuli with fixed slow or fast tempi, previous research shows greater cardiac
response to auditory stimuli that were initially entrained with participants’ heart rates and
subsequently played one beat per minute slower (Saperston, 1995). A comparable approach
was employed in a pilot study with six male participants by Nomura etal. (2003). Initially,
music was played three times as fast as the subjects’ heart rates, which had been measured prior
to the start of the music; after this the music was repeated, either 10% faster or slower than
previously. Results indicated significantly higher average heart rates in the fast condition than
in the slow. Similarly, in the current study, the starting tempo of the music is derived from the
heart rate of the participants themselves, reflecting their physiological arousal levels, and as
such enabling the investigation of possible entrainment effects. Taking the participants’ heart
rate as 100%, tempi were adjusted systematically (by 15%, 30%, or 45%) enabling comparison
of the impact of different extents of increase and decrease.
Possible confounding effects of: familiarity with the stimuli (Fontaine & Schwalm, 1979),
music preference (Bunt, 1994; Davis & Thaut, 1989), music training (Bernardi et al.,
2006), music style (Bernardi etal., 2006; Chlan, 1998), spectral features (Gingras, Marin, &
Fitch, 2014), age of the participants (Hilz et al., 2014), time of day (Piccione, Giannetto,
Assenza, Casella, & Caola, 2009), and use of chemical substances such as coffee, cigarettes,
and alcohol (Mahmud & Feely, 2003; Whitsett, Manion, & Christensen, 1984) were controlled
for and/or tested. Although gender was not expected to have an influence on the relationship
between heart rate and musical tempo (Knight & Rickard, 2001), its possible effects were exam-
ined, because some entrainment studies reported superior music-to-movement coordination
results for females than for males (Priest, Karageorghis, & Sharp, 2004; Van Dyck etal., 2015).
Adopting the methodology described above, the goal for this study is to identify possible
arousal or relaxation effects of music tempo on human heart rate in a passive listening condi-
tion. Alongside this, the holistic impact of music is investigated: participants’ pulses are taken
during a period of quiet rest after which non-vocal, ambient music with a steady beat is played
at tempi corresponding to their heart rate. In subsequent iterations of the stimulus, the
initial tempo is decreased, increased, or maintained. In the context of earlier research, it is
4 Musicae Scientiae
hypothesized (i) that by comparison with silence, there is an increase in heart rate in music
listening conditions, and (ii) that passive listening to music influences heart rate in proportion
to musical tempo; slow tempi lead to decreases of heart rate, while fast tempi lead to increases.
To establish the proper sample size, a power analysis was conducted using G*Power 188.8.131.52
(Faul, Erdfelder, Lang, & Buchner, 2007). With an α level of .05 and a power of 1-β = .80 to
protect beta at four times the level of alpha (Cohen, 1988), based on an estimated low to moder-
ate effect size, it was indicated that around 30 participants would be required.
Thirty-two healthy participants (16 males), with an average age of 23.59 years (SD = 2.73),
ranging from 19 to 31 years of age, took part in the experiment. Roughly half of the partici-
pants (53.13%) had received music training (Pearson’s chi-square test revealed no signifi-
cant association between gender and music training, χ2(1) = 0.13, p = .72). Subjects were
asked not to smoke on the morning of the study, and to avoid the consumption of caffeine
and alcohol, in order to control for possible confounding effects on heart rate (Mahmud &
Feely, 2003; Whitsett etal., 1984). All participants signed a form to declare that they partici-
pated voluntarily; that they had received sufficient information regarding the tasks, the pro-
cedures, and the technologies used; that they had had the opportunity to ask questions; and
that they were aware of the fact that heart rate was measured, for scientific and educational
purposes only. The study was approved by the Ethics of the Faculty of Arts and Philosophy of
Ghent University, Belgium, and all procedures followed were in accordance with the state-
ments of the Declaration of Helsinki.
First, participants filled out a general questionnaire to assess gender, age, and musical training.
They were also asked if they had smoked or taken caffeine or alcohol before the start of the
experiment. None of them reported to have used any of these substances. Participants were
seated comfortably in a soundproof, secluded room and were equipped with Sennheiser HD60
headphones and a pulse sensor attached to their right index finger. A preferred volume level
was selected which could not be modified by the participants during the further course of the
experiment. They were instructed to “relax and listen to the music”. Prior to starting, the
researcher left the demarcated room, dimmed the lights, and began the experiment. All experi-
ments took place between 9.00 and 11.00 am in order to standardize the protocol.
The experiment began with 9 minutes of silence to enable the stabilization of the heart rate
(HR). Next, the first condition was introduced. In this condition, no music was played for 60
seconds (silent condition). In the last 45 seconds of the condition, the participant’s mean HR
(interbeat intervals or RRI, converted to BPM) was calculated and taken as a reference for the
tempo of the 60 seconds of music in the subsequent “heart rate-based music” (HRBM) condi-
tion. Finally, in the altered tempo (AT) condition the same musical stimulus was played, either
with the tempo modified, being increased or decreased by 45%, 30%, or 15%; or at the same
speed as in the HRBM condition. These three conditions were repeated seven times to ensure
van Dyck et al. 5
that all levels of tempo modification would occur (see Figure 1). In total, the data collection
phase of the experiment had a duration of 30 minutes.
The order of the tempo modifications was randomized for each participant, ensuring that no
order occurred more than once. At the end of the experiment, participants were asked to rate
their familiarity with and preference for the stimuli.
Heart rate measurements
A photoplethysmograph (PPG) was used to measure heart rate. A PPG consists of an optical
device that measures change in volume of arterial blood, generating a periodic voltage from
which the RR intervals (RRI) can be derived (Shelley & Shelley, 2001). During the experiment a
Pulse Sensor Amped was employed (http://pulsesensor.com). The sensor was attached to the
right index finger of each participant and an Arduino Uno microcontroller processed the result-
ing signal. The software running on the Arduino, provided with the sensor, was also used to
determine RRI. Subsequently, the raw data and the RRI were sent from the Arduino to a
MacBook over a serial-USB connection. On the laptop, the signal was visualized and the instan-
taneous HR, calculated from the RR intervals, was stored. Since the optical device was prone to
motion artefacts, the participants were instructed to remain relatively still. Should a partici-
pant move to the extent that an increase in HR was discovered, that participant’s condition was
removed for further analysis. The signal was monitored continuously during the experiment, to
Music database and selection
A normal human adult HR at rest ranges from 60–85 BPM (Palatini, 1999), so a music database
was created (see Table S1 in the Supplemental Material Online section), primarily consisting of
stimuli with tempi lying within that range. However, extra stimuli were added, enabling the
Figure 1. Experimental loop.
6 Musicae Scientiae
inclusion of participants with slightly higher or lower heart rates (e.g., trained athletes). All the
stimuli consisted of non-vocal, ambient music with a binary rhythmical structure and were pur-
chased from iTunes. They were chosen according to the following criteria: first, the music was
required to have a steady beat, which was verified using BeatRoot (Dixon, 2007). Second, the
tempi of the stimuli needs must be adjustable to increases and decreases up to 45% without
quality loss. Third, in order to control for familiarity, only stimuli that had made few or no appear-
ances in popular music charts were selected. Familiarity was also checked in a post-test showing
that participants were unfamiliar with 94% of the music. A different stimulus was selected for
each of the seven adaptation levels. Adobe Audition was used to cut off intros or outros in case
of the detection of unstable tempi in these sections of the music and ReplayGain was used to
normalize perceived loudness and minimize possible imbalances in sound pressure level (SPL).
To automate the experimental procedure, a script was developed using the Ruby program-
ming language (Flanagan & Matsumoto, 2008). It controlled (i) the transition from one condi-
tion to another, (ii) the presentation of the stimuli, (iii) the registration of HR measurements,
and (iv) the logging of events and data. For both the HRBM and the AT condition, the partici-
pant was presented with time-stretched music. A time-stretching algorithm enabled tempo
modification without affecting the pitch of the stimuli. Each stimulus was played for 60 sec-
onds. Therefore each audio excerpt had a required duration of at least 87 seconds (= 60
s+45%), to enable the 45% tempo increase condition. The time stretching itself was performed
in the two-second pause in between conditions with the command-line version of the Rubber
Band time stretcher. This time stretcher separates onsets from harmonic content in the spectral
domain in order to minimize audible artefacts (which is especially required for time-stretch fac-
tors of more than 15%). Time-stretch factors were minimized, as in each HRBM condition a
musical excerpt was selected with an initial tempo as close as possible to the detected HR. To
regulate the number of occurrences for each AT condition, a permutation of conditions was
determined beforehand and followed by the experimenter.
Effect of music
To check for differences in heart rate (HR) between the silent condition and the heart rate-
based music (HRBM) condition, a 2 × 2 × 2 mixed-design ANOVA with the condition (silent,
HRBM) as within-subjects factor and gender (male, female) and music training (no training,
training) as between-subjects factors was performed. The analysis revealed a significant main
effect of the condition, F(1, 22) = 8.44, p = .01, r = .53,1 showing that participants’ HR (BPM)
was significantly higher in the HRBM condition (M = 68.26, SE = 1.53) compared to the silent
condition (M = 65.45, SE = 1.09). There was neither a significant main effect of gender, F(1,
22) = 0.31, p = .59, r = .12, nor of musical training, F(1, 22) = 2.00, p = .17, r = .29. No
interaction effect was found between the condition and gender (see Figure 2), F(2, 44) = 3.01,
p = .10, r = .35, the condition and musical training, F(2, 44) = 0.52, p = .48, r = .15, or
between the condition, gender, and musical training, F(2, 44) = 0.50, p = .49, r = .15.
Effect of music tempo
Next, the effect of the different tempo modifications on participants’ HR was checked, by com-
parison between the HRBM condition and the altered tempo (AT) condition. For each adaptation
level, a 2 × 2 × 2 mixed-design ANOVA with the condition (HRBM, AT) as within-subjects factor
and gender (male, female) and musical training (no training, training) as between-subjects
van Dyck et al. 7
factors was performed. Only for adaptations of -45% and -30%, was a significant main effect of
the condition found (see Table 1 and Figure 3).
There was no main effect for gender or musical training at any of the adaptation levels, nor
were there any interaction effects between the condition and gender, between the condition and
music training, or between the condition, gender, and music training (see Table 2).
Effect of music preference
Regarding music preference, 26.34% of the stimuli received low ratings, 18.75% were given
medium ones, and 54.91% was regarded as highly preferred. To check for a possible effect of
preference, mean HR in the HRBM condition for music with low, medium, and high preference
Figure 2. A comparison of the HR during the silent vs. HRBM condition for females and males. Data
presented are mean ± 1 SE (N = 32).
Table 1. Results of the main effect of condition for each tempo adaptation level.
HRBM condition AT condition F P R
–45% 67.95 (1.59) 66.70 (1.55) 5.45 .03* .41
–30% 67.26 (1.55) 65.23 (1.46) 6.26 .02* .46
–15% 69.10 (1.58) 68.32 (1.49) 1.56 .22 .24
0% 66.53 (1.18) 66.87 (1.39) 0.51 .48 .16
+15% 66.95 (1.33) 67.25 (1.79) 0.09 .77 .05
+30% 67.07 (1.50) 67.69 (1.53) 0.73 .40 .18
+45% 67.91 (1.85) 68.73 (1.80) 0.32 .57 .11
Note. Mean HR values and standard errors (M (SE)) are reported, as well as test statistics (F), significance values (p)
(* significant main effect), and effect sizes (r).
8 Musicae Scientiae
Figure 3. A comparison of HR during the HRBM condition vs. AT condition for all adaptation levels. Data
presented are mean ± 1 SE (N = 32) (* significant main effect).
Table 2. Results of main (gender, musical background) and interaction (condition, gender, musical
–45% –30% –15% 0% +15% +30% +45%
F1.92 1.58 0.83 1.58 0.92 1.11 3.12
p (r) .18 (.26) .22 (.25) .37 (.18) .22 (.27) .35 (.18) .30 (.21) .09 (.32)
Condition × gender
F0.26 0.10 0.62 0.04 0.18 2.59 0.53
p (r) .61 (.10) .76 (.06) .44 (.16) .84 (.05) .68 (.08) .12 (.32) .47 (.14)
F0.96 2.02 1.50 2.60 3.02 1.27 1.90
p (r) .34 (.19) .22 (.28) .23 (.24) .12 (.34) .09 (.32) .30 (.27) .18 (.25)
Condition × music
F0.0004 0.13 0.22 1.26 1.88 0.41 1.00
p (r) .95 (.01) .73 (.07) .65 (.09) .28 (.24) .18 (.25) .53 (.13) .33 (.19)
Condition × gender
× music training
F0.91 0.53 3.71 0.99 1.17 0.41 0.37
p (r) .35 (.18) .47 (.15) .07 (.36) .33 (.22) .29 (.20) .53 (.13) .55 (.11)
Note. Test statistics (F), significance values (p), and effect sizes (r) are reported.
van Dyck et al. 9
scores were compared. A repeated-measures ANOVA revealed no significant effect of music
preference on HR, F(2, 24) = 2.047, p = .151, r = .38.
Here we investigated the effect of music tempo on human heart rate during a controlled passive
music listening task. Additionally, the effect of listening to music (by comparison to silence) on
heart rate was examined. With heart rate measurements of 32 participants, the experiment
showed that pulses increased significantly in the music condition compared to the silent one. By
comparison with the initial (HRBM) music condition, it was also shown that substantial
decreases of tempo (-45% and -30%) significantly reduced participants’ heart rates. However,
heart rate did not respond to less considerable drops (-15%) or increases (+15%, +30%, +45%)
in the tempo of the non-vocal, ambient stimuli. Factors such as gender, musical preference, or
training did not have significance for the results of the experiment.
Thus, overall, we observed an arousal effect caused by the music. In addition, a regulating
effect of music tempo was identified: slower tempi induced lower heart rates, but never drop-
ping below the initial heart rate, which was measured in silence. Our results concerning the
arousal effect of music as opposed to silence correspond with previous research. Bernardi etal.
(2006), for instance, found more evidence of relaxation during intermissions or pauses than in
musical conditions. In a study by Lingham and Theorell (2009), it was shown that self-selected
stimulating music resulted in heart rate increases (and increased emotional arousal), but also
that self-selected relaxing music induced small but nonetheless significant increases in heart
rate (alongside emotional arousal and calm).
It has been speculated that passive music listening induces arousal resulting from focused
attention, similar to the effect of reading silently (Bernardi et al., 2000; Haas, Distenfeld, &
Axen, 1986). In the case of silence, arousal is released and the subject is left in a state of relaxa-
tion. Also, in neuroscientific research it has been suggested that the initial autonomic and car-
diovascular responses to music reflect an arousal response. fMRI and PET studies have
demonstrated activation or deactivation of multiple brain regions during music stimulation,
including areas of central autonomic control (Spyer, 1999), such as the ventral medial prefron-
tal cortex, anterior cingulate cortex, insula, and amygdala, depending on the level of arousal,
which is in turn associated with a music excerpt (Altenmüller, Schurmann, Lim, & Parlitz;
Blood & Zatorre, 2001; Koelsch, Fritz, Cramon, Müller, & Friederici, 2006).
There was no additional arousal effect of increased music tempo, and only a regulatory
effect of substantial tempo decreases was found, whereas previous research has often indicated
that passive listening to music could modify heart rate proportionally to the tempo of the stim-
uli (Bernardi etal., 2009; Bernardi etal., 2006; Chlan, 1998; Iwanaga etal., 2005; Krumhansl,
1997). This is likely due to the methodological choices made in this particular study compared
to those made in past investigations. Previously, the impact of different musical stimuli was
examined in contrast to silence and to stimuli with unsystematically reduced or elevated tempo
ranges, simultaneously encompassing different music styles (Bernardi et al., 2006; Chlan,
1998; Hilz etal., 2014; Iwanaga etal., 2005; Krumhansl, 1997). In another example of previ-
ous research, tempo changes (increases/decreases of 10%) and music stimuli were controlled,
although without reference to the initial heart rate (Nomura etal., 2003). Thus in that study it
remained unclear whether arousal or relaxation mechanisms (or both) were responsible for the
10 Musicae Scientiae
By presenting a music stimulus only after a period of silence, and subsequently repeating the
very same music at adjusted tempi, we applied a novel approach here. Consequently, within a
given pair of stimuli all of the musical parameters remained constant: the tempo alone was
varied systematically, allowing us to draw conclusions about it exclusively. Most preceding
research has regarded only up to two conditions (silence and music or slow and fast music)
instead of three (silence, music, and music with an increased or decreased tempo), as was the
case here. Moreover, the current study confirmed that music listening induces arousal in and of
itself, likely to a greater extent than the arousal effect of tempo change. Therefore, rather than
being caused by the tempo of the music, it seems plausible that the arousal effects of fast music
(as observed by others), could be largely or even exclusively put down to the mere introduction
of a music stimulus after a period of silence (Roy, Mailhot, Gosselin, Paquette, & Peretz, 2009);
or to the regulatory effects of the contrast between fast and slow musical stimuli.
Thus, our results seem to contradict the idea of the relaxing influence of music listening on
heart rate. Although previous research has often supported this notion (e.g., Bernardi etal.,
2009; Bernardi et al., 2006; Chlan, 1998; Iwanaga et al., 2005; Nomura et al., 2003;
Saperston, 1995), others have disputed such an effect. Research by Zimny and Weidenfeller
(1969) did not detect any change in heart rate following listening to calm music, whereas
Lingham and Theorell (2009) revealed that not only listening to self-selected stimulating music
can increase heart rate, but that also the same applies to self-selected calm music. As discussed
above, that our results concerning the effects of music tempo on heart rate are inconsistent
with a number of previous studies can largely be traced back to methodological issues, such as
the disentangling of music and music tempo while controlling for other musical parameters.
However, they do not necessarily contradict the general belief that certain music can lessen
stress and anxiety (Lee, Henderson, & Shum, 2004; Szmedra & Bacharach, 1998; Trappe,
2012; White, 1999, 2000).
In therapeutic settings, music intervention is often employed to maximize the attempt to
promote comfort and relaxation, as well as to reduce or control distress. It should be noted that
relaxation might also concern other psychophysiological parameters; slow music, for instance,
has been shown to lead to decreases in blood pressure and respiratory rate (Hilz etal., 2014;
Knight & Rickard, 2001; Möckel etal., 1994). Furthermore, our findings apply to a passive lis-
tening setting, during which the participants were already in a relaxed state. Other contexts,
where psychophysiological properties are measured in more active situations (e.g., during exer-
cise or sports activities), might imply quite a different relationship between music and heart
rate. For instance, at any given level of physical exercise, music (particularly at faster tempi) has
been shown to lower the heart rate, as well as the perceived level of exertion, through its dis-
tracting effect (Szabo, Small, & Leigh, 1999). Also in other contexts where the initial heart rate
is substantially higher than when at rest (e.g., in a stressful situation), one might expect the
relaxing effects of music to be more pronounced.
Although we did not discover any relaxation effect of decreased tempo, we did find that sub-
stantial decreases in tempo regulated the arousal effect of the music. As described above, previ-
ous research indicated that slow music might induce relaxation in situations where the initial
measured heart rate is higher than in rest. Therefore, it is plausible that any effects observed in
a passive listening situation are comparatively reduced, because in rest, heart rates tend to be
low and therefore less susceptible to further decreases. As musical tempo has been shown to
affect respiratory rate, which could also be related to heart rate (Hilz etal., 2014; Knight &
Rickard, 2001; Möckel etal., 1994), the regulatory effect of reductions in tempo might also be
a function of lower respiration rates linked with heart rate decreases. In addition, since passive
music listening is believed to induce arousal on account of the focused attention that it inheres
van Dyck et al. 11
(Bernardi et al., 2000; Haas et al., 1986), music with a substantially slow tempo might be
rather uninteresting to listen to. As such, the focus of listeners’ attention might have drifted
away from the stimuli, resulting in a discontinuation of any implicit arousal effects.
The results of this study only apply to a certain tempo spectrum (tempo of heart rate in rest
-/+45%). However, deviation from this spectrum (especially when further increasing music
tempo, since larger decreases would generally result in rather unnatural sounding stimuli)
might yield different results. In order to test this in future research, different methodological
choices should be made, because there is a limit to the extent to which an audio excerpt can be
time stretched without adversely affecting the perceptible quality of the recording. In this study,
the quality of the musical stimuli was controlled to ensure that they were perceived to “sound
natural”, even after the implementation of large tempo decreases/increases. However, in most
cases, it is clear that excessive time stretching can pose a threat to ecological validity. Beyond
time stretching, other methodological choices might also differ in future research. However, in
controlling for other musical parameters, a notable advantage of this approach is that tonal
frequency is kept constant as the tempo increases/decreases. As such, the total energy level is
affected as little as possible. In order to further expand the tempo spectrum available to experi-
menters, whilst maintaining control over all of the musical parameters, electronically pro-
duced music tailored to the experiment would probably be most suitable, as it can tolerate
substantial time stretching.
In this particular study, a music-to-heart rate alignment strategy was implemented as a
baseline; individuals’ heart rates were taken in silence, and used as a reference for selecting the
tempo of the music in the first condition (Bason & Celler, 1972; Nomura etal., 2003; Saperston,
1995). As such, music tempo reflected their personal physiological arousal levels, and this has
been shown to be preferable to participants in other studies (Iwanaga, 1995a, 1995b;
Karageorghis etal., 2006). This alignment strategy is rooted in entrainment theory (Thaut,
2008), but it also diverts from it: heart rate and music tempo can be regarded as interacting
oscillating systems, set off with the same period, but unveiling a unidirectional propensity of
one of these systems to re-entrain to bidirectional deviations of the other. It should be noted
that this alignment strategy was only implemented at the start of the experiment in order to
select the tempo of the initial musical stimuli. Moreover, since heart rate increased significantly
after the introduction of these stimuli, no heart rate-to-music alignment was uncovered, indi-
cating that human heart rates do not entrain to musical beats.
Neither musical preference nor training was proven to impact participants’ heart rate, a
finding that is in line with previous cardiovascular research on music (Bernardi etal., 2006).
Also, the gender of the participants did not have a significant main effect. Yet, there was some
indication that arousal effects of music were more pronounced for female participants than for
male subjects. It has been suggested that gender-based differences in psychophysiological
responses to music could be influenced by hormonal status (Nater, Abbruzzese, Krebs, & Ehlert,
2006). However, since our results regarding this effect were not significant, and as there is very
little in the literature to describe gender differences between women and men regarding cardiac
autonomic responses to music, this is a matter of some speculation, which would benefit from
That heart rates did not respond to smaller drops in tempo might be put down to the rela-
tively high initial heart rate in the -15% adaptation level, as compared to that of other levels.
However, this is debatable, and was probably caused by chance (especially given the randomiza-
tion of the order in which excerpts were played). Conversely however, this raises the question of
whether a lower starting heart rate (such as those in the silent condition of the other adapta-
tion levels), might have been significantly impacted by tempo decreases of -15% as well. The
12 Musicae Scientiae
majority of the participants were presented with a -15% modification at a point when their
initial heart rate was relatively high, which was therefore succeeded by corresponding high
tempi, and thus conceivably cancelling out regulating effects. As such, possible effects of -15%
tempo drops might have been cancelled out. This issue could be further elaborated on in future
Furthermore, it would be interesting to know whether the observed effect is maintained over
longer time spans and if it can be replicated in older age groups. In the current study, the test
group consisted of healthy young adults. However, as arousal responses may change with age
(Tsai, Levenson, & Carstensen, 2000), different autonomic cardiovascular responses in young
and older healthy persons could occur (Hilz etal., 2014). Another point that would be interest-
ing to pursue further is whether different music styles (with fixed tempi) impact heart rate dif-
ferently. Here, a homogeneous dataset of ambient, non-vocal musical stimuli with low to no
appearances in popular music charts was employed in order to control for spectral features
(Gingras et al., 2014), music style (Bernardi et al., 2006; Chlan, 1998), and familiarity
(Fontaine & Schwalm, 1979). Yet, it should be taken into account that some of these items have
been shown to influence arousal ratings, and thus might also affect heart rate (e.g., spectral
flux, spectral entropy), while for others, a more direct link has already been demonstrated (e.g.,
familiar music and heart rate increases).
We presented evidence that when people listen passively to non-vocal, ambient music, their
heart rate increases, while subsequently slowing down music could regulate the arousal effect
of listening to music. In contrast to what has been suggested previously, musical tempo did not
enhance heart rate. These findings contribute to thinking about how we can use music in eve-
ryday activities, demonstrating an arousal effect of music and a regulatory effect of music
tempo. They also further expand the discussion concerning the therapeutic power of music.
Furthermore, these results are also valuable in the sports and exercise domain, as the ergogenic
and regulatory effects of music are exploited not only during, but also before and even after
Tables and figures/audio files with the index “S” are available as Supplemental Online Material, which
can be found attached to the online version of this article at http://msx.sagepub.com. Click on the hyper-
link “Supplemental material” to view the additional files. The authors acknowledge Ivan Schepers for
The authors acknowledge the Methusalem project, awarded by the Flemish Government, for funding this
1. To indicate effect size, r is provided (instead of η2) since Field (2009) advises reporting this indicator
of effect size for mixed-design ANOVA tests. It is calculated as rFdf
for small, medium and large effect sizes remain as usual (.10, .30, .50).
van Dyck et al. 13
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