Regular heartbeat dynamics are associated with cardiac health

Transcription

1 Am J Physol - Regul Integr Comp Physol (1): R368-R372 Regular heartbeat dynamcs are assocated wth cardac health Drk Cysarz 1,2, Slke Lange 3, Peter F. Matthessen 1, Peter van Leeuwen 3 1 Char of Medcal Theory and Complementary Medcne, Unversty of Wtten/Herdecke, D Herdecke, Germany 2 Integrated Studes of Anthroposophc Medcne, D Wtten, Germany 3 Department of Bomagnetsm, Grönemeyer Insttute for Mcrotherapy, D Bochum, Germany Correspondng author: Drk Cysarz, PhD Char of Medcal Theory and Complementary Medcne Unversty of Wtten/Herdecke Gerhard-Kenle-Weg 4 D Herdecke, Germany Tel: Fax: Emal: d.cysarz@rhythmen.de

2 D. Cysarz et al. Regular heartbeat dynamcs s healthy 2 Abstract The human heartbeat seres s more varable and, hence, more complex n healthy subjects than n congestve heart falure (CHF) patents. However, lttle s known about the complexty of the heart rate varatons on a beat-to-beat bass. We present an analyss based on symbolc dynamcs that focuses on the dynamc features of such beat-to-beat varatons on a small tme scale. The sequence of acceleraton and deceleraton of 8 successve heartbeats s represented by a bnary sequence consstng of 1s and 0s. The regularty of such bnary sequences s quantfed usng Approxmate Entropy. Holter electrocardograms from 30 healthy subjects, 15 patents wth congestve heart falure (CHF) and ther surrogate data were analyzed wth respect to the regularty of such bnary sequences. The results of ths approach are compared to spectral analyss and Approxmate Entropy of heart rate varablty. Counter-ntutvely, healthy subjects show a large amount of regular beat-to-beat patterns n addton to a consderable amount of rregular beat-to-beat patterns. CHF patents lack the regular patterns observed n healthy subjects. Instead, they show a predomnance of one regular beat-to-beat pattern (alternaton of acceleraton and deceleraton) as well as some rregular beat-to-beat patterns smlar to the beatto-beat patterns observed n the surrogate data. In healthy subjects regular beat-to-beat patterns reflect the physologcal adaptaton to dfferent actvtes,.e. sympathetc modulaton, whereas rregular beat-to-beat-patterns may arse from parasympathetc modulaton. CHF patents show regular as well as rregular beat-to-beat patterns close to a purely erratc behavour ndcatng a largely reduced nfluence of the autonomc nervous system. In concluson, the analyss of short beat-to-beat patterns wth respect to regularty leads to a consderably ncrease of nformaton compared to spectral analyss or ApEn of heart rate varatons. Introducton On a neural bass dynamc features of the human cardac actvty are modfed by two dfferent nputs of the autonomc nervous system: sympathetc actvty ncreases heart rate and parasympathetc actvty lowers heart rate. Ths seems to be a smple antagonsm but n healthy subjects these competng branches are nfluenced by numerous dfferent nputs medatng many knds of stmul. Hence, the resultng tme seres of nterbeat ntervals s hghly non-statonary and complex (Fg. 1a). The analyss of such tme seres has revealed a reduced heart rate varablty (HRV) n patents wth cardac dsease such as e.g. congestve heart falure (CHF) (6). Lkewse, CHF patents show decreased fractal and chaotc features of heartbeat dynamcs (11, 15, 21). These fndngs and ther mplcatons wth respect to complexty are based on the analyss of the heartbeat seres contanng at least a hundred or more consecutve heartbeats, some methods even requre 10 3 or 10 4 consecutve heartbeats. Here, we nvestgate dynamc features of partcularly short beat-to-beat sequences n the order 10 consecutve heartbeats by means of symbolc dynamcs. At present, two dfferent approaches to derve symbolc dynamcs from a tme seres may be dstngushed. One approach uses local mean and standard devaton of the heart rate tme seres to create a symbolzed tme seres. E.g. a symbolc sequence may be created assgnng 1 to a heartbeat f the nstantaneous heart rate s near the average heart rate, assgnng 2 for heart rates consderably below the average heart rate, and assgnng 3 f the heart rate s consderably above the average heart rate (13, 16-18). The analyss of such symbolc sequences has proven useful to mprove the detecton of cardac patents at hgh rsk (16) or to characterze dynamc dfferences of slow and fast ventrcular tachycardas (17).

3 D. Cysarz et al. Regular heartbeat dynamcs s healthy 3 Recently, a smlar approach revealed a loss of complexty n cardac patents wth lfethreatenng arrhythmas before the onset of these arrhythmas (13). The analyss of ths knd of symbolc sequences led to the noton that the heart rate varatons are more complex n healthy subjects than n e.g. cardac patents. Ths noton s compatble wth the results from approaches that nvestgate complexty of physologc tme seres but do not use symbolc dynamcs, such as methods derved from chaos theory (7, 11, 15, 21). The other approach to derve symbolc dynamcs symbolzes the ncrease or decrease of the nstantaneous heart rate by two dfferent symbols. Hence, the local average heart rate or smlar quanttes of the tme seres under nvestgaton are not mportant for the creaton of the symbolc sequences. It has already been shown that n healthy subjects the average dynamcs of such short beat-to-beat sequences durng nght-tme sleep s more rregular,.e. more complex and less predctable, compared to heartbeat dynamcs durng wakng tme (8). Specfc short symbolc sequences appear durng nght-tme as a result of the modulaton of heartbeat varatons by respraton (respratory snus arrhythma) and s assocated wth cardorespratory synchronzaton (3, 4). Furthermore, the emergence of certan symbolc sequences on small tme scales seems to be an ndvdual characterstc feature. For nstance, both pathologcal states, CHF and atral fbrllaton show characterstc short dynamc patterns (25). Recently, a classfcaton of short symbolc sequences based on the acceleraton or deceleraton of heart rate usng muscal rhythm prncples has been developed (2). However, ths classfcaton dd not emphasze dynamc features of such symbolc sequences. Here, we focus on dynamc features of such short beat-to-beat seres from healthy subjects and patents wth CHF and ther respectve surrogate data. We wll show that ths knd of analyss reveals a fundamental dfference between short-scale heartbeat dynamcs n health and dsease. A comparson of the results of ths analyss wth the results obtaned from spectral analyss and Approxmate Entropy of HRV s used to exemplfy the augmentaton of nformaton made possble by the new method. Methods Subjects Heartbeat tme seres from thrty healthy subjects (15 female, average age: 29 ± 8 years) (9) and ffteen patents wth severe CHF (NYHA class III-IV; age range years; BIDMC congestve heart falure database taken from the Physonet-database; see (12)) were analyzed wth respect to heartbeat dynamcs on small tme scales. Holter ECGs of the healthy subjects were recorded wth Oxford FD3 sold-state memory recorders wth smultaneous R-peak detecton. They were about 24 hours n duraton. The maxmum samplng rate of 1024 Hz provded a temporal resoluton of the tmes of the R-peaks of 1 ms. The data were subsequently vsually examned wth the Oxford Excel software. After elmnaton of artfacts (<0.1% of all R-peaks) the tmes of the R-peaks and the beat annotatons were transferred to data fles. Data of the CHF group were recorded wth Del Mar Avoncs Model 445 Holter recorder. They were dgtzed wth a samplng rate of 250 Hz permttng a temporal resoluton of the R-peaks of 4 ms. The recordngs were about 20 hours n duraton. We reled on the nformaton provded n the Physonet database. The data n the database (tmes of the R-peaks and classfcaton of the heartbeats) were taken as provded and were nether nspected vsually nor corrected manually.

4 D. Cysarz et al. Regular heartbeat dynamcs s healthy 4 Constructon of symbolc sequences The seres of nterbeat ntervals RR ( = 1, K, N ) between successve R-peaks served as the bass for the calculatons. A bnary sequence S ( = 2, K, N ) was created usng the dfferences RR = RR RR 1 between successve nterbeat ntervals (Fg. 1c): 0, f RR 0, S = 1, f RR < 0. Hence, 0 symbolzes a deceleraton and 1 an acceleraton of the heart rate. Subsequently, the probablty of the appearance of the 17 pattern sets n the symbolc seres S was calculated (see below). Approxmate Entropy (ApEn) In ths paper, we analyze dynamc propertes of bnary sequences of length 8. For example, the bnary sequence s obvously more regular than e.g I.e., the successon of 0s and 1s s easy to predct n the frst sequence whereas the predcton of the successon of 0s and 1s n the latter sequence s more dffcult. Approxmate Entropy s an approprate measure for the quantfcaton of such aspects of bnary sequences (8, 19). For normal tme seres ApEn calculates the logarthmc frequency that sequences of length m that are close (wthn a tolerance r) reman close (wthn the same tolerance) n sequences of length m+1 (20). ApEn(m,r) depends on the length m and the tolerance r and t assgns hgher numbers to more rregular sequences. For bnary sequences the tolerance r s set to r < 1 because ths s the only practcal settng for a bnary metrc. Furthermore, to apply ApEn to short bnary sequences, the length m s set to 1. For further detals of the mplementaton of ApEn for bnary sequences see reference (19). As a result, a number reflectng the seral rregularty of the successon of 0s and 1s s assgned to each bnary sequence: the hgher ApEn, the more rregular (and less predctve of the successon of the 0s and 1s) the bnary sequence. Due to redundances wth respect to rregulartes of the bnary sequences, the 2 8 = 256 dfferent sequences are assgned only 17 dfferent values of ApEn. Hence, 17 dfferent pattern sets are created by mergng the bnary sequences wth the same value of ApEn n one set (for the sequences belongng to each set, see Onlne Data Supplements). These 17 pattern sets reflect dfferent dynamc propertes rangng from regular to rregular. It has to be noted that the appearance of sngle ectopc heartbeats or sngle artfacts s not crucal because they only cause an alternaton of one symbol resultng n a mnor bas n the frequency of some bnary patterns. If ectopc heartbeats appear frequently they are relevant for the assessment of the heartbeat dynamcs. Consequently, the contrbuton of ectopc heartbeats to the frequency of several bnary patterns s not a dsadvantage but reflects a relevant characterstcs of the dynamcs. In addton to the bnary approach, ApEn was also calculated for the normal RR nterval seres of each consecutve segment comprsng 1000 RR ntervals. The length m was set to 2 and the radus r was set to 20% of SDNN. Heart rate varablty As basc tme doman parameters the mean RR-nterval and the accompanyng standard devaton (SDNN) were calculated for each consecutve 5-mnute epoch. Furthermore, for these epochs, n the frequency doman the low and hgh frequency power (LF: Hz, HF: Hz) and the rato LF/HF were calculated usng the fast Fourer transformaton (22). For the CHF patents a fltered RR-tachogram was used to reduce the nfluence of premature ventrcular ectopc beats on these parameters (24).

5 D. Cysarz et al. Regular heartbeat dynamcs s healthy 5 Surrogate data In addton to the orgnal data, one surrogate data set of each recordng was created by shufflng the nterbeat ntervals RR n random order (23). The resultng seres of nterbeat ntervals only shares the dstrbuton of the orgnal nterbeat seres. All other lnear and non-lnear characterstcs, e.g. any temporal correlatons, are destroyed (Fg. 1b). Subsequently, the analyss of the bnary sequences n the surrogate data was carred out n the same manner as for the orgnal data. Statstcs As crcadan varatons of heart rate and HRV are well known (14), the analyss was carred out for the daytme (11:00 to 17:00) and nght-tme (0:00-6:00) perod. Based on the bnary sequence S of each perod the probablty of each pattern set (.e. the probablty of the bnary patterns belongng to each pattern set) was calculated. The results of the bnary analyss are presented as box plots n order to gve a detaled pcture of the dstrbutons. Approprate to ths non-parametrc approach, the dstrbutons of patterns of healthy subjects and CHF patents were compared usng the Wlcoxon rank sum test. Dfferences between the dstrbutons of daytme and nght-tme were evaluated wth Wlcoxon sgned rank test. The HRV parameters were log-transformed due to ther skewed dstrbuton. The transformed HRV parameters and the ApEn of the normal RR-ntervals are presented as mean ± standard devaton. Dfferences n the dstrbutons of these parameters between healthy subjects and CHF patents were examned usng Student s t-test. Furthermore, the dfferences between daytme and nght-tme n each group were also assessed usng the t-test (for dependent samples). A p-value <0.05 was consdered statstcally sgnfcant. Results The HRV parameters and ApEn of the RR-tachogram showed the followng results. The mean RR-nterval durng daytme was 703 ms for the healthy subjects and 662 ms for the CHF patents (see Table 1). Durng nght-tme the average RR-nterval of the healthy subjects and CHF patents ncreased sgnfcantly compared to daytme. Stll, the average RR-nterval of healthy subjects was sgnfcantly larger compared to CHF patents. SDNN was sgnfcantly larger for the healthy subjects but dd not show a dfference between daytme and nght-tme. For the spectral parameters of HRV ln LF, ln HF and ln LF/HF were sgnfcantly larger for the healthy subjects compared to the CHF patents. A sgnfcant dfference between daytme and nght-tme was found for ln HF and ln LF/HF of the healthy subjects HRV and ln LF for the CHF patents HRV. Durng daytme ApEn was sgnfcantly lower for the healthy subjects compared to the CHF patents (1.01 vs 1.29). Durng nght-tme ApEn of the healthy subjects ncreased sgnfcantly whereas ApEn of the CHF patents dd not change. The analyss of the bnary sequences reveals that durng daytme the beat-to-beat heartbeat dynamcs s clearly dfferent between healthy subjects and CHF patents (Fg. 2a). Sxteen out of 17 pattern sets show sgnfcant dfferences between the groups (p<0.01 for the pattern sets 1-15, p<0.05 for pattern set 17, pattern set 16 n.s.). Surprsngly the heartbeat dynamcs n healthy subjects shows a substantal amount of very regular dynamc patterns durng daytme (partcularly pattern sets 2-5). At the same tme, the bnary patterns belongng to these pattern sets appear very seldom n CHF patents. In contrast, only one very regular pattern set promnently appears n CHF patents (pattern set 1 contanng only the patterns and e. alternaton of acceleraton and deceleraton of the heart rate). Obvously, also

6 D. Cysarz et al. Regular heartbeat dynamcs s healthy 6 pattern sets 6 and 7 wth a medum regularty emerge far more often n CHF patents than n healthy subjects. Wth respect to pattern sets wth hgher rregularty durng daytme, sets 9, 12, 13 and 17 appear more often n CHF patents whereas pattern sets 8, 10, 11, 14 and 15 appear more often n healthy subjects. Durng nght-tme sleep the heartbeat dynamcs changes notably n healthy subjects whereas the heartbeat dynamcs of CHF patents remans very smlar compared to daytme (Fg. 2b). A number of pattern sets contanng the dynamc patterns wth hgher rregularty (pattern sets 9-17) were more lkely to occur durng nght-tme sleep compared to daytme (p<0.01, pattern sets 9, 13, 15-17; p<0.05, pattern sets 12, 14). As a consequence, as opposed to the dynamc propertes durng daytme, pattern set 14, 15 and 16 appear more often n healthy subjects compared to CHF patents (p<0.01). On the other hand, the lkelhood of the pattern sets 2-5, contanng the more regular patterns, decreased compared to daytme (p<0.01, pattern sets 3-5; p<0.05, pattern set 2). Stll, the pattern sets 2-5 are more lkely to appear n healthy subject than n CHF patents (p<0.01) and vce versa for pattern sets 1, 6 and 7 (p<0.01). In the medum range of rregularty the pattern sets 8, 10 and 11 are agan more lkely n healthy subjects (p<0.01 pattern sets 10 and 11, p<0.05 pattern set 8) and pattern set 9 s more lkely on CHF patents (p<0.05). We also carred out the analyss for other lengths of bnary sequences (7-12 successve heartbeats) and found analogous results for daytme and nght-tme heartbeat dynamcs. The probablty of the pattern sets for the surrogate data s the very smlar for healthy subjects and CHF patents (Fg. 2 a and b; hence, only one red astersk s shown per pattern set). The analyss of the surrogate data reveals that the dynamc features observed n beat-to-beat varatons of CHF patents s close to the dynamc features of random behavour of the heartbeat. Remarkably, the dynamcs of the random heartbeat s nether partcularly regular nor complex. In contrast to healthy heartbeat dynamcs, pattern set 1,.e. a beat-to-beat alternaton of acceleraton and deceleraton, s the only pattern set that substantally contrbutes to regularty whereas other regular dynamc patterns (pattern sets 2-5; whch nclude most of the regularty n healthy heartbeat dynamcs) are rare. Furthermore, the pattern sets 6-17 show a probablty whch s obvously typcal for random behavour. Hence, from a dynamc pont of vew on small tme scales, a random heartbeat also shows bnary patterns wth hgh rregularty. Dscusson The analyss of the rregularty of short beat-to-beat sequences reveals a detaled pcture of ts dynamc features. On short tme scales n the order of some seconds the healthy heartbeat s especally characterzed by a large amount of regular dynamcs consstng of a successon of beats reflectng heart rate acceleraton or deceleraton. Durng daytme such regular dynamcs are observable approxmately half of the tme. Physologcally, the contnuous adaptaton of the heartbeat to dfferent actvtes,.e. the transtons between behavoural states, leads to sequences of acceleraton or deceleraton lastng several heartbeats. Ths adaptaton s medated by sympathetc actvaton or wthdrawal (e.g. the transton from sttng to standng causes an ncrease of sympathetc actvty gvng rse to an acceleraton of the heartbeat). On larger tme scales, ths contnuous adaptaton,.e. the alternaton of sympathetc actvaton and wthdrawal, leads to a hgh varablty manly due to low frequency varatons whch s reflected by a large value of ln LF. At the same tme a prevalng parasympathetc modulaton s rather seldom as

7 D. Cysarz et al. Regular heartbeat dynamcs s healthy 7 ndcated by a rather low value of ln HF durng daytme. Hence, there s no preference of specfc bnary patterns wth hgher rregularty. Durng nght-tme the amount of regular patterns n the healthy beat-to-beat dynamcs decreases and the appearance of more complex heartbeat patterns ncreases. Such complex patterns manly reflect the rato between heart rate and respratory frequency as a result of respratory snus arrhythma (e.g. a rato of 7:2 s ndcated by the pattern whch belongs to pattern set 17) (4). Hence, the ncrease of more complex heartbeat patterns s an ndcator of an augmented parasympathetc modulaton whch s also reflected by an ncreased value of ln HF compared to daytme. On the other hand, physcal actvty durng sleep such as leg movement s accompaned by parasympathetc wthdrawal leadng to longer sequences of acceleraton of the heartbeat, followed by sequences of deceleraton when the movement stops. Thus, the correspondng regular bnary patterns stll occur to a certan extent even durng nght-tme sleep. Consequently, the well-known ncrease of heart rate varablty (especally ln HF) (10) and the well-known ncrease of complexty (as represented by ApEn of a RR-tachogram) (5) of heart rate durng nght-tme sleep on larger tme scales emerges prmarly from rregular but also regular heartbeat patterns on small tme scales. The beat-to-beat dynamcs of CHF patents hardly show the regular pattern sets observed n healthy subjects. Instead, they show a predomnance of regular pattern sets whch contan prmarly an alternaton of acceleraton and deceleraton of heart rate (pattern set 1, 6 and 7). Ths alternaton reflects the nablty of the CHF patents to adapt to dfferent actvtes. Takng nto account that the ampltude of such acceleratons and deceleratons s rather lmted, ths alternaton obvously leads to a well-known reducton of heart rate varablty whch s reflected by lower values of ln LF and ln HF compared to healthy subjects (6). However, the predomnance of regular pattern sets does not mply a sgnfcantly decreased complexty on larger tme scales as durng daytme ApEn of the RR-tachogram for CHF patents s not dfferent from ApEn for healthy subjects. Hence, very dfferent heartbeat dynamcs on small tme scales may lead to smlar ApEn values on larger tme scales. Takng nto account that more rregular pattern sets appear n the heart rate dynamcs of healthy people durng nght-tme sleep, t seems that the ncrease of ApEn on longer tme scales manly reflects the ncrease of the appearance of these pattern sets. The dynamcs of the beat-to-beat patterns of CHF patents approaches random heartbeat dynamcs whch s characterzed by a specfc dstrbuton of the dfferent pattern sets. Apart from the predomnance of alternaton of acceleraton and deceleraton, ths ncludes bnary sequences wth hgh rregularty. Ths erratc behavour reflects the absence of nfluence of the autonomc nervous system and, hence, may contrbute as a factor for hgh-rsk of mortalty (1). We only dfferentated between daytme and nght-tme dynamcs of the heart rate. Hence, the precse prerequstes of regular or rregular heartbeat dynamcs n terms of sympathetc and parasympathetc actvty or modulaton need to be explored more explctly, e.g. wth the help of pharmacologcal agents or under specfc physologcal condtons. We note that the present analyss requres a samplng rate of the electrocardogram of at least 250 Hz to dentfy the R- peaks wth a suffcent temporal resoluton. A low samplng rate n conjuncton wth a low heart rate varablty could lead to a successon of acceleraton or deceleraton comprsng two or three heartbeats. Hence, the assgnment of the bnary patterns to the pattern sets would be erroneous. Such symbolc sequences would turn out to be an alternaton of acceleraton and deceleraton f

8 D. Cysarz et al. Regular heartbeat dynamcs s healthy 8 the samplng rate would be suffcently hgh. Although symbolc dynamcs consderably reduces the amount of nformaton contaned n the orgnal tme seres, the symbolzaton presented n ths paper s advantageous because t does not requre statonarty of the tme seres as a prerequste for ts analyss. In concluson, the analyss of dfferent levels of rregularty n short sequences of acceleraton or deceleraton of the nstantaneous heart rate extends and refnes the noton of complexty of human heartbeat dynamcs. In healthy subjects the contnuous adaptaton to dfferent actvtes durng daytme,.e. the sympathetc modulaton, leads to regular heartbeat dynamcs on small tme scales. They manly contan successons of acceleraton or deceleraton of heart rate. Durng nght-tme sleep rregular heartbeat dynamcs on small tme scales emerge caused by parasympathetc modulaton. Both, regular as well as rregular, contrbute to a pronounced heart rate varablty as found n healthy subjects. In CHF patents the heartbeat dynamcs on small tme scales s close to an erratc behavour. Regular heartbeat patterns contanng an alternaton of acceleraton and deceleraton largely contrbute to such dynamcs, but also heartbeat patterns wth hgh rregularty. They reflect the lmted nfluence of the autonomc nervous system on heartbeat varatons. Taken together, t may be worth lookng at the amount and the knd of regular beat-to-beat dynamcs (pattern sets) to unambguously dstngush between health and dsease. Acknowledgements Ths work was supported by grants of the Software AG Stftung (D.C., P.M.). References 1. Bauer A, Kantelhardt JW, Barthel P, Schneder R, Makkallo T, Ulm K, Hnatkova K, Schomg A, Hukur H, Bunde A, Malk M and Schmdt G. Deceleraton capacty of heart rate as a predctor of mortalty after myocardal nfarcton: cohort study. Lancet 367: , Bettermann H, Amponsah D, Cysarz D and Van Leeuwen P. Muscal rhythms n heart perod dynamcs - a cross-cultural and nterdscplnary approach to cardac rhythms. Am J Physol 277: H1762-H1770, Bettermann H, Cysarz D and Van Leeuwen P. Detectng cardorespratory synchronzaton by respratory pattern analyss of heart perod dynamcs: the muscal rhythm approach. Int J Bfurcat Chaos 10: , Bettermann H, Cysarz D and Van Leeuwen P. Comparson of two dfferent approaches n the detecton of ntermttent cardorespratory coordnaton durng nght sleep. BMC Physol 2: 18, Bettermann H and Van Leeuwen P. Evdence of phase transtons n heart perod dynamcs. Bol Cybern 78: 63-70, Casolo G, Ball E, Tadde T, Amuhas J and Gor C. Decreased spontaneous heart rate varablty n congestve heart falure. Am J Cardol 64: , Costa M, Goldberger AL and Peng CK. Multscale entropy analyss of complex physologc tme seres. Phys Rev Lett 89: , Cysarz D, Bettermann H and Van Leeuwen P. Entropes of short bnary sequences n heart perod dynamcs. Am J Physol Heart Crc Physol 278: H2163-H2172, 2000.

9 D. Cysarz et al. Regular heartbeat dynamcs s healthy 9 9. Cysarz D, Schürholz T, Bettermann H and Kümmell HC. Evaluaton of modulatons n heart rate varablty caused by a composton of herbal extracts. Arznemttelforschung 50: , Fallen EL and Kamath M. Crcadan rhythms of heart rate varablty. In: Heart rate varablty, edted by Malk M and Camm AJ. Armonk NY: Futura Publshng, 1995, p Goldberger AL, Amaral LA, Hausdorff JM, Ivanov PC, Peng CK and Stanley HE. Fractal dynamcs n physology: alteratons wth dsease and agng. Proc Natl Acad Sc USA 99: , Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Metus JE, Moody GB, Peng CK and Stanley HE. PhysoBank, PhysoToolkt, and PhysoNet: components of a new research resource for complex physologc sgnals. Crculaton 101: E215-E220, Guzzett S, Borron E, Garbell PE, Ceran E, Della Bella P, Montano N, Coglat C, Somers VK, Mallan A and Porta A. Symbolc dynamcs of heart rate varablty. A probe to nvestgate cardac autonomc modulaton. Crculaton 112: , Hukur HV, Kessler KM, Terracall E, Castellanos A, Lnnaluoto MK and Myerburg RJ. Reproducblty and crcadan rhythm of heart rate varablty n healthy subjects. Am J Cardol 65: , Ivanov PC, Amaral LAN, Goldberger AL, Havln S, Rosenblum MG, Struzk ZR and Stanley HE. Multfractalty n human heartbeat dynamcs. Nature 399: , Kurths J, Voss A, Saparn P, Wtt A, Klener HJ and Wessel N. Quanttatve analyss of heart rate varablty. Chaos 5: 88-94, Meyerfeldt U, Wessel N, Schutt H, Selbg D, Schumann A, Voss A, Kurths J, Zehmann C, Detz R and Schrdewan A. Heart rate varablty before the onset of ventrcular tachycarda: dfferences between slow and fast arrhythmas. Int J Cardol 84: , Palazzolo JA, Estafanous FG and Murray PA. Entropy measures of heart rate varaton n conscous dogs. Am J Physol 274: H1099-H1105, Pncus S and Snger BH. Randomness and degrees of rregularty. Proc Natl Acad Sc USA 93: , Pncus SM. Approxmate entropy as a measure of system complexty. Proc Natl Acad Sc USA 88: , Poon CS and Merrll CK. Decrease of cardac chaos n congestve heart falure. Nature 389: , Task Force of the European Socety of Cardology and the North Amercan Socety of Pacng and Electrophysology. Heart rate varablty: standards of measurement, physologcal nterpretaton, and clncal use. Crculaton 93: , Theler J, Eubank S, Longtn A, Galdrkan B and Farmer JD. Testng nonlnearty n tme seres: the method of surrogate data. Physca D 58: 77-94, Wessel N, Voss A, Malberg H, Zehmann C, Voss HU, Schrdewan A, Meyerfeldt U and Kurths J. Nonlnear analyss of complex phenomena n cardologcal data. Herzschr Elektrophys 11: , Yang ACC, Hseu SS, Yen HW, Goldberger AL and Peng CK. Lngustc analyss of the human heartbeat usng frequency and rank order statstcs. Phys Rev Lett 90: , 2003.

10 D. Cysarz et al. Regular heartbeat dynamcs s healthy 10 Supportng Informaton lstng the bnary patterns belongng to each of the 17 pattern sets s avalable onlne. Fgure legends Fgure 1: (A) Non-statonarty of the healthy human nterbeat tme seres. The non-statonartes lead to large fluctuatons on large tme scales as well as on small tme scales (see nset). The fluctuatons on small tme scales reveal sequences of acceleraton and deceleraton of the heartbeat often lastng several heartbeats. (B) Surrogate data for the same data set. Obvously the temporal structure of the orgnal data s completely lost. (C) Creaton of symbolc sequences. Based on the nterbeat ntervals the acceleraton of the heartbeat s symbolzed by 1's (negatve slope of the lne between two successve nterbeat ntervals) and the deceleraton of the heartbeat s symbolzed by 0's (postve slope of the lne between two successve nterbeat ntervals). (D) Symbolc sequences for the surrogate data.

11 D. Cysarz et al. Regular heartbeat dynamcs s healthy 11 Fgure 2: Lkelhood of the appearance of the 17 pattern sets n the heartbeat dynamcs of healthy subjects (whte boxes) and CHF patents (grey boxes) durng daytme (A) and nght-tme (B). The successon of the pattern sets reflects the ncrease of rregularty of the bnary patterns contaned n the pattern sets. The red astersks show the medan probablty of the 17 pattern sets for the surrogate data (the use of Boxplots was not practcal as the dstrbutons are very narrow).