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Licensed Unlicensed Requires Authentication Published by De Gruyter February 3, 2020

A Matlab toolbox for analyzing repetitive movements: application in gait and tapping experiments

Mehmet Eylem Kirlangic EMAIL logo , Safwan Al-Qadhi , Christian Hauptmann and Hans-Joachim Freund

Abstract

Coordination and timing in repetitive movements have been intensively investigated in diverse experimental settings for understanding the underlying basic mechanisms in healthy controls. On this basic research side, there are mainly two theoretical models: the Wing-Kristofferson (WK) model and the Haken-Kelso-Bunz (HKB) model. On the clinical side of the research, several efforts have been spent on quantitatively assessing gait and other repetitive movements such as tapping, especially as an outcome measure of clinical trials in diverse neurological disorders. Nevertheless, Parkinson’s disease (PD) remains the predominant disorder in the clinical literature in this context, as the tremor activity and the changes in the gait are both common symptoms in PD. Although there are motion recording systems for data acquisition in clinical settings, the tools for analysis and quantification of the extracted time-series offered by these systems are severely restricted. Therefore, we introduce a toolbox which enables the analysis of repetitive movements within the framework of the two main theoretical models of motor coordination, which explicitly focuses on varying clinical and experimental settings such as self-paced vs. cued or uni-manual vs. bi-manual measurements. The toolbox contains particular pipelines for digital signal processing. Licensed under the GNU General Public License (GNU-GPL), the open source toolbox is freely available and can be downloaded from the Github link: https://github.com/MehmetEylemKirlangic/RepetitiveMovementAnalysis. We illustrate the application of the toolbox on sample experiments of gait and tapping with a control subject, as well as with a Parkinson’s patient. The patient has gone through a brain surgery for deep brain stimulation (DBS); hence, we present the results for both stimulation ON and stimulation OFF modes. Sample data are freely accessible at: https://github.com/MehmetEylemKirlangic/DATA.

Acknowledgments

We would like to thank to Prof. Dr. Dr. A. Peter Tass for the invaluable discussions on synchronization analysis. We also thank to Thomas Barnikol, Dr. Utako Barnikol, Heidi Mellenthin, Andrea Muren, Veronika Kriebel, Irene Werner and Natalie Schlothauer for their support in the clinical work and measurements with the subjects.

  1. Research funding: Authors state no funding involved.

  2. Conflict of interest: Authors state no conflict of interest.

  3. Informed consent: All measurement protocols have been institutionally approved by the University Clinic Cologne and informed consent has been obtained.

  4. Ethical approval: All measurement protocols have been institutionally approved by the Ethics Commitee of the University Clinic Cologne.

References

[1] Wing AM, Kristofferson AB. The timing of interresponse intervals. Atten Percept Psychophys 1973;13:455–60.10.3758/BF03205802Search in Google Scholar

[2] Wing AM, Kristofferson AB. Response delays and the timing of discrete motor responses. Atten Percept Psychophys 1973;14:5–12.10.3758/BF03198607Search in Google Scholar

[3] Wing AM. Voluntary timing and brain function: an information processing approach. Brain Cogn 2002;48:7–30.10.1006/brcg.2001.1301Search in Google Scholar

[4] Doumas M, Wing MA, Wood K. Interval timing and trajectory in unequal amplitude movements. Exp Brain Res 2008;189:49–60.10.1007/s00221-008-1397-6Search in Google Scholar

[5] Haken H, Kelso JAS, Bunz H. A theoretical model of phase transitions in human hand movements. Biol Cybern 1985;51:347–56.10.1007/BF00336922Search in Google Scholar

[6] Haken H. Synergetics: an introduction: nonequilibrium phase transitions and self-organisation in physics, chemistry and biology. Second enlarged edition, Berlin, Heidelberg: Springer Verlag; 1983.Search in Google Scholar

[7] Kelso JAS, Scholz JP, Schöner G. Nonequilibrium phase transitions in coordinated biological motion: critical fluctuations. Phys Lett A 1986;118:279–84.10.1016/0375-9601(86)90359-2Search in Google Scholar

[8] Kelso JAS. Dynamic patterns: the self-organization of brain and behavior. Cambridge, MA: MIT Press; 1995.Search in Google Scholar

[9] Haken H, Peper CE, Beek PJ, Daffertshofer A. A model for phase transitions in human hand movements during multifrequency tapping. Physica D 1996;90:179–96.10.1016/0167-2789(95)00235-9Search in Google Scholar

[10] Collyer C, Broadbent H, Church R. Preferred rates of repetitive tapping and categorical time production. Atten Percept Psychophys 1994;55:443–53.10.3758/BF03205301Search in Google Scholar PubMed

[11] Peper CE, Beek PJ. Are frequency-induced transitions in rhythmic coordination mediated by a drop in amplitude? Biol Cybern 1998;79:291–300.10.1007/s004220050479Search in Google Scholar PubMed

[12] Peper CE, Beek PJ. Distinguishing between the effects of frequency and amplitude on interlimb coupling in tapping a 2:3 polyrhythm. Exp Brain Res 1998;118:78–92.10.1007/s002210050257Search in Google Scholar PubMed

[13] Peper CE, Beek PJ. Modeling rhythmic interlimb coordination: the roles of movement amplitude and time delays. Hum Mov Sci 1999;18:263–80.10.1016/S0167-9457(99)00011-1Search in Google Scholar

[14] Beek PJ, Peper CE, Daffertshofer A. Timekeepers vs. nonlinear oscillators: how the approaches differ. In: Desain P, Windsor L, editors. Rhythm perception and production. Lisse: Swets and Zeitlinger; 2000:9–33.Search in Google Scholar

[15] Beek PJ, Peper CE, Daffertshofer A. Modeling rhythmic interlimb coordination: beyond the Haken-Kelso-Bunz model. Brain Cogn 2002;48:149–65.10.1006/brcg.2001.1310Search in Google Scholar

[16] Frischer M. Voluntary vs. autonomous control of repetitive finger tapping in a patient with Parkinson’s disease. Neuropsychologia 1989;27:1261–6.10.1016/0028-3932(89)90038-9Search in Google Scholar

[17] O’Boyle DJ, Freeman J, Cody FWJ. The accuracy and precision of timing of self-paced, repetitive movements in subjects with Parkinson’s disease. Brain 1996;119:51–70.10.1093/brain/119.1.51Search in Google Scholar

[18] Konczak J, Ackermann H, Hertrich I, Spieker S, Dichgans J. Control of repetitive lip and finger movements in Parkinson’s disease: influence of external timing signals and simultaneous execution on motor performance. Mov Disord 1997;12:665–76.10.1002/mds.870120507Search in Google Scholar

[19] Costa J, Gonzalez HA, Valldeoriola F, Gaig C, Tolosa E, Valls-Sole J. Nonlinear dynamic analysis of oscillatory repetitive movements in Parkinson’s disease and essential tremor. Mov Disord 2010;25:2577–86.10.1002/mds.23334Search in Google Scholar

[20] Stolze H, Kuhtz-Buschbeck JP, Mondwurf C, Boczek-Funcke A, Jöhnk K, Deuschl G, et al. Gait analysis during treadmill and overground locomotion in children and adults. Electroencephalogr Clin Neurophysiol 1997;105:490–7.10.1016/S0924-980X(97)00055-6Search in Google Scholar

[21] Kirtley C. Clinical gait analysis – theory and practice. China: Churchill Livingstone Elsevier; 2006.Search in Google Scholar

[22] Ebersbach G, Sojer M, Valldeoriola F, Wissel J, Müller J, Tolosa E, et al. Comparative analysis of gait in Parkinson’s disease, cerebellar ataxia and subcortical arteriosclerotic encephalopathy. Brain 1999;122:1349–55.10.1093/brain/122.7.1349Search in Google Scholar PubMed

[23] Stolze H, Kuhtz-Buschbeck JP, Drücke H, Jöhnk K, Illert M, Deuschl G. Comparative analysis of the gait disorder of normal pressure hydrocephalus and Parkinson’s disease. J Neurol Neurosurg Psychiatry 2001;70:289–97.10.1136/jnnp.70.3.289Search in Google Scholar PubMed PubMed Central

[24] Suteerawattananon M, Morris GS, Etnyre BR, Jankovic J, Proras EJ. Effects of visual and auditory cues on gait in individuals with Parkinson’s disease. J Neurol Sci 2004;219:63–9.10.1016/j.jns.2003.12.007Search in Google Scholar PubMed

[25] Bartsch R, Plotnik M, Kantelhardt JW, Havlin S, Giladi N, Hausdorff JM. Fluctuation and synchronization of gait intervals and gait force profiles distinguish stages of Parkinson’s disease. Physica A 2007;383:455–65.10.1016/j.physa.2007.04.120Search in Google Scholar

[26] Plotnik M, Giladi N, Hausdorff JM. Bilateral coordination of walking and freezing of gait in Parkinson’s disease. Eur J Neurosci 2008;27:1999–2006.10.1111/j.1460-9568.2008.06167.xSearch in Google Scholar

[27] Plotnik M, Giladi N, Hausdorff J. A new measure for quantifying the bilateral coordination of human gait: effects of aging and Parkinson’s disease. Exp Brain Res 2007;181:561–70.10.1007/s00221-007-0955-7Search in Google Scholar

[28] Benabid AL, Chabardes S, Mitrofanis J, Pollak P. Deep brain stimulation of the subthalamic nucleus for the treatment of Parkinson’s disease. Lancet Neurol 2009;8:67–81.10.1016/S1474-4422(08)70291-6Search in Google Scholar

[29] Stolze H, Klebe S, Poepping M, Lorenz D, Herzog J, Hamel W, et al. Effects of bilateral subthalamic nucleus stimulation on parkinsonian gait. Neurology 2001;57:144–6.10.1212/WNL.57.1.144Search in Google Scholar PubMed

[30] Volkmann J. Deep brain stimulation for the treatment of Parkinson’s disease. J Clin Neurophysiol 2004;21:6–17.10.1097/00004691-200401000-00003Search in Google Scholar PubMed

[31] Sekhar SC, Sreenivas TV. Adaptive window zero-crossing-based instantaneous frequency estimation. EURASIP J Appl Signal Process 2004;12:1791–806.10.1155/S111086570440417XSearch in Google Scholar

[32] Tass P, Rosenblum MG, Weule J, Kurths J, Pikovsky A, Volkmann J, et al. Detection of n:m phase locking from noisy data: application to magnetoencephalography. Phys Rev Lett 1998;81:3291–4.10.1103/PhysRevLett.81.3291Search in Google Scholar

[33] Kirlangic ME, Perez D, Ivanova G. Adaptive recursive threshold for unsupervised epileptic pattern recognition. Proceed. of the 38th Annual Congress of the German Society for Biomedical Engineering (DGBMT), ISSN 0939-4990, Biomed Eng/Biomed Tech – de Gruyter 2004;49:330–1.Search in Google Scholar

Received: 2018-09-27
Accepted: 2019-10-07
Published Online: 2020-02-03
Published in Print: 2020-08-27

©2020 Walter de Gruyter GmbH, Berlin/Boston

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