Multiscale entropy analysis of human gait dynamics
We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity wh...
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| Published in | Physica A Vol. 330; no. 1; pp. 53 - 60 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier B.V
01.12.2003
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0378-4371 1873-2119 1873-2119 |
| DOI | 10.1016/j.physa.2003.08.022 |
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| Abstract | We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to walking paced by a metronome. These findings have implications for modeling locomotor control and for quantifying gait dynamics in physiologic and pathologic states. |
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| AbstractList | We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to walking paced by a metronome. These findings have implications for modeling locomotor control and for quantifying gait dynamics in physiologic and pathologic states.We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to walking paced by a metronome. These findings have implications for modeling locomotor control and for quantifying gait dynamics in physiologic and pathologic states. We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to walking paced by a metronome. These findings have implications for modeling locomotor control and for quantifying gait dynamics in physiologic and pathologic states. |
| Author | L. Goldberger, Ary Costa, M. Peng, C.-K. Hausdorff, Jeffrey M. |
| AuthorAffiliation | b Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, Campo Grande 1749-016 Lisbon, Portugal a Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA d Gerontology Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue East Campus, Boston, MA 02215, USA c Movement Disorders Unit, Tel-Aviv Sourasky Medical Center; Sackler School of Medicine, Tel-Aviv, Israel |
| AuthorAffiliation_xml | – name: d Gerontology Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue East Campus, Boston, MA 02215, USA – name: b Institute of Biophysics and Biomedical Engineering, Faculty of Sciences, University of Lisbon, Campo Grande 1749-016 Lisbon, Portugal – name: c Movement Disorders Unit, Tel-Aviv Sourasky Medical Center; Sackler School of Medicine, Tel-Aviv, Israel – name: a Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA |
| Author_xml | – sequence: 1 givenname: M. surname: Costa fullname: Costa, M. organization: Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA – sequence: 2 givenname: C.-K. surname: Peng fullname: Peng, C.-K. organization: Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA – sequence: 3 givenname: Ary surname: L. Goldberger fullname: L. Goldberger, Ary organization: Cardiovascular Division, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA – sequence: 4 givenname: Jeffrey M. surname: Hausdorff fullname: Hausdorff, Jeffrey M. email: jhausdorff@alum.mit.edu organization: Movement Disorders Unit, Tel-Aviv Sourasky Medical Center; Sackler School of Medicine, Tel-Aviv, Israel |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35518362$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | 2003 Elsevier B.V. |
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| SubjectTerms | Complexity Human gait Locomotion Multiscale entropy Neural control |
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| Title | Multiscale entropy analysis of human gait dynamics |
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