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Jordão S, Stergiou N, Brandão R, Pezarat-Correia P, Oliveira R, Cortes N, Vaz JR. Muscle activity variability patterns and stride to stride fluctuations of older adults are positively correlated during walking. Sci Rep 2023; 13:20721. [PMID: 38007498 PMCID: PMC10676363 DOI: 10.1038/s41598-023-47828-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 11/18/2023] [Indexed: 11/27/2023] Open
Abstract
It has been found that fractal-like patterns are present in the temporal structure of the variability of healthy biological rhythms, while pathology and disease lead to their deterioration. Interestingly, it has recently been suggested that these patterns in biological rhythms are related with each other, reflecting overall health or lack of it, due to their interaction. However, the underlying neurophysiological mechanisms responsible for such dependency remain unknown. In addition, this relationship between different elements needs to be first verified before we even pursue understanding their interaction. This study aimed to investigate the relationship between two elements of the neuromuscular system, gait and muscle activity variability patterns in older adults. Twenty-one older adults walked at their preferred walking speed on a treadmill. Inter-stride intervals were obtained through an accelerometer placed on the lateral malleoli to assess the temporal structure of variability of stride-to-stride fluctuations. Inter muscle peak intervals were obtained through the electromyographic signal of the gastrocnemius to assess the temporal structure of the variability of the simultaneous muscle activity. The temporal structure of variability from both signals was evaluated through the detrended fluctuation analysis, while their magnitude of variability was evaluated using the coefficient of variation. The Pearson's Correlation coefficient was used to identify the relationship between the two dependent variables. A significant strong positive correlation was found between the temporal structure of gait and muscle activity patterns. This result suggests that there is an interdependency between biological rhythms that compose the human neuromuscular system.
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Affiliation(s)
- Sofia Jordão
- CIPER, Neuromuscular Research Lab, Faculty of Human Kinetics, University of Lisbon, Lisbon, Portugal
- Egas Moniz Center for Interdisciplinary Research (CiiEM), Egas Moniz School of Health & Science, Campus Universitário, Quinta da Granja, Monte da Caparica, 2829 - 511, Caparica, Portugal
- Hospital da Ordem Terceira Chiado, Lisbon, Portugal
| | - Nick Stergiou
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE, USA
- Department of Physical Education and Sport Science, Aristotle University, Thessaloniki, Greece
| | - Rita Brandão
- CIPER, Neuromuscular Research Lab, Faculty of Human Kinetics, University of Lisbon, Lisbon, Portugal
| | - Pedro Pezarat-Correia
- CIPER, Neuromuscular Research Lab, Faculty of Human Kinetics, University of Lisbon, Lisbon, Portugal
| | - Raúl Oliveira
- CIPER, Neuromuscular Research Lab, Faculty of Human Kinetics, University of Lisbon, Lisbon, Portugal
| | - Nelson Cortes
- School of Sport, Rehabilitation and Exercise Sciences, University of Essex, Colchester, UK
- Department of Bioengineering, George Mason University, Fairfax, VA, USA
| | - João R Vaz
- CIPER, Neuromuscular Research Lab, Faculty of Human Kinetics, University of Lisbon, Lisbon, Portugal.
- Egas Moniz Center for Interdisciplinary Research (CiiEM), Egas Moniz School of Health & Science, Campus Universitário, Quinta da Granja, Monte da Caparica, 2829 - 511, Caparica, Portugal.
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, NE, USA.
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Kamal SM, Babini MH, Tee R, Krejcar O, Namazi H. Decoding the correlation between heart activation and walking path by information-based analysis. Technol Health Care 2023; 31:205-215. [PMID: 35848002 DOI: 10.3233/thc-220191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
BACKGROND One of the important areas of heart research is to analyze heart rate variability during (HRV) walking. OBJECTIVE In this research, we investigated the correction between heart activation and the variations of walking paths. METHOD We employed Shannon entropy to analyze how the information content of walking paths affects the information content of HRV. Eight healthy students walked on three designed walking paths with different information contents while we recorded their ECG signals. We computed and analyzed the Shannon entropy of the R-R interval time series (as an indicator of HRV) versus the Shannon entropy of different walking paths and accordingly evaluated their relation. RESULTS According to the obtained results, walking on the path that contains more information leads to less information in the R-R time series. CONCLUSION The analysis method employed in this research can be extended to analyze the relation between other physiological signals (such as brain or muscle reactions) and the walking path.
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Affiliation(s)
| | | | - Rui Tee
- School of Pharmacy, Monash University, Selangor, Malaysia
| | - Ondrej Krejcar
- Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czech Republic.,Malaysia Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia
| | - Hamidreza Namazi
- School of Engineering, Monash University, Selangor, Malaysia.,Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czech Republic
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Abstract
In this work, we analyze the complexity of monthly rainfall temporal series recorded from 1962 to 2012, at 133 gauge stations in the state of Pernambuco, northeastern Brazil. To this end, we employ the modified multiscale entropy method (MMSE), which is well suited for short time series, to analyze the rainfall regularity across a wide range of temporal scales, from one month to one year. We identify the temporal scales that distinguish rainfall regularity in the inland semiarid Sertão region, the transitional inland Agreste region, and the coastal, tropical humid Zona da Mata region, by comparing the results for stations across the study area and performing statistical significance tests. Our work contributes to the establishment of multiscale methods based on information theory in climatological studies.
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Pakniyat N, Namazi H. Decoding the coupling between the brain and skin reactions in auditory stimulation by information-based analysis of EEG and GSR signals. Technol Health Care 2021; 30:623-632. [PMID: 34542048 DOI: 10.3233/thc-213052] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The analysis of brain activity in different conditions is an important research area in neuroscience. OBJECTIVE This paper analyzed the correlation between the brain and skin activities in rest and stimulations by information-based analysis of electroencephalogram (EEG) and galvanic skin resistance (GSR) signals. METHODS We recorded EEG and GSR signals of eleven subjects during rest and auditory stimulations using three pieces of music that were differentiated based on their complexity. Then, we calculated the Shannon entropy of these signals to quantify their information contents. RESULTS The results showed that music with greater complexity has a more significant effect on altering the information contents of EEG and GSR signals. We also found a strong correlation (r= 0.9682) among the variations of the information contents of EEG and GSR signals. Therefore, the activities of the skin and brain are correlated in different conditions. CONCLUSION This analysis technique can be utilized to evaluate the correlation among the activities of various organs versus brain activity in different conditions.
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Pakniyat N, Babini MH, Kulish VV, Namazi H. Information-based analysis of the coupling between brain and heart reactions to olfactory stimulation. Technol Health Care 2021; 30:661-671. [PMID: 34397441 DOI: 10.3233/thc-213136] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
BACKGROUND Analysis of the heart activity is one of the important areas of research in biomedical science and engineering. For this purpose, scientists analyze the activity of the heart in various conditions. Since the brain controls the heart's activity, a relationship should exist among their activities. OBJECTIVE In this research, for the first time the coupling between heart and brain activities was analyzed by information-based analysis. METHODS Considering Shannon entropy as the indicator of the information of a system, we recorded electroencephalogram (EEG) and electrocardiogram (ECG) signals of 13 participants (7 M, 6 F, 18-22 years old) in different external stimulations (using pineapple, banana, vanilla, and lemon flavors as olfactory stimuli) and evaluated how the information of EEG signals and R-R time series (as heart rate variability (HRV)) are linked. RESULTS The results indicate that the changes in the information of the R-R time series and EEG signals are strongly correlated (ρ=-0.9566). CONCLUSION We conclude that heart and brain activities are related.
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Affiliation(s)
| | | | - Vladimir V Kulish
- Faculty of Mechanical Engineering, Czech Technical University in Prague, Prague, Czech Republic
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Kamal SM, Dawi NM, Namazi H. Information-based decoding of the coupling among human brain activity and movement paths. Technol Health Care 2021; 29:1109-1118. [PMID: 33749623 DOI: 10.3233/thc-202744] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Walking like many other actions of a human is controlled by the brain through the nervous system. In fact, if a problem occurs in our brain, we cannot walk correctly. Therefore, the analysis of the coupling of brain activity and walking is very important especially in rehabilitation science. The complexity of movement paths is one of the factors that affect human walking. For instance, if we walk on a path that is more complex, our brain activity increases to adjust our movements. OBJECTIVE This study for the first time analyzed the coupling of walking paths and brain reaction from the information point of view. METHODS We analyzed the Shannon entropy for electroencephalography (EEG) signals versus the walking paths in order to relate their information contents. RESULTS According to the results, walking on a path that contains more information causes more information in EEG signals. A strong correlation (p= 0.9999) was observed between the information contents of EEG signals and walking paths. Our method of analysis can also be used to investigate the relation among other physiological signals of a human and walking paths, which has great benefits in rehabilitation science.
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