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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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Soundirarajan M, Kuca K, Krejcar O, Namazi H. Decoding of the coupling between the brain and facial muscle reactions in auditory stimulation. Technol Health Care 2021; 30:859-868. [PMID: 34842201 DOI: 10.3233/thc-213528] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Analysis of the reactions of different organs to external stimuli is an important area of research in physiological science. OBJECTIVE In this paper, we investigated the correlation between the brain and facial muscle activities by information-based analysis of electroencephalogram (EEG) signals and electromyogram (EMG) signals using Shannon entropy. METHOD The EEG and EMG signals of thirteen subjects were recorded during rest and auditory stimulations using relaxing, pop, and rock music. Accordingly, we calculated the Shannon entropy of these signals. RESULTS The results showed that rock music has a greater effect on the information of EEG and EMG signals than pop music, which itself has a greater effect than relaxing music. Furthermore, a strong correlation (r= 0.9980) was found between the variations of the information of EEG and EMG signals. CONCLUSION The activities of the facial muscle and brain are correlated in different conditions. This technique can be utilized to investigate the correlation between the activities of different organs versus brain activity in different situations.
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Affiliation(s)
| | - Kamil Kuca
- Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Czechia.,Malaysia Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia
| | - Ondrej Krejcar
- Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Czechia.,Malaysia Japan International Institute of Technology (MJIIT), 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, Czechia
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Pakniyat N, Namazi H. Complexity-Based Analysis of the Variations of Brain and Muscle Reactions in Walking and Standing Balance While Receiving Different Perturbations. Front Hum Neurosci 2021; 15:749082. [PMID: 34690727 PMCID: PMC8531105 DOI: 10.3389/fnhum.2021.749082] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 09/06/2021] [Indexed: 11/18/2022] Open
Abstract
In this article, we evaluated the variations of the brain and muscle activations while subjects are exposed to different perturbations to walking and standing balance. Since EEG and EMG signals have complex structures, we utilized the complexity-based analysis. Specifically, we analyzed the fractal dimension and sample entropy of Electroencephalogram (EEG) and Electromyogram (EMG) signals while subjects walked and stood, and received different perturbations in the form of pulling and rotation (via virtual reality). The results showed that the complexity of EEG signals was higher in walking than standing as the result of different perturbations. However, the complexity of EMG signals was higher in standing than walking as the result of different perturbations. Therefore, the alterations in the complexity of EEG and EMG signals are inversely correlated. This analysis could be extended to investigate simultaneous variations of rhythmic patterns of other physiological signals while subjects perform different activities.
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Affiliation(s)
| | - Hamidreza Namazi
- Incubator of Kinanthropology Research, Faculty of Sports Studies, Masaryk University, Brno, Czechia.,College of Engineering and Science, Victoria University, Melbourne, VIC, Australia
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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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Namazi H. Complexity-based analysis of the correlation between stride interval variability and muscle reaction at different walking speeds. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102956] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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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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Ahamed MRA, Babini MH, Namazi H. Analysis of the information transfer between brains during a conversation. Technol Health Care 2021; 29:283-293. [DOI: 10.3233/thc-202366] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND: The interaction between people is one of the usual daily activities. For this purpose, people mainly connect with others, using their voice. Voices act as the auditory stimuli on the brain during a conversation. OBJECTIVE: In this research, we analyze the relationship between the brains’ activities of subjects during a conversation. METHODS: Since human voice transfers information from one subject to another, we used information theory for our analysis. We investigated the alterations of Shannon entropy of electroencephalography (EEG) signals for subjects during a conversation. RESULTS: The results demonstrated that the alterations in the information contents of the EEG signals for the listeners and speakers are correlated. Therefore, we concluded that the brains’ activities of both subjects are linked. CONCLUSION: Our results can be expanded to analyze the coupling among other physiological signals of subjects (such as heart rate) during the conversation.
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Soundirarajan M, Pakniyat N, Sim S, Nathan V, Namazi H. Information-based analysis of the relationship between brain and facial muscle activities in response to static visual stimuli. Technol Health Care 2021; 29:99-109. [DOI: 10.3233/thc-192085] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND: Human facial muscles react differently to different visual stimuli. It is known that the human brain controls and regulates the activity of the muscles. OBJECTIVE: In this research, for the first time, we investigate how facial muscle reaction is related to the reaction of the human brain. METHODS: Since both electromyography (EMG) and electroencephalography (EEG) signals, as the features of muscle and brain activities, contain information, we benefited from the information theory and computed the Shannon entropy of EMG and EEG signals when subjects were exposed to different static visual stimuli with different Shannon entropies (information content). RESULTS: Based on the obtained results, the variations of the information content of the EMG signal are related to the variations of the information content of the EEG signal and the visual stimuli. Statistical analysis also supported the results indicating that the visual stimuli with greater information content have a greater effect on the variation of the information content of both EEG and EMG signals. CONCLUSION: This investigation can be further continued to analyze the relationship between facial muscle and brain reactions in case of other types of stimuli.
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Affiliation(s)
| | | | - Sue Sim
- School of Engineering, Monash University, Selangor, Malaysia
| | - Visvamba Nathan
- School of Engineering, Monash University, Selangor, Malaysia
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Babini MH, Kulish VV, Namazi H. Physiological State and Learning Ability of Students in Normal and Virtual Reality Conditions: Complexity-Based Analysis. J Med Internet Res 2020; 22:e17945. [PMID: 32478661 PMCID: PMC7313733 DOI: 10.2196/17945] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 03/04/2020] [Accepted: 03/14/2020] [Indexed: 12/31/2022] Open
Abstract
Background Education and learning are the most important goals of all universities. For this purpose, lecturers use various tools to grab the attention of students and improve their learning ability. Virtual reality refers to the subjective sensory experience of being immersed in a computer-mediated world, and has recently been implemented in learning environments. Objective The aim of this study was to analyze the effect of a virtual reality condition on students’ learning ability and physiological state. Methods Students were shown 6 sets of videos (3 videos in a two-dimensional condition and 3 videos in a three-dimensional condition), and their learning ability was analyzed based on a subsequent questionnaire. In addition, we analyzed the reaction of the brain and facial muscles of the students during both the two-dimensional and three-dimensional viewing conditions and used fractal theory to investigate their attention to the videos. Results The learning ability of students was increased in the three-dimensional condition compared to that in the two-dimensional condition. In addition, analysis of physiological signals showed that students paid more attention to the three-dimensional videos. Conclusions A virtual reality condition has a greater effect on enhancing the learning ability of students. The analytical approach of this study can be further extended to evaluate other physiological signals of subjects in a virtual reality condition.
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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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