2011
DOI: 10.1142/s0218127411030532
|View full text |Cite
|
Sign up to set email alerts
|

A Study of Chaotic Phenomena in Human-Like Reaching Movements

Abstract: In this paper, the feasibility of observing chaotic behavior in the model of a human arm is discussed. Two-Link Arm driven by Six Muscles (TLASM) which is a well-known model of planar human arm reaching movements in the horizontal plane is investigated. Reinforcement learning (RL) that is considered as a model for Dopamine-based learning in the brain is used to control the TLSAM. Finally, the existence of chaos phenomena in the TLASM model controlled with RL is researched using tools like bifurcation maps, Lya… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
5
0

Year Published

2012
2012
2023
2023

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 9 publications
(5 citation statements)
references
References 28 publications
0
5
0
Order By: Relevance
“…This type of signal is widely utilized in various applications such as bio-modeling, smart prostheses, and functional electrical stimulation [8] , [9] , [10] . To develop such models, it is necessary to first acquire the biological signals and extract their relevant features, which may vary depending on the specific modeling objectives [11] .One notable characteristic of biological signals is their non-forecasting and nonlinearity, which are also present in systems based on chaotic theory [12] , [13] , [14] , [15] . Consequently, many biological signals exhibit chaotic features as well [12] , [13] , [14] , [15] .…”
Section: Data Descriptionmentioning
confidence: 99%
See 1 more Smart Citation
“…This type of signal is widely utilized in various applications such as bio-modeling, smart prostheses, and functional electrical stimulation [8] , [9] , [10] . To develop such models, it is necessary to first acquire the biological signals and extract their relevant features, which may vary depending on the specific modeling objectives [11] .One notable characteristic of biological signals is their non-forecasting and nonlinearity, which are also present in systems based on chaotic theory [12] , [13] , [14] , [15] . Consequently, many biological signals exhibit chaotic features as well [12] , [13] , [14] , [15] .…”
Section: Data Descriptionmentioning
confidence: 99%
“…To develop such models, it is necessary to first acquire the biological signals and extract their relevant features, which may vary depending on the specific modeling objectives [11] .One notable characteristic of biological signals is their non-forecasting and nonlinearity, which are also present in systems based on chaotic theory [12] , [13] , [14] , [15] . Consequently, many biological signals exhibit chaotic features as well [12] , [13] , [14] , [15] . For instance, in natural conditions such as shifts in light intensity or the frequency of light switching on and off in front of a salamander's eye, the EMG signal can become chaotic [ 16 , 17 ].…”
Section: Data Descriptionmentioning
confidence: 99%
“…The examples illustrating wing rock and surge in jet engines [Lynch & Christopher, 1999] also involve multiple steady states made up of stable limit cycles. Chaotic phenomena in human-like reaching movements using a two-link arm mechanism driven by six muscles is described in [Rahatabad et al, 2011], where bifurcation maps, Lyapunov exponents and power spectra are employed to detect the chaos. In 1994, Webber and Zbilut applied recurrence plot strategies to assess physiological states such as respiration and muscle fatigue dynamically.…”
Section: The Periodically Forced Nonlinear Pendulummentioning
confidence: 99%
“…For this reason, recent studies on biological systems indicate that the structure and behavior of many of these systems, particularly the vital organs of the human body, are nonlinear, complex, and sometimes chaotic. [ 13 14 15 16 17 ] Furthermore, most biomarkers enter the chaos applying external stimuli. [ 18 19 ] Consequently, it is required to use a black box modeling to model the output EMG signal based on a specific nonlinear stimulation, including chaotic equations.…”
Section: Introductionmentioning
confidence: 99%