Wavelet Decomposition in Analysis of Impact of Virtual Reality Head Mounted Display Systems on Postural Stability

Wodarski, P.; Jurkojć, Jacek; Gzik, M.

doi:10.3390/s20247138

Cited by 17 publications

(25 citation statements)

References 23 publications

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“…As a result, it causes the deviation of the COP time series and obscures the characteristics of human changes. WT can precisely assess the dissimilarities of human movement and balance control capability [ 24 ], can respond to different time scales under diverse time characteristics [ 9 ], and can also show the postural control mechanism at dissimilar time scales [ 25 ]. Additionally, WT can not only analyse the energy of COP displacement in a specific time period to illustrate the present problems in posture control [ 26 ] but can also quantify the multi-resolution spectrum of COP displacement signal to depict the smoothness and diversity of the fractal structure of the signal [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

“…The transform changes the real-time sequence signal s ( t ) into a two-dimensional real space with variables a and b . The wavelet coefficients (WC) at time scale a and time b are estimated using Equation (4) [ 9 ]:

where s ( t ) represents the time series signal; “*” represents the complex conjugate; and ψ is the wavelet function. The ‘child wavelet’ derived from the ‘mother wavelet’ is as shown in Equation (5):

…”

Section: Methodsmentioning

confidence: 99%

“…As a comprehensive variable, it reflects limb sway and posture balance control ability [ 8 ]. COP signal is unstable and nonlinear [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…Many more studies have shown that postural control is attained by visual, proprioceptive, and vestibular sensory organs, while the dynamic alterations of the postural control system cannot be assessed effectively if people only assess the swing amplitude and disregard the overall change by decreasing the change in postural control. Thus, higher evaluation methods are required to measure the dynamic changes in the postural control system [ 9 ]. The nonlinear time-domain and frequency-domain method, which is based on the concepts of chaos, fractals, and complexity [ 10 ], has been used to evaluate COP signals.…”

Section: Introductionmentioning

confidence: 99%

“…In recent times, the majority of studies have utilised nonlinear time series analysis methods to analyse COP. Some researchers instead argue that complex postural control is more stable and adaptable [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

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Study on the Difference of Human Body Balance Stability Regulation Characteristics by Time-Frequency and Time-Domain Data Processing Methods

Cui

Liu

et al. 2022

IJERPH

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This paper aims to investigate the differences in standing balance control ability between freestyle skiing aerials athletes and ordinary graduate students by means of wavelet transform (WT) and the overall stability index (OSI) and to discover the characteristics of the postural control ability of dissimilar subjects and appropriate methods to assess the postural control ability of the human body. Research Methods: In all, 16 subjects were tested, including 8 from the Chinese national team who had won the world championships of freestyle skiing aerials, with 10+ years of training (age: 23 ± 23.1 years, Height: 176 ± 2.1 cm, and weight: 69 ± 3.5 kg), and 8 ordinary graduate students of Shenyang Institute of Physical Education (age: 22.6 ± 4.6 years, Height: 179 ± 3.3 cm, and weight: 73 ± 4.1 kg). When performing the tasks, the research subjects were required to stand on the steady support surface (with eyes closed and legs closed) for 30 s in each testing. The displacement data of the anteroposterior (AP) direction and the mediolateral (ML) direction of their centre of pressure (COP) were recorded. Then, WT and OSI were calculated. Two dissimilar methods were compared to analyse the characteristics of balance ability. Results: (1) The athletes’ WT values in the AP direction and the ML direction were concentrated in the interval of 22~30 s and 0–8 s, respectively, while the ordinary graduate students’ WT values in the AP direction and the ML direction were concentrated in the interval of 10~25 s and 0–7 s, respectively; (2) the WT values of the regular graduate students in the AP direction and the ML direction were higher than those of the athletes (p < 0.01); and (3) the OSI value in the AP direction of the athletes was higher than of the ordinary graduate students, while the OSI value in the ML direction of the athletes was lower than that of regular graduate students. Conclusion: Compared to the OSI, WT can analyse the characteristics of balance control ability more effectively. The COP displacement frequencies of the athletes and ordinary graduate students were concentrated in the low-frequency bands. The athletes had superior adjustment ability in an imbalanced state and could adjust to the best position without effort. In addition, the athletes had a stronger adaptive ability. In comparison, the ordinary graduate students had comparatively poor adaptive ability and weak adjustment ability in the imbalanced state, so it was difficult for them to attain the best angle after adjustment.

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