A new methodology based on functional principal component analysis to study postural stability post-stroke

Sánchez-Sánchez, M. Luz; Belda-Lois, Juan-Manuel; Horno, Silvia Mena-del; Viosca-Herrero, Enrique; Camacho, Celedonia Igual; Gisbert-Morant, Beatriz

doi:10.1016/j.clinbiomech.2018.05.003

Cited by 9 publications

(4 citation statements)

References 34 publications

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“…Additionally, this study employed time-series principal component analysis and observed significant differences in the fourth principal component of the rectus femoris muscle. Action recognition scoring and research related to time-series principal component analysis have gradually matured (Xiaolin Liu er ai., 2023) and have been widely applied in studies such as movement development, movement technique analysis (Huijie et al, 2012), sports injury diagnosis (Donoghue et al, 2008;Epifanio et al, 2008), and rehabilitation outcome assessment (Sánchez-Sánchez et al, 2018). This study identified the fourth principal component of the rectus femoris muscle as a sensitive indicator for action recognition.…”

Section: Trapezius Muscle Key Force Phase Recognitionmentioning

confidence: 95%

Effects of muscle strength in different parts of adolescent standing long jump on distance based on surface electromyography

Wang,

Dong

2023

Front. Physiol.

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Objective: To reveal the influence of muscle strength in different parts of the body on the distance of standing jump, to establish the key force phases of muscle strength in different parts, and to improve the recognition of movement norms.Methods: VICON infrared three-dimensional motion capture acquisition and analysis system and Noraxon Ultium surface electromyography acquisition and analysis system were used to complete the surface electromyography signal acquisition of 18 randomly selected subjects performing standing long jump.Results: 1) Triceps brachii, anterior deltoid, latissimus dorsi, semitendinosus, rectus femoris, upper trapezius, pectoralis major, and biceps femoris had significant effects on standing jump distance. 2) From the point of view of the key exertion phase of the standing jump mainly affecting the muscle group; the main exertion phase of the semitendinosus occurs from the rising stage to the descending stage; the rectus femoris, triceps, and latissimus dorsi occur during the ascending phase of the flight; the anterior deltoid muscle occurs in the transition stage from rising to falling in the air; the trapezius muscle occurs in the transition stage from pre-swing to kick-off.Conclusion: 1) From the regression analysis of the measured muscles on the distance of each stage of standing long jump, deltoid muscle strength is conducive to the improvement of standing long jump distance, which further indicates the importance of upper limb deltoid muscle strength. 2) Through time series analysis, it is found that the force performance of the rectus femoris muscle at this stage can be used as the main identification parameter of standing long jump, and can effectively distinguish different types of movements.

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Section: Trapezius Muscle Key Force Phase Recognitionmentioning

confidence: 95%

Effects of muscle strength in different parts of adolescent standing long jump on distance based on surface electromyography

Wang,

Dong

2023

Front. Physiol.

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“…Connected with the current trend of increasing age of the population [ 2 , 3 ], this has led to a rise in pathologies that affect balance, causing an increased risk of falls in the elderly population. Around 30% of people aged over 65 years, and more than 50% of individuals in health centers or care homes suffer one or more falls per year, and between approximately 20% and 30% of the global population has had or will have a vertiginous episode in their lives [ 4 , 5 , 6 , 7 , 8 , 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Applying the Minimal Detectable Change of a Static and Dynamic Balance Test Using a Portable Stabilometric Platform to Individually Assess Patients with Balance Disorders

Torre

Marín

Polo³

et al. 2020

Healthcare

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Balance disorders have a high prevalence among elderly people in developed countries, and falls resulting from balance disorders involve high healthcare costs. Therefore, tools and indicators are necessary to assess the response to treatments. Therefore, the aim of this study is to detect relevant changes through minimal detectable change (MDC) values in patients with balance disorders, specifically with vertigo. A test-retest of a static and dynamic balance test was conducted on 34 healthy young volunteer subjects using a portable stabilometric platform. Afterwards, in order to show the MDC applicability, eight patients diagnosed with balance disorders characterized by vertigo of vestibular origin performed the balance test before and after a treatment, contrasting the results with the assessment by a specialist physician. The balance test consisted of four tasks from the Romberg test for static balance control, assessing dynamic postural balance through the limits of stability (LOS). The results obtained in the test-retest show the reproducibility of the system as being similar to or better than those found in the literature. Regarding the static balance variables with the lowest MDC value, we highlight the average velocity of the center of pressure (COP) in all tasks and the root mean square (RMS), the area, and the mediolateral displacement in soft surface, with eyes closed. In LOS, all COP limits and the average speed of the COP and RMS were highlighted. Of the eight patients assessed, an agreement between the specialist physician and the balance test results exists in six of them, and for two of the patients, the specialist physician reported no progression, whereas the balance test showed worsening. Patients showed changes that exceeded the MDC values, and these changes were correlated with the results reported by the specialist physician. We conclude that (at least for these eight patients) certain variables were sufficiently sensitive to detect changes linked to balance progression. This is intended to improve decision making and individualized patient monitoring.

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“…Consequently, the applications of functional data analysis techniques have been successfully implemented in many different fields during the last years, for examples, environment and ecology (Gao and Niemeie 2008;Ikeda et al 2008;Torres et al 2010;Sierra et al 2017;Dennis et al 2019), hydrology and metrology (Berrendero et al 2011;Suhaila et al 2011;Chebana et al 2012;Suhaila and Yusop 2016;Beyaztas and Yaseen 2019;Hael et al 2020), in economics and finance (Müller et al 2011;Feng and Qian 2018), demography (Hyndman and Booth 2008;Hyndman and Shang 2010;Han et al 2018), and science and biomedicine (Illian et al 2009;Sánchez-Sánchez et al 2018;Granato et al 2018;Reiss and Xu 2019). For more details, (Ullah and Finch 2013) prepared a systematic review to identify FDA application studies in many different areas.…”

Section: Introductionmentioning

confidence: 99%

Modeling of rainfall variability using functional principal component method: a case study of Taiz region, Yemen

Hael

2020

Model. Earth Syst. Environ.

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The sophisticated functional techniques can efficiently analyze and model various earth systems, such as the climate change system. The major objective of this study is to adapt the functional principal component analysis (FPCA) method for rainfall data to capture the variations over time intervals and establish a functional model of the rainfall patterns. Furthermore, this work contributes to discovering and modeling the main rainfall features. It could be useful for a better understanding of the Taiz region's rainfall regime during the past 2 decades. The analysis was conducted according to the average monthly rainfall of the Taiz region from 1998 to 2019 and processed using R software. The proposed approach of functional principal components has been successfully carried out and demonstrated significant findings for rainfall patterns and temporal variations. According to the results of the current study, the first four functional principal components illustrated 33%, 23.3%, 17.3%, and 13.3% of the total variance of the rainfall variability, respectively. Moreover, the FPCs model showed that the amount of rainfall over the Taiz region during the last 2 decades has influenced by the monsoonal intertropical and Red Sea convergence zones.

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A new methodology based on functional principal component analysis to study postural stability post-stroke

Cited by 9 publications

References 34 publications

Effects of muscle strength in different parts of adolescent standing long jump on distance based on surface electromyography

Effects of muscle strength in different parts of adolescent standing long jump on distance based on surface electromyography

Applying the Minimal Detectable Change of a Static and Dynamic Balance Test Using a Portable Stabilometric Platform to Individually Assess Patients with Balance Disorders

Modeling of rainfall variability using functional principal component method: a case study of Taiz region, Yemen

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