Influence of feet position on COP measures in post-stroke patients in quiet standing

Boumer, Tatiane Caroline; Martello, Suzane Ketlyn; Devetak, Gisele Francini; Iucksch, Dielise Debona; Scrok, Nicoly Dominique; Manffra, Elisängela Ferretti

doi:10.1016/j.gaitpost.2018.07.182

Cited by 9 publications

(7 citation statements)

References 23 publications

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“…Postural stability when standing has been frequently studied post-stroke using force platforms to measure the center of pressure (COP) trajectories [ 78 ]. In line with previous studies that have determined greater displacements of the COP in people with chronic stroke [ 79 , 80 ], our participating chronic stroke survivors also displayed higher values of COM displacement in the medial-lateral direction. This is an interesting result since balance recovery post-stroke is characterized by a reduction in postural sway and instability, particularly in the frontal balance plane [ 81 ].…”

Section: Discussionsupporting

confidence: 91%

Validity of an android device for assessing mobility in people with chronic stroke and hemiparesis: a cross-sectional study

Sánchez-Sánchez,

Ruescas-Nicolau,

Arnal-Gómez

et al. 2024

J NeuroEngineering Rehabil

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Background Incorporating instrument measurements into clinical assessments can improve the accuracy of results when assessing mobility related to activities of daily living. This can assist clinicians in making evidence-based decisions. In this context, kinematic measures are considered essential for the assessment of sensorimotor recovery after stroke. The aim of this study was to assess the validity of using an Android device to evaluate kinematic data during the performance of a standardized mobility test in people with chronic stroke and hemiparesis. Methods This is a cross-sectional study including 36 individuals with chronic stroke and hemiparesis and 33 age-matched healthy subjects. A simple smartphone attached to the lumbar spine with an elastic band was used to measure participants’ kinematics during a standardized mobility test by using the inertial sensor embedded in it. This test includes postural control, walking, turning and sitting down, and standing up. Differences between stroke and non-stroke participants in the kinematic parameters obtained after data sensor processing were studied, as well as in the total execution and reaction times. Also, the relationship between the kinematic parameters and the community ambulation ability, degree of disability and functional mobility of individuals with stroke was studied. Results Compared to controls, participants with chronic stroke showed a larger medial-lateral displacement (p = 0.022) in bipedal stance, a higher medial-lateral range (p < 0.001) and a lower cranio-caudal range (p = 0.024) when walking, and lower turn-to-sit power (p = 0.001), turn-to-sit jerk (p = 0.026) and sit-to-stand jerk (p = 0.001) when assessing turn-to-sit-to-stand. Medial-lateral range and total execution time significantly correlated with all the clinical tests (p < 0.005), and resulted significantly different between independent and limited community ambulation patients (p = 0.042 and p = 0.006, respectively) as well as stroke participants with significant disability or slight/moderate disability (p = 0.024 and p = 0.041, respectively). Conclusion This study reports a valid, single, quick and easy-to-use test for assessing kinematic parameters in chronic stroke survivors by using a standardized mobility test with a smartphone. This measurement could provide valid clinical information on reaction time and kinematic parameters of postural control and gait, which can help in planning better intervention approaches.

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Section: Discussionsupporting

confidence: 91%

Validity of an android device for assessing mobility in people with chronic stroke and hemiparesis: a cross-sectional study

Sánchez-Sánchez,

Ruescas-Nicolau,

Arnal-Gómez

et al. 2024

J NeuroEngineering Rehabil

View full text Add to dashboard Cite

show abstract

“…Recent studies have found that the global parameters of the stroke group (COP elliptical swing area and COP sway path length) are signi cantly larger than those of the healthy control group [18], indicating that the static balance of the stroke group is seriously damaged and shows obvious postural instability, which is consistent with previous research results [19]. Rahimzadeh et al analyzed the COP of stroke patients standing with EO and EC, and found that the sway range and sway speed of COP increased signi cantly during visual deprivation, indicating that the balance dysfunction caused by central nerve system damage was worse in the EC state, and also suggesting that the visual system played an important role in the balance control of stroke patients [20].…”

Section: Introductionsupporting

confidence: 88%

Automatic characterization of stroke patients’ posturography based on probability density analysis

Wang

Chen

et al. 2022

Preprint

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Objective The probability density analysis was applied to automatically characterize the center of pressure (COP) data for evaluation of the stroke patients’ balance ability. Methods The real-time COP coordinates of 38 stroke patients with eyes open and close during quiet standing were obtained respectively from a precision force platform. The COP data was analyzed and characterized by the commonly used parameters: total sway length (SL), sway radius (SR), envelope sway area (EA), and the probability density analysis based parameters: projection area (PA), skewness (SK) and kurtosis (KT), and their statistical correlations were analyzed. The differences of both conventional parameters and probability density parameters under the conditions of eyes open (EO) and eyes closed (EC) were compared.Results The PA from probability density analysis is strongly correlated with SL and SR. Both the traditional parameters and probability density parameters in the EC state are significantly different from those in the EO state. The obtained different statokinesigrams were calculated and categorized into typical sway types through probability density function for clinical evaluation of the balance ability of stroke patients. Conclusions The probability density analysis of COP data can be used to characterize the posturography for evaluation of the balance ability of stroke patients.

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“…Recent studies have found that the global parameters of the stroke group (COP elliptical swing area and COP sway path length) are significantly larger than those of the healthy control group [ 21 ], indicating that the static balance of the stroke group is seriously reduced and shows obvious postural instability, which is consistent with previous research results [ 22 ]. Rahimzadeh et al analyzed the COP of stroke patients standing with eyes open (EO) and eyes closed (EC), and found that the sway range and sway speed of COP increased significantly during visual deprivation, indicating that the balance dysfunction caused by central nerve system damage was worse in the EC state, and also suggesting that the visual system played an important role in the balance control of stroke patients [ 23 ].…”

Section: Introductionsupporting

confidence: 88%

Automatic characterization of stroke patients’ posturography based on probability density analysis

Wang

Chen

et al. 2023

BioMed Eng OnLine

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Objective The probability density analysis was applied to automatically characterize the center of pressure (COP) data for evaluation of the stroke patients’ balance ability. Methods The real-time COP coordinates of 38 stroke patients with eyes open and closed during quiet standing were obtained, respectively, from a precision force platform. The COP data were analyzed and characterized by the commonly used parameters: total sway length (SL), sway radius (SR), envelope sway area (EA), and the probability density analysis based parameters: projection area (PA), skewness (SK) and kurtosis (KT), and their statistical correlations were analyzed. The differences of both conventional parameters and probability density parameters under the conditions of eyes open (EO) and eyes closed (EC) were compared. Results The PA from probability density analysis is strongly correlated with SL and SR. Both the traditional parameters and probability density parameters in the EC state are significantly different from those in the EO state. The obtained various statokinesigrams were calculated and categorized into typical sway types through probability density function for clinical evaluation of the balance ability of stroke patients. Conclusions The probability density analysis of COP data can be used to characterize the posturography for evaluation of the balance ability of stroke patients.

show abstract

Influence of feet position on COP measures in post-stroke patients in quiet standing

Cited by 9 publications

References 23 publications

Validity of an android device for assessing mobility in people with chronic stroke and hemiparesis: a cross-sectional study

Validity of an android device for assessing mobility in people with chronic stroke and hemiparesis: a cross-sectional study

Automatic characterization of stroke patients’ posturography based on probability density analysis

Automatic characterization of stroke patients’ posturography based on probability density analysis

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