Assessment of postural stability using the Zebris Platform in women above the age of 60

Jaworski, Janusz; Kołodziej, Ewelina

doi:10.5604/01.3001.0014.8210

Cited by 2 publications

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“…group and comparison were made based on their COP sway parameters. The result suggested that the older group had a lower level of postural stability compared to the younger group(Jaworski & Kołodziej, 2020).Nevertheless, the force platform has been reported to suffer from several limitations such as high cost (around £11,529), weight (around 10 kg for only the platform), considerable testing area (around 2.5 square metre), difficulty to transport, difficult of use, lack of sensitivity to the weight of children (Estévez-Pedraza et al, 2020; Rodríguez-Rubio et al 2020). Matłosz et al (2020) compared three different and commonly used force platforms among 111 young healthy adult subjects.…”

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Computerised accelerometric machine learning techniques and statistical developments for human balance analysis

Ojie¹

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Balance maintenance is crucial to participating in the activities of daily life. Balance is often considered as the ability to maintain the centre of mass (COM) position within the base of support. Primarily, to maintain balance, reliance is placed on the balance related sensory systems i.e., the visual, proprioceptive and vestibular. Several factors can affect a person’s balance such as neurological diseases, ageing, medication and obesity etc. To gain insight into the balance operations, studies rely on statistical and machine learning techniques. Statistical techniques are used for inferencing while machine learning techniques proved effective for interpretation. The focus of this study was on the issues encountered in human balance analysis such as the quantification of balance by relevant features, the relationships between COM and ground projected body sway, the performance of various sensory systems in balance analysis, and their relationships between the directions of body sway (i.e., mediolateral (ML) and anteriorposterior (AP)). A portable wireless accelerometry device was developed, balance analysis methods based on the inverted pendulum were devised and evaluated for their accuracy and reliability against a setup designed to allow manual balance measurements. Balance data were collected from 23 healthy adult subjects with the mean (standard deviation) of the age, height and weight: 24.5 (4.0) years, 173.6 (6.8) cm, and 72.7 (9.9) kg respectively. The accelerometry device was attached to the subjects at the approximate position of the illac crest, while they performed 30 seconds trials of the four conditions associated with a standard balance test called the modified Clinical Test of Sensory Interaction and Balance (mCTSIB). These required standing on a hard (ground) surface with the eyes open, standing on hard surface with the eyes closed, standing on a compliant surface (sponge, 10 cm thick) with the eyes open and standing on a compliant surface with the eyes closed. Statistical and machine learning techniques such as t-test, Wilcoxon signed-rank test, the Mann-Whitney U test, Analysis of variance (ANOVA), Kruskal-Wallis test, Friedman test, correlation analysis, linear regression, Bland and Altman analysis, principal component analysis (PCA), K-means clustering, and Kohonen neural network (KNN) were employed for interpreting the measurements. The findings showed close agreement between the developed balance analysis methods and the related measurements from the manual setup for balance analysis. The COM was observed to be responsible for differing amount of sway across the subjects and could affect both the angle and ground projected sway. The AP direction was more sensitive to sway than the ML direction. The subjects were observed to depend more on their proprioceptive system to control balance. The proprioceptive system was observed to have a greater impact in controlling the AP velocity of the subjects as compared to their visual system. The proprioceptive system had no impact on the ML velocity. The visual system was responsible for the control of the ML velocity and for reducing the acceleration in both directions. It was concluded that for comparison of postural sway information, subjects with closely related COM positions should be compared, comparison should be carried out in respect to the base of their support. The sway normalisation by dividing with COM position should be performed to reduce the obscuring effect of the COM. Enhancement of the proprioceptive system should be carried out to reduce the AP velocity while enhancement of the visual system should be used to reduce the ML sway and acceleration in ML and AP directions. The velocity in the AP direction should be used to examine the performance of the proprioceptive system while the ML velocity and acceleration should be used for the visual system. The vestibular system characterised sway more in the AP direction, and hence, the AP direction should be used to examine its performance in balance.

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Computerised accelerometric machine learning techniques and statistical developments for human balance analysis

Ojie¹

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The Effects of Different Breathing Techniques on Lower Extremity Muscle Function and Postural Stability

Baek,

Shin,

Lee

2024

Asian J Kinesiol

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OBJECTIVES This study examines the effects of bracing versus hollowing breathing techniques on lower limb muscle function and postural stability, aiming to identify the most effective breathing strategy for functional movement.METHODS Conducted on ten healthy males in their twenties without back or musculoskeletal issues, the study involved pre-experiment training in both breathing techniques. It assessed maximal strength, endurance, and power during knee flexion and extension, alongside postural stability, with both eyes open and closed, using the non-parametric Wilcoxon signed-rank test for analysis.RESULTS Except for certain specific measurements (right flexor muscle peak torque, left flexor muscle total work, and right extensor muscle power), statistical analysis showed significant differences in Knee muscle function favoring the bracing technique (p<.05). While postural stability tests showed no significant overall differences between the techniques, an observable trend emerged: the hollowing group showed superior performance in one-foot balance tasks, whereas the bracing group demonstrated better outcomes in two-footed stances.CONCLUSIONS It is anticipated that bracing breathing will positively influence muscle training, surpassing the effects of hollowing by bolstering the strength, endurance, and power of the lower limbs. However, for postural stability, the hollowing technique may offer advantages in tasks requiring higher balance acuity, like one-legged standing. In contrast, bracing appears more effective for simpler stability tasks. These findings underscore breathing techniques' role in physical performance, highlighting the need for further, detailed research considering posture and musculoskeletal influences.

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Assessment of postural stability using the Zebris Platform in women above the age of 60

Cited by 2 publications

References 3 publications

Computerised accelerometric machine learning techniques and statistical developments for human balance analysis

Computerised accelerometric machine learning techniques and statistical developments for human balance analysis

The Effects of Different Breathing Techniques on Lower Extremity Muscle Function and Postural Stability

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