Human static postures analysis using empirical mode decomposition.

Area of Science:

• Biomechanics
• Human postural control
• Physiological measurements

Background:

• Static posture stability is crucial for daily activities and rehabilitation.
• Conventional stabilometric analysis has limitations in capturing dynamic postural control.
• Understanding factors influencing human stability is essential for effective interventions.

Purpose of the Study:

• To analyze human stability during static postures using advanced signal processing of stabilometric data.
• To investigate the influence of visual input, feet position, age, and gender on postural stability.
• To introduce and validate a novel method for assessing postural stability.

Main Methods:

• Utilized stabilometric signals to measure center of pressure (CoP) displacements in Medio-Lateral (ML) and Antero-Posterior (AP) directions.
• Employed Empirical Mode Decomposition (EMD) to decompose stabilometric signals into Intrinsic Mode Functions (IMFs).
• Applied a stabilogram-diffusion method to calculate the Critical Point (CP) index for each IMF.

Main Results:

• The Critical Point (CP) parameter demonstrated significant differences across various groups.
• These significant differences were particularly notable in the Medio-Lateral (ML) direction.
• Factors influencing stability included visual modality, feet position, age, and gender.

Conclusions:

• The proposed Critical Point (CP) method offers a sensitive and effective approach to analyzing human postural stability.
• Findings highlight the impact of sensory-motor and demographic factors on static postural control.
• The results provide valuable insights that can guide the rehabilitation process for individuals with stability deficits.