Understanding the mechanisms behind human balance has been a subject of interest as various postural instabilities have been linked to neuromuscular diseases (Parkinson’s, multiple sclerosis, and concussion). This paper presents a classification method for an individual’s postural stability and estimation of their neuromuscular feedback control parameters. The method uses a generated topological mapping between a subjects experimental data and a data set consisting of time series realizations generated using an inverted pendulum mathematical model of upright balance. The performance of the method is quantified using a time series realizations with known stability and neuromuscular control parameters. The method was found to have an overall sensitivity of 85.1% and a specificity of 91.9%. Furthermore, the method was most accurate when identifying limit cycle oscillations with a sensitivity of 91.1% and a specificity of 97.6%. Such a method has the capability of classifying an individual’s stability and revealing possible neuromuscular impairment related to balance control, ultimately providing useful information to clinicians for diagnostic and rehabilitation purposes.

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