Variations in Anterior-Posterior CoP Patterns in Elderly Adults Between Psychophysically Detected and Non-Detected Short Horizontal Perturbations

Emergence of Lissajous Patterns as a Function of a Perturbation Frequency in Postural Responses to the Short Sinusoidal Translations of Varying Frequencies

The existence of in-phase and anti-phase postural responses to sinusoidal perturbations to the base of support is well known. In this study, we investigate if such coordinated postural responses exist at 'near-sway' perturbations where the perturbation amplitudes are kept within the range of normal sway lengths in healthy adults (n=10). The postural responses are analyzed via bursts of anterior-posterior (AP) 2.5 mm horizontal sinusoidal oscillations of the base of support at sequentially varying frequencies (0.25, 0.375, 0.5, 0.625, 0.75, 1 and 1.25 Hz). The parametric plots of the perturbation signal (platform position) and the response profiles (AP Center of Pressure [APCoP]) show the emergence of elliptical Lissajous patterns as the perturbation frequency is increased from 0.25 Hz to 1.25 Hz. The presence of such characteristic pattern shows the 'lock-in' behavior of APCoP with perturbation signal. These elliptical patterns become more apparent at the center frequencies (0.375 to 0.75 Hz). At the higher frequencies (1 and 1.25 Hz), the Lissajous patterns do exist but are dominated by low-frequency drift. The area and orientation of Lissajous patterns and the phase shifts between perturbation and APCoP show a strong nonlinear decreasing trend with increasing perturbation frequency for both, young (n=5) as well as mature (n=5) adults within the study group. This may suggest that such characteristic, frequency-locked, phased shifted response of healthy posture control could be a fundamental property of a healthy posture control's response to 'near-sway' sinusoidal translations in AP direction.

Classification of body movements based on posturographic data

The human body, standing on two feet, produces a continuous sway pattern. Intended movements, sensory cues, emotional states, and illnesses can all lead to subtle changes in sway appearing as alterations in ground reaction forces and the body's center of pressure (COP). The purpose of this study is to demonstrate that carefully selected COP parameters and classification methods can differentiate among specific body movements while standing, providing new prospects in camera-free motion identification. Force platform data were collected from participants performing 11 choreographed postural and gestural movements. Twenty-three different displacement- and frequency-based features were extracted from COP time series, and supplied to classification-guided feature extraction modules. For identification of movement type, several linear and nonlinear classifiers were explored; including linear discriminants, nearest neighbor classifiers, and support vector machines. The average classification rates on previously unseen test sets ranged from 67% to 100%. Within the context of this experiment, no single method was able to uniformly outperform the others for all movement types, and therefore a set of movement-specific features and classifiers is recommended.

Categorizing and comparing psychophysical detection strategies based on biomechanical responses to short postural perturbations

Background

A fundamental unsolved problem in psychophysical detection experiments is in discriminating guesses from the correct responses. This paper proposes a coherent solution to this problem by presenting a novel classification method that compares biomechanical and psychological responses.

Methods

Subjects (13) stood on a platform that was translated anteriorly 16 mm to find psychophysical detection thresholds through a Adaptive 2-Alternative-Forced-Choice (2AFC) task repeated over 30 separate sequential trials. Anterior-posterior center-of-pressure (APCoP) changes (i.e., the biomechanical response R_B) were analyzed to determine whether sufficient biomechanical information was available to support a subject's psychophysical selection (R_Ψ) of interval 1 or 2 as the stimulus interval. A time-series-bitmap approach was used to identify anomalies in interval 1 (a₁) and interval 2 (a₂) that were present in the resultant APCoP signal. If a₁ > a₂ then R_B = Interval 1. If a₁ < a₂, then R_B= Interval 2. If a₂ - a₁ < 0.1, R_B was set to 0 (no significant difference present in the anomaly scores of interval 1 and 2).

Results

By considering both biomechanical (R_B) and psychophysical (R_Ψ) responses, each trial run could be classified as a: 1) HIT (and True Negative), if R_B and R_Ψ both matched the stimulus interval (SI); 2) MISS, if R_B matched SI but the subject's reported response did not; 3) PSUEDO HIT, if the subject signalled the correct SI, but R_B was linked to the non-SI; 4) FALSE POSITIVE, if R_B = R_Ψ, and both associated to non-SI; and 5) GUESS, if R_B = 0, if insufficient APCoP differences existed to distinguish SI. Ensemble averaging the data for each of the above categories amplified the anomalous behavior of the APCoP response.

Conclusions

The major contributions of this novel classification scheme were to define and verify by logistic models a 'GUESS' category in these psychophysical threshold detection experiments, and to add an additional descriptor, "PSEUDO HIT". This improved classification methodology potentially could be applied to psychophysical detection experiments of other sensory modalities.

A biomechanical model of human ankle angle changes arising from short peri-threshold anterior translations of platform on which a subject stands

This study modeled ankle angle changes during small forward perturbations of a standing platform. A two-dimensional biomechanical inverted pendulum model was developed that uses sway frequencies derived from quiet standing observations on a subject's Anterior Posterior Center of Pressure (APCoP) to track ankle angle changes during a 16 mm anterior displacement perturbation of a platform on which a subject stood. This model used the total torque generated at the ankle joint as one of the inputs, and calculated it assuming a PID controller. This feedback system generated a simulated ankle torque based on the angular position of the center of mass (CoM) with respect to vertical line passing through the ankle joint. This study also assumed that the internal components of the net torque were only a controller torque and a sway-pattern-generating torque. The final inputs to the model were the platform acceleration and anthropometric terms. This model of postural sway dynamics predicted sway angle and the trajectory of the center of mass. Knowing these relationships can advance an understanding of the ankle strategy employed in balance control.

Amplitude demodulation of entrained sway to analyze human postural control

This paper presents an innovative technique to study postural control. Our translating platform, the Sliding Linear Investigative Platform For Analyzing Lower Limb Stability and Simultaneous Tracking, EMG and Pressure mapping (SLIP-FALLS-STEPm), makes precise, vibration movements under controlled conditions. We look at the psychophysical thresholds to the perception of a sinusoidally induced sway. In the Sine Lock experiments described, an induced sinusoidal perturbation locks the subject's natural sway pattern at the frequency of the perturbation. The input / output system is treated as an Amplitude Shift Key (ASK) modulated signal modulating a carrier frequency (at or about a subject's natural sway frequency). The Position signal (input) and the Anterior-Posterior Center of Pressure (APCOP) signal (output) or the ankle angle are demodulated by mixing them with the pure sine wave carrier at the frequency of underlying oscillation and then low-pass filtering it to detect the amplitude envelope. These detected envelopes elucidate that the square pulse increase in the position sine wave amplitude yields a triangular increase in APCOP demodulated signal.