A phase-locked loop model of the response of the postural control system to periodic platform motion

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.

Phase-locked loop for precisely timed acoustic stimulation during sleep

BACKGROUND

A brain-computer interface could potentially enhance the various benefits of sleep.

NEW METHOD

We describe a strategy for enhancing slow-wave sleep (SWS) by stimulating the sleeping brain with periodic acoustic stimuli that produce resonance in the form of enhanced slow-wave activity in the electroencephalogram (EEG). The system delivers each acoustic stimulus at a particular phase of an electrophysiological rhythm using a phase-locked loop (PLL).

RESULTS

The PLL is computationally economical and well suited to follow and predict the temporal behavior of the EEG during slow-wave sleep.

COMPARISON WITH EXISTING METHODS

Acoustic stimulation methods may be able to enhance SWS without the risks inherent in electrical stimulation or pharmacological methods. The PLL method differs from other acoustic stimulation methods that are based on detecting a single slow wave rather than modeling slow-wave activity over an extended period of time.

CONCLUSIONS

By providing real-time estimates of the phase of ongoing EEG oscillations, the PLL can rapidly adjust to physiological changes, thus opening up new possibilities to study brain dynamics during sleep. Future application of these methods hold promise for enhancing sleep quality and associated daytime behavior and improving physiologic function.

Analysis of human standing balance by largest lyapunov exponent

The purpose of this research is to analyse the relationship between nonlinear dynamic character and individuals' standing balance by the largest Lyapunov exponent, which is regarded as a metric for assessing standing balance. According to previous study, the largest Lyapunov exponent from centre of pressure time series could not well quantify the human balance ability. In this research, two improvements were made. Firstly, an external stimulus was applied to feet in the form of continuous horizontal sinusoidal motion by a moving platform. Secondly, a multiaccelerometer subsystem was adopted. Twenty healthy volunteers participated in this experiment. A new metric, coordinated largest Lyapunov exponent was proposed, which reflected the relationship of body segments by integrating multidimensional largest Lyapunov exponent values. By using this metric in actual standing performance under sinusoidal stimulus, an obvious relationship between the new metric and the actual balance ability was found in the majority of the subjects. These results show that the sinusoidal stimulus can make human balance characteristics more obvious, which is beneficial to assess balance, and balance is determined by the ability of coordinating all body segments.

Empirical mode decomposition/Hilbert transform analysis of postural responses to small amplitude anterior-posterior sinusoidal translations of varying frequencies

Bursts of 2.5mm horizontal sinusoidal anterior-posterior oscillations of sequentially varying frequencies (0.25 to 1.25 Hz) are applied to the base of support to study postural control. The Empirical Mode Decomposition (EMD) algorithm decomposes the Center of Pressure (CoP) data (5 young, 4 mature adults) into Intrinsic Mode Functions (IMFs). Hilbert transforms are applied to produce each IMF's time-frequency spectrum. The most dominant mode in total energy indicates a sway ramble with a frequency content below 0.1 Hz. Other modes illustrate that the stimulus frequencies produce a 'locked-in' behavior of CoP with platform position signal. The combined Hilbert Spectrum of these modes shows that this phase-lock behavior of APCoP is more apparent for 0.5, 0.625, 0.75 and 1 Hz perturbation intervals. The instantaneous energy profiles of the modes depict significant energy changes during the stimulus intervals in case of lock-in. The EMD technique provides the means to visualize the multiple oscillatory modes present in the APCoP signal with their time scale dependent on the signals's successive extrema. As a result, the extracted oscillatory modes clearly show the time instances when the subject's APCoP clearly synchronizes with the provided sinusoidal platform stimulus and when it does not.