Abstract. [Purpose] We have proposed in a previous paper a novel indicator of smoothness using the power spectrum entropy of acceleration time-series during movement. In this paper, we describe this indicator's ability to distinguish between fallers' and non-fallers' gait in community dwelling elderly. This novel indicator is simple to use and can directly evaluate gait.[Subjects] Two hundred and fifty-one subjects (age = 71.0 ± 7.7) were categorized fallers (39) and non-fallers (191) based on their histories (21 were unknown).[Methods] Grip strength, walking speed and the functional reach test, were used as convenient indicators, and the entropy of spectrum of acceleration during gait were measured and compared between fallers and non-fallers.[Results] Significant differences were found in the entropy of the fastest gait as well as in the other indices (p<.05). We also examined the correlation between entropy and grip strength (Spearman's ρ = -.35, p<.01). Correlations of entropy with the other indices were also low.[Conclusion] These results imply that entropy provides useful information, not found in the other indices, on body function in relation to falling.

We propose a novel indicator for smoothness of movement, i.e., the power spectrum entropy of the acceleration time-series, and compare it with conventional indices of smoothness. For this purpose, nineteen healthy adults (21.3+/-2.5 years old) performed the task of raising and lowering a beaker between the level of the umbilicus and eye level under the two following conditions: one with the beaker containing water and the other with the beaker containing a weight of the same mass as the water. Moving the beaker up and down when it contained water required extra control to prevent the water from being spilled. This means that movement was not as smooth as when the beaker contained a weight. Under these two conditions, entropy was measured along with a traditional indicator of smoothness of movement, the jerk index. The entropy could distinguish just as well as the jerk index (p<0.01) between when water was used and when the weight was used. The entropy correlated highly with the jerk index, with Spearman's rho at 0.88 (p<0.01). These results showed that the entropy derived from the spectrum of the acceleration time-series during movement is useful as an indicator of the smoothness of that movement.

Abstract.[Purpose] The purpose of this study was to verify a method of spectral analysis of stride-tostride variability, and to apply this method to the analysis of the gait pattern of patients with Parkinson's disease.[Subjects] Ten healthy young individuals, ten community-dwelling elderly individuals and nine individuals with Parkinson's disease were recruited.[Methods] To quantitatively evaluate stride-to-stride variability, we used fast Fourier transform, calculated the power spectrum, and separated it into three frequency ranges. We plotted a double-log graph for the power spectrum and calculated the slope of the line using least-squares regression. For each of the participants we measured 10-meter walking speed, stride-to-stride variability, and disease severity (only Parkinson's disease).[Results] Each of three ranges of the power spectrum was four times larger for Parkinson's disease patients than for the healthy groups (p < 0.05). The severity of Parkinson's disease correlated significantly with the very low frequency range (0.01-0.05 Hz) of the power spectrum (r = 0.767, p = 0.0159) and the scaling factor β of the power spectrum (r = 0.850, p = 0.0037). [Conclusion] This method of spectral analysis of stride-to-stride variability may be useful for gait analysis of patients with Parkinson's.

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