Biomedical subjects

Masaki Sekine

Publications and source records attributed to Masaki Sekine.

4 recordsLinked to original sources

PubMed2006

Improving the accuracy of pedometer used by the elderly with the FFT algorithm.

PURPOSE: The aim of this study was to investigate and improve the accuracy of accelerometer-type pedometers used by the elderly with slow walking speeds, with or without gait disorders, who do or do not use a cane. METHODS: Eighteen subjects walked with a cane (5 males, 13 females; age, 80.9 +/- 7.7 yr; height, 148.1 +/- 7.7 cm; weight, 51.8 +/- 8.8 kg (mean +/- SD); nine had impaired gait), and 31 subjects walked without a cane (7 males, 24 females; age, 80.9 +/- 7.7 yr; height, 148.1 +/- 7.7 cm; weight, 51.8 +/- 8.8 kg; 15 had impaired gait). Subjects walked for approximately 20 m (10 m in each direction and a turning arc) at their own speed. We determined the number of steps by pedometer (PM), by visually counting the actual number of steps (RM), and by the triaxial acceleration signals. The power spectrum of the accelerometer in each direction calculated by fast Fourier transform (FFT) for a 4-s temporal window was normalized with the maximum power of each window. It was composited, and the frequency at maximum power was considered as the cadence. The number of steps taken (FM) was determined by summing all the estimated steps in each window. RESULTS: PM was significantly less than the RM (P < 0.05), and the error of PM was 53.2 +/- 34.1% of RM. FM did not differ from the RM, and the average error of FM was -0.7 +/- 7.9% of RM (absolute value: 5.8 +/- 5.3%). CONCLUSION: We suggest that our FFT method is suitable for estimating the number of steps during walking in this population.

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PubMed2004

Fractal dynamics of body motion in patients with Parkinson's disease.

In this paper, we assess the complexity (fractal measure) of body motion during walking in patients with Parkinson's disease. The body motion of 11 patients with Parkinson's disease and 10 healthy elderly subjects was recorded using a triaxial accelerometry technique. A triaxial accelerometer was attached to the lumbar region. An assessment of the complexity of body motion was made using a maximum-likelihood-estimator-based fractal analysis method. Our data suggest that the fractal measures of the body motion of patients with Parkinson's disease are higher than those of healthy elderly subjects. These results were statistically different in the X (anteroposterior), Y (lateral) and Z (vertical) directions of body motion between patients with Parkinson's disease and the healthy elderly subjects (p < 0.01 in X and Z directions and p < 0.05 in Y direction). The complexity (fractal measure) of body motion can be useful to assess and monitor the output from the motor system during walking in clinical practice.

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PubMed2004

The effects of maturation on early and late phases of phrenic neurogram during eupnea.

In this paper, we investigate the effects of maturation on the early and late phases of the phrenic neurogram. We have used the matching pursuit (MP) method to examine the effects of maturation on breathing patterns in both time and frequency domains. The MP was chosen since the wavelet transform method may not represent signals whose Fourier transforms have a narrow high-frequency support. The phrenic neurogram was recorded from 25 piglets (3-35 days) during eupnea (normal breathing) at three postnatal age groups: young (3-7 days (n = 9)), (middle) 10-21 days (n = 6), and old (29-35 days (n = 10)). The energy percentage of atoms representing the nonperiodic neural activities (NPNAs) significantly decreased from young age to middle age groups (p<0.01) and from young age to old age groups (p<0.01), and from middle age to old age groups (p<0.055) in the early phase (the first half) of the phrenic neurogram, but these changes were not statistically significant in the late phase (the second half) of the phrenic neurogram as maturation proceeded. However, the energy percentage of atoms representing the periodic neural activities (PNAs) decreased with maturation, but these changes were not statistically significant in the early phase of the phrenic neurogram. The energy percentage of (PNAs) increased in the late phase of the phrenic neurogram as maturation proceeded although these changes were only significant between young and old age groups (p<0.01). These results suggest that the significant decrease of the NPNAs in the early phase and the increase in the late phase of the phrenic neurogram could be a sign of maturation in piglets.

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PubMed2002

Discrimination of walking patterns using wavelet-based fractal analysis.

In this paper, we attempted to classify the acceleration signals for walking along a corridor and on stairs by using the wavelet-based fractal analysis method. In addition, the wavelet-based fractal analysis method was used to evaluate the gait of elderly subjects and patients with Parkinson's disease. The triaxial acceleration signals were measured close to the center of gravity of the body while the subject walked along a corridor and up and down stairs continuously. Signal measurements were recorded from 10 healthy young subjects and 11 elderly subjects. For comparison, two patients with Parkinson's disease participated in the level walking. The acceleration signal in each direction was decomposed to seven detailed signals at different wavelet scales by using the discrete wavelet transform. The variances of detailed signals at scales 7 to 1 were calculated. The fractal dimension of the acceleration signal was then estimated from the slope of the variance progression. The fractal dimensions were significantly different among the three types of walking for individual subjects (p < 0.01) and showed a high reproducibility. Our results suggest that the fractal dimensions are effective for classifying the walking types. Moreover, the fractal dimensions were significantly higher for the elderly subjects than for the young subjects (p < 0.01). For the patients with Parkinson's disease, the fractal dimensions tended to be higher than those of healthy subjects. These results suggest that the acceleration signals change into a more complex pattern with aging and with Parkinson's disease, and the fractal dimension can be used to evaluate the gait of elderly subjects and patients with Parkinson's disease.

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