Acceleration patterns of the head and pelvis when walking on level and irregular surfaces

Menz, Hylton B.; Lord, Stephen R.; Fitzpatrick, Richard C.

doi:10.1016/s0966-6362(02)00159-5

Cited by 560 publications

(587 citation statements)

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“…Menz et al reported that the magnitude of pelvis accelerations increased, while head accelerations were not affected by the walking surface when walking on an irregular surface [10]. In the present study, when we compared each parameter of the healthy control group by upper and lower back, the CV of ML and VT were lower in the upper back, while the CV of AP was lower in the lower back.…”

Section: Discussionmentioning

confidence: 39%

“…Previously, we reported that SARA did not correlate with the total length traveled or the root mean square area of body sway as measured 11 by body stabilometry [8]. Some reports of gait analysis in PD patients have evaluated acceleration, but not amplitude or CV [9].Menz et al reported that the magnitude of pelvis accelerations increased, while head accelerations were not affected by the walking surface when walking on an irregular surface [10]. In the present study, when we compared each parameter of the healthy control group by upper and lower back, the CV of ML and VT were lower in the upper back, while the CV of AP was lower in the lower back.…”

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confidence: 78%

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Quantitative evaluation of gait ataxia by accelerometers

Shirai

Yabe

Matsushima

et al. 2015

Journal of the Neurological Sciences

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Correspondence to Hidenao Sasaki, h-isasak@med.hokudai.ac.jp Although there are various types of biomarkers such as molecular markers and imaging markers, an appropriate maker for neurodegenerative disease has not been identified. Thus, we use clinical evaluation scales. However, it is important to identify an appropriate biomarker in order to evaluate the efficiency of a given clinical trial.Here, we performed gait analyses in patients with pure cerebellar type spinocerebellar degeneration (SCD) and assessed whether the obtained data could be used as a neurophysiological biomarker for cerebellar ataxia.Here we performed gait analysis in patients with pure cerebellar type spinocerebellar degeneration (SCD) and assessed whether the obtained data could be used as a neurophysiological biomarker for cerebellar ataxia. We evaluated the clinical severity of each patient in the SCD group using the Scale for the Assessment and Rating of Ataxia (SARA) [1, 2] and the Berg Balance Scale (BBS) [3,4]. The mean SARA of the SCD group was 13.26±4.43, while the mean Unified Parkinson's Disease Rating Scale (UPDRS) part III was 18. 48±8.4760. 6 This study was approved by the ethics panels of Hokkaido University Hospital and Kushiro Rosai Hospital. Methods (Fig. 1)Acceleration signals were measured during 6 min walking and 1 min standing tasks by two sets of triaxial accelerometers (Mimamori-gait system, LSI Medience; size, 7.5 cm × 5 cm × 2 cm; weight, 95 g) that were secured with a fixation vest to the middle of the subject's lower and upper back.When in the standing position, the subjects were evaluated with their eyes open for 1 min and then their eyes closed for another 1 min. An assistant remained beside the subjects in order to prevent falls, however, no falls occurred. The subjects were evaluated while they shuttle-walked a 30 m straight line for 6 min (6-min walk test (6MWT) [5]). Similar tasks were performed in the JASMITT study [6] and in other studies. When standing in the anatomical position, the orientation of the three acceleration axes, X, Y, and Z, were medial/lateral (ML), vertical (VT), and anterior/posterior (AP), respectively. Data were collected at a sampling frequency of 100 Hz and stored on a secure digital memory card inserted into the device for later analysis. To quantify body motion during standing, we examined parameters as follows:1. The three acceleration components ax(t), ay(t), and az(t) were smoothed by a moving-window average with a window size of 5.6 s to generate three 8 baseline signals: Bx(t), By(t), and Bz(t). Statistical analysisWe used Student's t-test for inter-group comparison and Pearson's correlation coefficients for disease severity and each parameter analysis.The JMPⓇ Pro 11.2.0 software program (SAS Institute Inc., Cary, NC, USA) was used for statistical analyses. We considered the results significant if p<0.05. The test of significance was adjusted for multiple testing using a Bonferroni step-down (Holm) correction. ResultsWe compared each parameter of SCD patients to that of...

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Section: Discussionmentioning

confidence: 39%

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confidence: 78%

Quantitative evaluation of gait ataxia by accelerometers

Shirai

Yabe

Matsushima

et al. 2015

Journal of the Neurological Sciences

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“…Other research studies 8) using the harmonic ratio have reported that the harmonic ratio for a comfortable walking speed is lower than the harmonic ratio for the maximum walking speed, i.e., smoothness of the gait is reduced at maximum walking speed. This description conflicts with our results.…”

Section: Discussionmentioning

confidence: 99%

“…Harmonics are elements of the power spectrum of acceleration derived by FFT, and the harmonic ratio is the ratio of the even-numbered harmonics to odd-numbered harmonics. Higher ratios indicate a greater steadiness of the gait pattern, i.e., a more rhythmic in-phase gait [7][8][9] . The harmonic ratio has been presented as an index of smoothness 10) .…”

Section: Discussionmentioning

confidence: 99%

“…This description conflicts with our results. The harmonic ratio indicates whether gait is rhythmic in-phase 8,9) ; it does not express the smoothness of a movement such as the entropy which we are proposing. That is, a change in walking pattern may occur by increasing the walking speed, but it may not cause a decrease in the smoothness of movement.…”

Section: Discussionmentioning

confidence: 99%

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Comparison of Smoothness during Gait between Community Dwelling Elderly Fallers and Non-Fallers Using Power Spectrum Entropy of Acceleration Time-Series

et al. 2008

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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.

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Single and Multiple Sensor Networking for Gait Analysis

2020

Body Sensor Networking, Design and Algorithms

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Acceleration patterns of the head and pelvis when walking on level and irregular surfaces

Cited by 560 publications

References 40 publications

Quantitative evaluation of gait ataxia by accelerometers

Quantitative evaluation of gait ataxia by accelerometers

Comparison of Smoothness during Gait between Community Dwelling Elderly Fallers and Non-Fallers Using Power Spectrum Entropy of Acceleration Time-Series

Single and Multiple Sensor Networking for Gait Analysis

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