Investigating the stationarity of paediatric aspiration signals

Chau, Tom; Chau, Dennis Chak Wai; Casas, Michael J; Berall, Glenn; Kenny, Dave

doi:10.1109/tnsre.2004.841384

Cited by 55 publications

(48 citation statements)

References 36 publications

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“…The RAT is often used to evaluate the weak stationarity of physiological and biomedical signals (Alves and Chau, 2008;Chau et al, 2005;Nhan and Chau, 2009;Harris et al, 1993;Hampson et al, 2005;Bilodeau et al, 1997;Novak et al, 1996).…”

Section: Reverse Arrangements Testmentioning

confidence: 99%

“…The minimum window size was constrained to include at least 10 stride intervals and the maximum window size was constrained to include at least 10 windows (for all series but one). In this way, we maintained an adequate number of data points as required to estimate a single statistical parameter (Chau et al, 2005) when calculating both the mean squared value within each interval and the total number of reverse arrangements.…”

Section: Stationarity Testingmentioning

confidence: 99%

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The effect of treadmill walking on the stride interval dynamics of children

Fairley

Sejdić

Chau

2010

Human Movement Science

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The stride interval of typical human gait is correlated over thousands of strides. This statistical persistence diminishes with age, disease, and pace-constrained walking. Considering the widespread use of treadmills in rehabilitation and research, it is important to understand the effect of this speed-constrained locomotor modality on stride interval dynamics. To this end, and given that the dynamics of children have been largely unexplored, this study investigated the impact of treadmill walking, both with and without handrail use, on paediatric stride interval dynamics. An initial stationarity analysis of stride interval time series identified both non-stationary and stationary signals during all walking conditions. Subsequent scaling analysis revealed diminished stride interval persistence during unsupported treadmill walking compared to overground walking. Finally, while the correlation between stride interval dynamics and gross energy expenditure was investigated in an effort to elucidate the clinical meaning of persistence, no simple linear correlation was found.ii DedicationTo my grandmother, whose inspiration I will carry with me always.iii Acknowledgements A sincere thank-you to my supervisor, Dr. Tom Chau, whose patience, support and guidance has allowed me to navigate the world of research. I am continually amazed by your dedication to your students and work, and am grateful for the knowledge and training that you have provided me.To my committee members, Dr. Karl Zabjek and Dr. Brian Maki, thank you for your invaluable feedback and advice.To the members of the PRISM lab, I am truly appreciative of your insights, perspectives and friendship. A special thank-you to Brian Nhan, Jorge Torres, Sarah Power and Stefanie Blain, with whom I shared an office, for your considerable help, thoughtful comments, good humour, and fun. Many thanks also to: Ervin Sejdić, for your expertise and contribution; Ka Lun Tam, for your technical wizardry; and Matthew Chang, for the thought-provoking discussions.

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Section: Reverse Arrangements Testmentioning

confidence: 99%

Section: Stationarity Testingmentioning

confidence: 99%

The effect of treadmill walking on the stride interval dynamics of children

Fairley

Sejdić

Chau

2010

Human Movement Science

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“…We have employed the Bendat and Piersol's runs test, a general non-parametric test for weak or wide sense stationarity [12]. The assessment of stationarity with this method depends on the window size, which can be determined by roughly estimating the dominant low frequency band in terms of energy distribution [13]. We found that over half of the MEG epochs retained the majority of their energy below 10.6 Hz.…”

Section: Stationaritymentioning

confidence: 99%

“…Thus, a window of at least 94.3 ms is necessary. As a conservative estimate, the windows size should be more than three times the previous value [13]. Thus, in our study, a window length of 300 ms, that is 50 samples, was employed to test the stationarity.…”

Section: Stationaritymentioning

confidence: 99%

Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients

Gómez

Hornero

Mediavilla

et al. 2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-The goal of this study was to analyze the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD) using a nonlinear forecasting measure. It is a nonparametric method to quantify the predictability of time series. Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 15 patients with probable AD and 15 elderly control subjects. Stationary epochs of 5 seconds (848 points, sample frequency of 169.55 Hz) were selected. Our results showed that AD patients' MEGs were more predictable than controls' recordings. Additionally, an accuracy of 76.7% (80.0% sensitivity; 73.3% specificity) was reached using a receiver operating characteristic curve. These preliminary results suggest the usefulness of nonlinear forecasting to gain a better understanding of dynamical processes underlying the MEG recording.

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“…Essas variáveis se referem à potência e variância. Destas variáveis estudadas, somente duas estão presentes em trabalhos sobre disfagia, que são estacionaridade e taxa de dispersão (LEE et al, 2006a;CHAU et al, 2005).…”

Section: Classificadoresunclassified

Análise quantitativa do sinal da deglutição

Spadotto¹

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Investigating the stationarity of paediatric aspiration signals

Abstract: Abstract-An aspiration signal is the time-varying anterior-posterior acceleration measured infero-anterior to the thyroid notch when foreign material enters the airway during inspiration.

Cited by 55 publications

References 36 publications

The effect of treadmill walking on the stride interval dynamics of children

The effect of treadmill walking on the stride interval dynamics of children

Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients

Análise quantitativa do sinal da deglutição

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