Nonlinear Analysis of Ambulatory Activity Patterns in Community-Dwelling Older Adults

Cavanaugh, James T.; Kochi, Naomi; Stergiou, Nicholas

doi:10.1093/gerona/glp144

Cited by 57 publications

(46 citation statements)

References 36 publications

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“…Changes in the entropies (ApEn, SampEn) were already reported in some cardiovascular researches [21][22][23][24], postural control investigations [25,26], physical activity measures [27,28] and in analysis of cardiodepressive vasovagal syncope [24]. The presented analysis of changes in the complexity of joint signals of ECG, ICG and blood pressure during passive provocation of the neuro-cardiogenic reaction will add to further understanding of the course and mechanism of vasovagal syndrome.…”

Section: Introductionmentioning

confidence: 67%

“…The in-depth description of the comparisons of both of these statistics can be found in the literature [20]. Despite elementary differences between ApEn and SampEn, both statistics are extensively used in cardiovascular physiology [20,22,23,[27][28][29][30][31][33][34][35][36][40][41][42]. In this paper we also show the possible applications of ApEn (m, r, N) and SampEn (m, r, N) for the analysis of physiological signals.…”

Section: Approximate Entropy and Sample Entropymentioning

confidence: 99%

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Entropy in Investigation of Vasovagal Syndrome in Passive Head Up Tilt Test

Buszko

Piątkowska

Koźluk

et al. 2017

Entropy

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This paper presents an application of Approximate Entropy (ApEn) and Sample Entropy (SampEn) in the analysis of heart rhythm, blood pressure and stroke volume for the diagnosis of vasovagal syndrome. The analyzed biosignals were recorded during positive passive tilt tests-HUTT(+). Signal changes and their entropy were compared in three main phases of the test: supine position, tilt, and pre-syncope, with special focus on the latter, which was analyzed in a sliding window of each signal. In some cases, ApEn and SampEn were equally useful for the assessment of signal complexity (p < 0.05 in corresponding calculations). The complexity of the signals was found to decrease in the pre-syncope phase (SampEn (RRI): 1.20-0.34, SampEn (sBP): 1.29-0.57, SampEn (dBP): 1.19-0.48, SampEn (SV): 1.62-0.91). The pattern of the SampEn (SV) decrease differs from the pattern of the SampEn (sBP), SampEn (dBP) and SampEn (RRI) decrease. For all signals, the lowest entropy values in the pre-syncope phase were observed at the moment when loss of consciousness occurred.

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Section: Introductionmentioning

confidence: 67%

Section: Approximate Entropy and Sample Entropymentioning

confidence: 99%

Entropy in Investigation of Vasovagal Syndrome in Passive Head Up Tilt Test

Buszko

Piątkowska

Koźluk

et al. 2017

Entropy

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“…This is greater than the minimum of 600 steps/d thought to be necessary to sustain an independent lifestyle in a single-level residence with moderate family or social support and in some cases above the 1,100 to 1,450 steps/d recommended for independent living [40]. This is well below the average number of steps reported for both "highly active" and "moderately active" older community-dwelling adults (i.e., 12,660 and 7,596 steps/d, respectively) and even below those classified as "inactive" (i.e., 3,893 steps/d) [130]. Further, it has been reported that steps taken by individuals with TFLL appear as very short bouts lasting 1 to 2 min and consisting of 17 steps [91].…”

Section: Activitymentioning

confidence: 78%

Outcomes associated with the use of microprocessor-controlled prosthetic knees among individuals with unilateral transfemoral limb loss: A systematic review

Sawers¹,

Hafner²

2013

JRRD

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Abstract-Microprocessor-controlled prosthetic knees (MPKs) have been developed as an alternative to non-microprocessorcontrolled knees (NMPKs) to address challenges facing individuals with lower-limb loss. A body of scientific literature comparing MPKs and NMPKs exists but has yet to be critically appraised. Therefore, we conducted a systematic review to examine outcomes associated with the use of these interventions among individuals with transfemoral limb loss. A search of biomedical databases identified 241 publications, of which 27 met the inclusion and exclusion criteria and were reviewed for methodological quality and content. We developed 28 empirical evidence statements (EESs) in 9 outcome categories (metabolic energy expenditure, activity, cognitive demand, gait mechanics, environmental obstacle negotiation, safety, preference and satisfaction, economics, and health and quality of life) based on findings in the literature. The level of evidence supporting these EESs varied due to quantity, quality, and consistency of the results. EESs supported by a moderate level of evidence that noted significant differences between MPKs and NMPKs were derived in five of the nine outcome categories. The results from this review suggest that evidence exists to inform clinical practice and that additional research is needed to confirm existing evidence and better understand outcomes associated with the use of NMPKs and MPKs.Key words: amputation, artificial limb, function, gait, knee, microprocessor, outcome, preference, rehabilitation, safety. Abbreviations: AAOP = American Academy of Orthotists andProsthetists, ABC = Activities-specific Balance Confidence, CWS = controlled walking speed, DLW = doubly labeled water, EBP = evidence-based practice, EES = empirical evidence statement, EV = external validity, GRF = ground reaction force, HAI = Hill Assessment Index, HRQL = health-related quality of life, IV = internal validity, LLL = lower-limb loss, MFCL = Medicare Functional Classification Level, MP = microprocessor, MPC = microprocessor control, MPK = microprocessor-controlled prosthetic knee, MRPP = Montreal Rehabilitation Performance Profile, NMPK = non-microprocessor-controlled prosthetic knee, O 2 = oxygen, O&P = orthotic and prosthetic, PAEE = physical activity-related energy expenditure, PCBS = Prosthetic Cognitive Burden Scale, PCI = physiological cost index, PEQ = Prosthesis Evaluation Questionnaire, PEQ-A = PEQ Addendum, PRO = patient-reported outcome, QALY = quality adjusted life year, QOL = quality of life, RPE = rating of perceived exertion, SAI = Stair Assessment Index, SF-36 = 36-Item Short-Form Health Survey, SOT = sensory organization test, SSWS = selfselected walking speed, SSC = State of the Science Conference, TDEE = total daily energy expenditure, TFLL = transfemoral limb loss.

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“…age and disease [5,34]. Also, the α-values can vary substantially between behaviors in a particular species [7,10,12] [10].…”

Section: Effect Of Test Durationmentioning

confidence: 99%

Assessment of long-range correlation in animal behavior time series: The temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus)

Kembro¹,

Flesia²,

Gleiser³

et al. 2013

Physica A: Statistical Mechanics and its Applications

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Assessment of long-range correlation in animal behaviour time series: the temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus). AbstractThe aim of this study was to evaluate the performance of a classical method of fractal analysis, Detrended Fluctuation Analysis (DFA), in the analysis of the dynamics of animal behavior time series. In order to correctly use DFA to assess the presence of long-range correlation, previous authors using statistical model systems have stated that different aspects should be taken into account such as: 1) the establishment by hypothesis testing of the absence of short term correlation, 2) an accurate estimation of a straight line in the log-log plot of the fluctuation function, 3) the elimination of artificial crossovers in the fluctuation function, and 4) the length of the time series. Taking into consideration these factors, herein we evaluated the presence of long-range correlation in the temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus). In our study, modeling the data with the general ARFIMA model, we rejected the hypothesis of short range correlations (d=0) in all cases. We also observed that DFA was able to distinguish between the artificial crossover observed in the temporal pattern of locomotion of Japanese quail, and the crossovers in the correlation behavior observed in mosquito larvae locomotion. Although the test duration can slightly influence the parameter estimation, no qualitative differences were observed between different test durations.

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Nonlinear Analysis of Ambulatory Activity Patterns in Community-Dwelling Older Adults

Cited by 57 publications

References 36 publications

Entropy in Investigation of Vasovagal Syndrome in Passive Head Up Tilt Test

Entropy in Investigation of Vasovagal Syndrome in Passive Head Up Tilt Test

Outcomes associated with the use of microprocessor-controlled prosthetic knees among individuals with unilateral transfemoral limb loss: A systematic review

Assessment of long-range correlation in animal behavior time series: The temporal pattern of locomotor activity of Japanese quail (Coturnix coturnix) and mosquito larva (Culex quinquefasciatus)

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