Key result
Sample entropy demonstrated higher consistency and better ability to discriminate between young adults, older non-fallers, and older fallers compared to approximate entropy, particularly in 60-second anterior-posterior centre of pressure time-series.
Why the study?
ApEn and SampEn are sensitive to input parameters m, r, and N, but the effects of altering these parameters in centre of pressure time-series analysis have been scarcely investigated.
Cross-Sectional (n=159)
p-value: p=<0.001
For analyzing centre of pressure time-series, Sample Entropy is more consistent and better at discriminating between age and fall-risk groups than Approximate Entropy, particularly when using longer time-series (≥ 60 s).
BACKGROUND: Approximate entropy (ApEn) and sample entropy (SampEn) have been previously used to quantify the regularity in centre of pressure (COP) time-series in different experimental groups and/or conditions. ApEn and SampEn are very sensitive to their input parameters: m (subseries length), r (tolerance) and N (data length). Yet, the effects of changing those parameters have been scarcely investigated in the analysis of COP time-series. This study aimed to investigate the effects of changing parameters m, r and N on ApEn and SampEn values in COP time-series, as well as the ability of these entropy measures to discriminate between groups. METHODS: A public dataset of COP time-series was used. ApEn and SampEn were calculated for m = {2, 3, 4, 5}, r = {0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5} and N = {600, 1200} (30 and 60 s, respectively). Subjects were stratified in young adults (age < 60, n = 85), and older adults (age ≥ 60) with (n = 18) and without (n = 56) falls in the last year. The effects of changing parameters m, r and N on ApEn and SampEn were investigated with a three-way ANOVA. The ability of ApEn and SampEn to discriminate between groups was investigated with a mixed ANOVA (within-subject factors: m, r and N; between-subject factor: group). Specific combinations of m, r and N producing significant differences between groups were identified using the Tukey's honest significant difference procedure. RESULTS: A significant three-way interaction between m, r and N confirmed the sensitivity of ApEn and SampEn to the input parameters. SampEn showed a higher consistency and ability to discriminate between groups than ApEn. Significant differences between groups were mostly observed in longer (N = 1200) COP time-series in the anterior-posterior direction. Those differences were observed for specific combinations of m and r, highlighting the importance of an adequate selection of input parameters. CONCLUSIONS: Future studies should favour SampEn over ApEn and longer time-series (≥ 60 s) over shorter ones (e.g. 30 s). The use of parameter combinations such as SampEn (m = {4, 5}, r = {0.25, 0.3, 0.35}) is recommended.
No takes yet. Share an insight, caveat, or question.
Montesinos et al. (2018) conducted a cross-sectional in Postural balance and fall risk (n=159). Age and fall history vs. Young adults and older non-fallers was evaluated on Ability of Approximate Entropy (ApEn) and Sample Entropy (SampEn) to discriminate between experimental groups (p=<0.001). Sample entropy demonstrated higher consistency and better ability to discriminate between young adults, older non-fallers, and older fallers compared to approximate entropy, particularly in 60-second anterior-posterior centre of pressure time-series.
Synapse has enriched 3 closely related papers on similar clinical questions. Consider them for comparative context: