Publicação
Calculating sample entropy from isometric torque signals : methodological considerations and recommendations
| datacite.subject.fos | Ciências Médicas::Ciências da Saúde | |
| datacite.subject.sdg | 03:Saúde de Qualidade | |
| dc.contributor.author | Raffalt, Peter C. | |
| dc.contributor.author | Yentes, Jennifer M. | |
| dc.contributor.author | Freitas, Sandro R. | |
| dc.contributor.author | Vaz, João R. | |
| dc.date.accessioned | 2026-02-09T15:37:45Z | |
| dc.date.available | 2026-02-09T15:37:45Z | |
| dc.date.issued | 2023-06 | |
| dc.description.abstract | We investigated the effect of different sampling frequencies, input parameters and observation times for sample entropy (SaEn) calculated on torque data recorded from a submaximal isometric contraction. Forty-six participants performed sustained isometric knee flexion at 20% of their maximal contraction level and torque data was sampled at 1,000 Hz for 180 s. Power spectral analysis was used to determine the appropriate sampling frequency. The time series were downsampled to 750, 500, 250, 100, 50, and 25 Hz to investigate the effect of different sampling frequency. Relative parameter consistency was investigated using combinations of vector lengths of two and three and tolerance limits of 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, and 0.4, and data lengths between 500 and 18,000 data points. The effect of different observations times was evaluated using Bland-Altman plot for observations times between 5 and 90 s. SaEn increased at sampling frequencies below 100 Hz and was unaltered above 250 Hz. In agreement with the power spectral analysis, this advocates for a sampling frequency between 100 and 250 Hz. Relative consistency was observed across the tested parameters and at least 30 s of observation time was required for a valid calculation of SaEn from torque data. | eng |
| dc.identifier.citation | Raffalt PC, Yentes JM, Freitas SR and Vaz JR (2023) Calculating sample entropy from isometric torque signals: methodological considerations and recommendations. Front. Physiol. 14:1173702. doi: 10.3389/fphys.2023.1173702 | |
| dc.identifier.doi | 10.3389/fphys.2023.1173702 | |
| dc.identifier.issn | 1664-042X | |
| dc.identifier.uri | http://hdl.handle.net/10400.26/61563 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Frontiers Media | |
| dc.relation.hasversion | https://doi.org/10.3389/fphys.2023.1173702 | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | regularity | |
| dc.subject | time series | |
| dc.subject | nonlinear analysis | |
| dc.subject | motor control | |
| dc.subject | muscle contraction | |
| dc.title | Calculating sample entropy from isometric torque signals : methodological considerations and recommendations | eng |
| dc.type | contribution to journal | |
| dspace.entity.type | Publication | |
| oaire.citation.startPage | 1173702 | |
| oaire.citation.title | Frontiers in Physiology | |
| oaire.citation.volume | 14 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 |