A novel framework for quantifying accuracy and precision of event detection algorithms in FES-Cycling

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dc.creatorRonan Le Guillou
dc.creatorMartin Schmoll
dc.creatorBenoît Sijobert
dc.creatorDavid Lobato Borges
dc.creatorEmerson Fachin Martins
dc.creatorHenrique Resende Martins
dc.creatorRoger Pissard-Gibollet
dc.creatorCharles Fattal
dc.creatorChristine Azevedo Coste
dc.date.accessioned2023-09-14T19:25:21Z
dc.date.accessioned2025-09-09T00:29:30Z
dc.date.available2023-09-14T19:25:21Z
dc.date.issued2021
dc.identifier.doihttps://doi.org/10.3390/s21134571
dc.identifier.issn1424-8220
dc.identifier.urihttps://hdl.handle.net/1843/58692
dc.languagepor
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofSensors
dc.rightsAcesso Aberto
dc.subjectPsicologia
dc.subjectEngenharia biomédica
dc.subject.otherEvent detection
dc.subject.otherIMU
dc.subject.otherCyclic motion
dc.subject.otherRehabilitation
dc.subject.otherFunctional electrical stimulation
dc.subject.otherFES-cycling
dc.subject.otherGait cycle index
dc.titleA novel framework for quantifying accuracy and precision of event detection algorithms in FES-Cycling
dc.typeArtigo de periódico
local.citation.epage13
local.citation.issue13
local.citation.spage1
local.citation.volume21
local.description.resumoFunctional electrical stimulation (FES) is a technique used in rehabilitation, allowing the recreation or facilitation of a movement or function, by electrically inducing the activation of targeted muscles. FES during cycling often uses activation patterns which are based on the crank angle of the pedals. Dynamic changes in their underlying predefined geometrical models (e.g., change in seating position) can lead to desynchronised contractions. Adaptive algorithms with a real-time interpretation of anatomical segments can avoid this and open new possibilities for the automatic design of stimulation patterns. However, their ability to accurately and precisely detect stimulation triggering events has to be evaluated in order to ensure their adaptability to real-case applications in various conditions. In this study, three algorithms (Hilbert, BSgonio, and Gait Cycle Index (GCI) Observer) were evaluated on passive cycling inertial data of six participants with spinal cord injury (SCI). For standardised comparison, a linear phase reference baseline was used to define target events (i.e., 10%, 40%, 60%, and 90% of the cycle’s progress). Limits of agreement (LoA) of ±10% of the cycle’s duration and Lin’s concordance correlation coefficient (CCC) were used to evaluate the accuracy and precision of the algorithm’s event detections. The delays in the detection were determined for each algorithm over 780 events. Analysis showed that the Hilbert and BSgonio algorithms validated the selected criteria (LoA: +5.17/−6.34% and +2.25/−2.51%, respectively), while the GCI Observer did not (LoA: +8.59/−27.89%). When evaluating control algorithms, it is paramount to define appropriate criteria in the context of the targeted practical application. To this end, normalising delays in event detection to the cycle’s duration enables the use of a criterion that stays invariable to changes in cadence. Lin’s CCC, comparing both linear correlation and strength of agreement between methods, also provides a reliable way of confirming comparisons between new control methods and an existing reference.
local.identifier.orcidhttps://orcid.org/0000-0002-8236-8583
local.identifier.orcidhttps://orcid.org/0000-0001-6354-3879
local.identifier.orcidhttps://orcid.org/0000-0001-5204-5938
local.identifier.orcidhttps://orcid.org/0000-0002-6769-5359
local.identifier.orcidhttps://orcid.org/0000-0001-9858-9009
local.identifier.orcidhttps://orcid.org/0000-0002-4879-1345
local.identifier.orcidhttps://orcid.org/0000-0001-8045-3752
local.identifier.orcidhttps://orcid.org/0000-0002-3042-0941
local.identifier.orcidhttps://orcid.org/0000-0002-7379-8004
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELÉTRICA
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://www.mdpi.com/1424-8220/21/13/4571

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