The EMG+FMG band used for the experiment.
<p>We employed 8 EMG sensors and 8 FMG sensors which were housed in 3D printed housings and placed in an alternating sequence on a Velcro strap. The sensors were positioned such that they could be spaced equidistantly around the participant’s forearm before the band was strapped to the arm.<...
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2025
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| _version_ | 1852021377120337920 |
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| author | Peyton R. Young (14021643) |
| author2 | Kihun Hong (21072471) Eden J. Winslow (21072474) Giancarlo K. Sagastume (21072477) Marcus A. Battraw (14021640) Richard S. Whittle (21072480) Jonathon S. Schofield (4062958) |
| author2_role | author author author author author author |
| author_facet | Peyton R. Young (14021643) Kihun Hong (21072471) Eden J. Winslow (21072474) Giancarlo K. Sagastume (21072477) Marcus A. Battraw (14021640) Richard S. Whittle (21072480) Jonathon S. Schofield (4062958) |
| author_role | author |
| dc.creator.none.fl_str_mv | Peyton R. Young (14021643) Kihun Hong (21072471) Eden J. Winslow (21072474) Giancarlo K. Sagastume (21072477) Marcus A. Battraw (14021640) Richard S. Whittle (21072480) Jonathon S. Schofield (4062958) |
| dc.date.none.fl_str_mv | 2025-04-10T20:02:12Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0321319.g001 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/The_EMG_FMG_band_used_for_the_experiment_/28773861 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Physiology Biotechnology Science Policy Space Science Biological Sciences not elsewhere classified skin &# 8217 pattern recognition algorithms misclassification errors caused many modern technologies identify specific patterns bodied participants performed axial forces present augmented reality systems assistive mechatronic devices predict hand gestures 4 hand gestures muscle electrical activity 34 %) followed 3 sensing modalities statistically significant effects object loading effects highest classification accuracy grasped load combinations effective device control combination </ p grasped load hand gesture sensing modality muscle contraction device commands 27 %) gesture classification classification performance well established vital aspects underlying muscles technique suffers surface created research applications release task manipulated objects limb movements fused combination force myography daily life 84 %). 8 positions 27 able |
| dc.title.none.fl_str_mv | The EMG+FMG band used for the experiment. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>We employed 8 EMG sensors and 8 FMG sensors which were housed in 3D printed housings and placed in an alternating sequence on a Velcro strap. The sensors were positioned such that they could be spaced equidistantly around the participant’s forearm before the band was strapped to the arm.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_f679dea4e5298cf07cffa997ee68af42 |
| identifier_str_mv | 10.1371/journal.pone.0321319.g001 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28773861 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The EMG+FMG band used for the experiment.Peyton R. Young (14021643)Kihun Hong (21072471)Eden J. Winslow (21072474)Giancarlo K. Sagastume (21072477)Marcus A. Battraw (14021640)Richard S. Whittle (21072480)Jonathon S. Schofield (4062958)PhysiologyBiotechnologyScience PolicySpace ScienceBiological Sciences not elsewhere classifiedskin &# 8217pattern recognition algorithmsmisclassification errors causedmany modern technologiesidentify specific patternsbodied participants performedaxial forces presentaugmented reality systemsassistive mechatronic devicespredict hand gestures4 hand gesturesmuscle electrical activity34 %) followed3 sensing modalitiesstatistically significant effectsobject loading effectshighest classification accuracygrasped load combinationseffective device controlcombination </ pgrasped loadhand gesturesensing modalitymuscle contractiondevice commands27 %)gesture classificationclassification performancewell establishedvital aspectsunderlying musclestechnique sufferssurface createdresearch applicationsrelease taskmanipulated objectslimb movementsfused combinationforce myographydaily life84 %).8 positions27 able<p>We employed 8 EMG sensors and 8 FMG sensors which were housed in 3D printed housings and placed in an alternating sequence on a Velcro strap. The sensors were positioned such that they could be spaced equidistantly around the participant’s forearm before the band was strapped to the arm.</p>2025-04-10T20:02:12ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0321319.g001https://figshare.com/articles/figure/The_EMG_FMG_band_used_for_the_experiment_/28773861CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/287738612025-04-10T20:02:12Z |
| spellingShingle | The EMG+FMG band used for the experiment. Peyton R. Young (14021643) Physiology Biotechnology Science Policy Space Science Biological Sciences not elsewhere classified skin &# 8217 pattern recognition algorithms misclassification errors caused many modern technologies identify specific patterns bodied participants performed axial forces present augmented reality systems assistive mechatronic devices predict hand gestures 4 hand gestures muscle electrical activity 34 %) followed 3 sensing modalities statistically significant effects object loading effects highest classification accuracy grasped load combinations effective device control combination </ p grasped load hand gesture sensing modality muscle contraction device commands 27 %) gesture classification classification performance well established vital aspects underlying muscles technique suffers surface created research applications release task manipulated objects limb movements fused combination force myography daily life 84 %). 8 positions 27 able |
| status_str | publishedVersion |
| title | The EMG+FMG band used for the experiment. |
| title_full | The EMG+FMG band used for the experiment. |
| title_fullStr | The EMG+FMG band used for the experiment. |
| title_full_unstemmed | The EMG+FMG band used for the experiment. |
| title_short | The EMG+FMG band used for the experiment. |
| title_sort | The EMG+FMG band used for the experiment. |
| topic | Physiology Biotechnology Science Policy Space Science Biological Sciences not elsewhere classified skin &# 8217 pattern recognition algorithms misclassification errors caused many modern technologies identify specific patterns bodied participants performed axial forces present augmented reality systems assistive mechatronic devices predict hand gestures 4 hand gestures muscle electrical activity 34 %) followed 3 sensing modalities statistically significant effects object loading effects highest classification accuracy grasped load combinations effective device control combination </ p grasped load hand gesture sensing modality muscle contraction device commands 27 %) gesture classification classification performance well established vital aspects underlying muscles technique suffers surface created research applications release task manipulated objects limb movements fused combination force myography daily life 84 %). 8 positions 27 able |