Please use this identifier to cite or link to this item:
http://hdl.handle.net/2067/46201
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Molinaro, Luca | it |
dc.contributor.author | Taborri, Juri | it |
dc.contributor.author | Santospagnuolo, Adriano | it |
dc.contributor.author | Vetrano, Mario | it |
dc.contributor.author | Vulpiani, Maria Chiara | it |
dc.contributor.author | Rossi, Stefano | it |
dc.date.accessioned | 2021-11-11T10:44:16Z | - |
dc.date.available | 2021-11-11T10:44:16Z | - |
dc.date.issued | 2021 | it |
dc.identifier.issn | 1424-8220 | it |
dc.identifier.uri | http://hdl.handle.net/2067/46201 | - |
dc.description.abstract | The possibility of measuring predictive factors to discriminate athletes at higher risk of anterior cruciate ligament (ACL) injury still represents an open research question. We performed an observational study with thirteen female basketball players who performed monopodalic jumps and single-leg squat tests. One of them suffered from an ACL injury after the first test session. Data gathered from twelve participants, who did not suffer from ACL injury, were used for a reliability analysis. Parameters related to leg stability, load absorption capability and leg mobility showed good-to-excellent reliability. Path length, root mean square of the acceleration and leg angle with respect to the vertical axis revealed themselves as possible predictive factors to identify athletes at higher risk. Results confirm that six months after reconstruction represents the correct time for these athletes to return to playing. Furthermore, the training of leg mobility and load absorption capability could allow athletes to reduce the probability of new injuries. | it |
dc.rights | CC0 1.0 Universal | * |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
dc.title | Sensor-based indices for the prediction and monitoring of anterior cruciate ligament injury: Reliability analysis and a case study in basketball | it |
dc.type | article | * |
dc.identifier.doi | 10.3390/s21165341 | it |
dc.identifier.pmid | 34450783 | it |
dc.identifier.scopus | 2-s2.0-85112630555 | it |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/85112630555 | it |
dc.relation.journal | SENSORS | it |
dc.relation.firstpage | 5341 | it |
dc.relation.volume | 21 | it |
dc.relation.issue | 16 | it |
dc.type.miur | 262 | * |
item.fulltext | With Fulltext | - |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | restricted | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
crisitem.journal.journalissn | 1424-8220 | - |
crisitem.journal.ance | E186641 | - |
Appears in Collections: | A1. Articolo in rivista |
Files in This Item:
File | Description | Size | Format | Existing users please |
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sensors-21-05341.pdf | 2.08 MB | Adobe PDF | Request a copy |
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