2020
DOI: 10.1016/j.mex.2020.100988
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Design of a loading system for cyclic test on sutured organs

Abstract: The design of loading systems to test biologic samples is often challenging, due to shape variability and non-conventional loading set-ups. In addition to this, large economic investments would not be justified since the loading set up is usually designed for one single or for a limited range of applications. The object of this work is the development of a loading set-up finalised to on-site testing of sutures whose main function is applying a localised tensile load. The main challenges of this desi… Show more

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“…Therefore, the implementation of a joint approach has permitted relevant steps forward in the understanding of various biomechanical aspects, thus permitting relevant improvements in the clinical sphere, such as in surgical or biomedical procedures [1][2][3][4][5], implants realisation [6][7][8][9][10][11][12] and prosthesis design [13][14][15][16][17]. On the one hand, experimental analysis provides further insights into materials characterisation at different scales [18][19][20][21][22][23][24][25][26], objectifies clinical qualitative outcomes [27][28][29][30][31][32][33][34][35] and lets numerical models be validated [36]. On the other hand, numerical studies allow studying wider test scenarios and inferring physical quantities otherwise tough to figure out because of feasibility and costs reasons [37][38][39][40][41][42][43][44][45]…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, the implementation of a joint approach has permitted relevant steps forward in the understanding of various biomechanical aspects, thus permitting relevant improvements in the clinical sphere, such as in surgical or biomedical procedures [1][2][3][4][5], implants realisation [6][7][8][9][10][11][12] and prosthesis design [13][14][15][16][17]. On the one hand, experimental analysis provides further insights into materials characterisation at different scales [18][19][20][21][22][23][24][25][26], objectifies clinical qualitative outcomes [27][28][29][30][31][32][33][34][35] and lets numerical models be validated [36]. On the other hand, numerical studies allow studying wider test scenarios and inferring physical quantities otherwise tough to figure out because of feasibility and costs reasons [37][38][39][40][41][42][43][44][45]…”
Section: Introductionmentioning
confidence: 99%