The phenomenon of stress cracking of Pellethane 2363-80A (PEU) was investigated using the cage implant system. A cytotoxic polyvinylchloride (PVC) and a silicone rubber containing an anti-inflammatory steroid were used to create inflammatory environments in which the biostability of the pre-stressed PEU was tested. These coimplants provided alternative in vivo environments to study in vivo polymer interactions. The inflammatory responses to the implanted cages were monitored by analyzing the exudates aspirated from the cages at different implantation times over 21 days. The pre-stressed PEU specimens were retrieved after 5, 10, and 15 weeks postimplantation and examined by optical microscopy (OM) and scanning electron microscopy (SEM). The results support the conclusion that in vivo cracking of stressed (strained) Pellethane 80A is related to cell-polymer interactions. Severe cracking or rupture of the implanted PEU specimens was observed as early as 5 weeks postimplantation. Molecular chain degradation of the implanted specimens was evident from molecular weight measurements. Neither surface cracking nor degradation of macromolecules was found on the pre-stressed PEU specimens with the added cytotoxic PVC implanted over 15 weeks. No cracking was observed on the pre-stressed specimens in the presence of steroid silicone rubber, even after 10 weeks implantation.
(1) Background: An iterative learning control (ILC) strategy was developed for a “Muscle First” Motor-Assisted Hybrid Neuroprosthesis (MAHNP). The MAHNP combines a backdrivable exoskeletal brace with neural stimulation technology to enable persons with paraplegia due to spinal cord injury (SCI) to execute ambulatory motions and walk upright. (2) Methods: The ILC strategy was developed to swing the legs in a biologically inspired ballistic fashion. It maximizes muscular recruitment and activates the motorized exoskeletal bracing to assist the motion as needed. The control algorithm was tested using an anatomically realistic three-dimensional musculoskeletal model of the lower leg and pelvis suitably modified to account for exoskeletal inertia. The model was developed and tested with the OpenSim biomechanical modeling suite. (3) Results: Preliminary data demonstrate the efficacy of the controller in swing-leg simulations and its ability to learn to balance muscular and motor contributions to improve performance and accomplish consistent stepping. In particular, the controller took 15 iterations to achieve the desired outcome with 0.3% error.
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