Load exposure of osseointegrated implants for transfemoral limb prosthesis during running

Supervision of M.Sc. theses using the writing of a scientific article as a framework to increase efficiency and quality of research outcomes

The number of published peer-reviewed research articles has increased exponentially in the past decades, as has the degree of competitiveness in scientific publishing. Publication of scientific articles remains the gold standard for measuring research quality. In this context, quality is understood as to how rigorously the scientific method was applied. However, a critical disconnect exists between the continuous channel of projects fed to students by research laboratories, and the scientific quality of outcomes these students produce. Here, we present a process for the supervision of M.Sc. thesis projects conducted in research laboratories with the objective to increase productivity and quality. It is based on an iterative model of writing a scientific article naturally following the scientific method. This approach intends to maximize learning and development for the student, as well as productivity for the research laboratory by facilitating the publication of a peer-reviewed scientific article out of the thesis work.

Kinetics of Lower Limb Prosthesis: Automated Detection of Vertical Loading Rate

Vertical loading rate could be associated with residuum and whole body injuries affecting individuals fitted with transtibial prostheses. The objective of this study was to outline one out of five automated methods of extraction of vertical loading rate that stacked up the best against manual detection, which is considered the gold standard during pseudo-prosthetic gait. The load applied on the long axis of the leg of three males was recorded using a transducer fitted between a prosthetic foot and physiotherapy boot while walking on a treadmill for circa 30 min. The automated method of extraction of vertical loading rate, combining the lowest absolute average and range of 95% CI difference compared to the manual method, was deemed the most accurate and precise. The average slope of the loading rate detected manually over 150 strides was 5.56 ± 1.33 kN/s, while the other slopes ranged from 4.43 ± 0.98 kN/s to 6.52 ± 1.64 kN/s depending on the automated detection method. An original method proposed here, relying on progressive loading gradient-based automated extraction, produced the closest results (6%) to manual selection. This work contributes to continuous efforts made by providers of prosthetic and rehabilitation care to generate evidence informing reflective clinical decision-making.