The evolution of advanced powered prosthetic technology can be facilitated through the application of extrinsic approaches. The amalgamation of sophisticated machine learningMachine learning algorithms, such as the multilayer perceptron neural networkMachine learningMultilayer perceptron neural network, can be applied to distinguish between advanced control architectures by means of the acquisition of force plate signalForce plate signal data. An assortment of other machine learningMachine learning algorithms can be subsequently utilized, for which the J48 decision treeMachine learningJ48 decision tree can augment the visualization process of achieving machine learningMachine learning distinction. The utility of machine learningMachine learning can additionally facilitate the prioritization of sensor allocation and signal data post-processing. Additionally, inertial sensorsInertial sensor systems can be externally mounted to prosthetics for the evaluation of gait with the opportunity for augmented feedback acuity. Mounting strategies can be implemented through 3D printed adapters3D printed adapter and through a conformal wearableConformal wearable and wireless inertial sensor systems context.