Figure 2.

Experimental acquisition for Proprio-Neural Modeling simulations and Electro-Neural Modeling of the realistic nerve structures

(A) Experimental set-up for motion acquisition during walking trials. The motion capture system acquired body markers on the subject walking on a sensorized treadmill. Computed joint kinematics from the motion capture data is then used through NMS modeling to predict muscle tendon unit kinematics. Finally, EMG muscle activity, muscle lengths, and elongation velocity are used to predict Ia afferent fiber natural activity from the modeled Ia muscle spindle transducers.

(B) Histological images taken from three cross-sectional layers of the sciatic nerves from two transfemoral amputees and the corresponding nerve segmentations based on those cross-sections (shown on the right). On the bottom, the table shows the number of fascicles visible in the histological images.

(C) A schematic view of the ENM. In Electrical modeling: a geometrical reconstruction of a curving fascicle and the complete nerve representation, based on the segmented cross-sections; the meshed nerve structure; the model of the nerve section with an implanted electrode and the electrical potentials map obtained during an active site stimulation. In Neural modeling: probability density function of fibers spatial density, based on fiber diameter and on subject age; an example of fiber distribution in the endo-fascicular space; the stimulation-driven activation of the Ia target population estimated through NEURON from the potentials produced by the FEM model, interpolated on the generated fiber paths.