ABSTRACT
BACKGROUND: Significant progress has been made over the last 50 years in the design, development and testing of transcutaneous electrical nerve stimulation (TENS) in mediating different levels of tactile sensations. However, without knowing how best to stimulate the nerve fibers, the elicited sensation quality will always remain poor and unnatural. NEW METHOD: A new biomimetic 3D TENS computational model is developed to quantify the neural activation mechanism with varied surface electrodes. This model includes seven-layered anatomical structure of the forearm and biophysically-detailed myelinated Aß fibers. The Aß-fiber diameters from 1.5 - 7.5⯵m were randomly distributed beneath the skin to mimic the physiologically-realistic fiber population. The arithmetic averaging algorithm and Gaussian filter were adopted to identify the sensation center and to quantify sensation intensities under different stimulation conditions. RESULTS: Fibers larger than 4.5⯵m can usually be activated producing tactile sensations such as light touch, pressure, buzz, and vibration. While, fibers with diameters of 3.5 and 3⯵m can only be excited at uncomfortable numb and pain sensations. The resulted modelling predictions match the recent psychophysical experimental data. COMPARISON WITH EXISTING METHOD(S): The new TENS model is more physiologically-realistic by introducing a detailed morphological information and key ionic mechanisms in nerve fibers. CONCLUSIONS: Our results indicate that TENS may be a promising method to target functionally-distinct neural pathways in an effort to improve the elicited tactile sensations quality with electrical stimulation. This work provides a promising platform of discovering neural mechanisms under TENS.
