Device and method for quantitative assessment of small nerve fiber function

A method for diagnosing small fiber neuropathy, the method comprising the steps of:

• 1) providing a radiofrequency (RF) generator configured to deliver radiofrequency (RF) currents;
• 2) applying small-area probes to a subject's skin, wherein the small-area probes are capable of delivering the electromagnetic pulses to the subject's skin;
• 3) varying the RF stimulation intensity generated by the RF generator by means of an up-down staircase algorithm until a subjective sensory detection threshold is detected, wherein the detection of the subjective sensory detection threshold implies recording body responses from the subject by means of a monitoring module;
• and
• 4) comparing the obtained subjective sensory detection threshold with reference population values.

A method for diagnosing small fiber neuropathy, the method comprising the steps of:

• 1) providing a radiofrequency (RF) generator configured to deliver radiofrequency (RF) currents;
• 2) applying small-area probes to a subject's skin, wherein the small-area probes are capable of delivering the electromagnetic pulses to the subject's skin;
• 3) varying the RF stimulation intensity generated by the RF generator by means of an up-down staircase algorithm until a subjective pain threshold is detected, wherein the detection of the subjective pain threshold implies recording brain evoked potentials from an electroencephalogram from the subject by means of a monitoring module, this step comprising the sub steps of:
• a. increasing the stimulation intensity until an upper threshold is reached;
• and
• b. decreasing the stimulation intensity until a lower threshold is reached;
• 4) repeating sub steps a. and b. of step 3) a limited number of times to obtain a more precise estimation of the subjective pain threshold;
• 5) selecting a suitable multiplier of the detection threshold, and delivering a number of consecutive radiofrequency stimuli at different spots in the application region on the subject's skin while recording the brain evoked potentials from the electroencephalographic signals obtained in the electroencephalogram;
• 6) detecting salient features from the brain evoked potentials by means of an automatic detection algorithm;
• and
• 7) comparing the detected features with reference population values.