Surface Stimulation to Alleviate Phantom Limb Pain

Student Author(s)

Derek Blok, Hope CollegeFollow

Faculty Mentor(s)

Dr. Katharine Polasek, Hope College

Document Type


Event Date



In the United States alone, 6,000-10,000 upper extremity amputations are performed each year. Phantom Limb Pain is a post-amputation phenomenon present in 50-80% of amputees, resulting in pain and/or extreme discomfort in the missing limb. The etiology of the pain is not known for sure, but one leading hypothesis involves the reorganization of the neural connections in the cerebral cortex causing the phantom sensations to arise from real sensations being experienced elsewhere. The working hypothesis is that if some form of “real” sensation can be created in the phantom limb, the cortical reorganization process can be slowed or reversed and the phantom limb pain can be significantly reduced. This will be done through electrical surface stimulation of the severed nerves in the residual limb, with the goal of producing sensations that seem to be arising from the phantom limb. Before this process can be attempted in amputee patients, however, significant testing must be done in healthy subjects to determine the effectiveness of surface stimulation to produce real sensations. In order to do this testing, testing parameters and stimulation capability requirements were determined and MATLAB software capable of providing a wide range of stimuli was developed. The experimenter can provide electrical stimulation to a pair of electrodes in the form of either symmetric or non-symmetric square waves, with full control of the pulse width, amplitude, frequency and duration of the stimulation. The software also has place for recording the data collected by the experimenter based on the responses of the subject. This data is saved both as an image of the left hand (the hand tested) with color coded sensations and numbers signifying intensity, and as a matrix array of values containing the same information in MATLAB. This allows for a variety of ways to perform data analysis.


This material is based upon work supported by the Dean of Natural and Applied Sciences’ Research Fund

This document is currently not available here.