Studies have shown that a large percentage of amputees feel pain in their missing limbs. This condition, known as phantom limb pain (PLP), is caused by the part of brain responsible for a limb's movement becoming idle once that limb is lost. The ailment has so far proven difficult to treat, but a new study suggests therapy involving augmented reality and gaming could stimulate these unused areas of the brain, resulting in a significant reduction in discomfort.
Previous attempts to ease PLP by replicating sensory feedback from an artificial hand have included prosthetics and a treatment known as mirror therapy, where a reflection of the real-world limb is used to replace the phantom limb.
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Virtual reality systems have resulted in more sophisticated mirror therapy, but the approach is only useful for the treatment of one-sided amputees.
A research team from Sweden's Chalmers University of Technology sought to overcome this and achieve greater levels of relief by testing a treatment where the virtual limb would be controlled through myoelectric activity, that is, detecting muscle signals which would control the phantom limb at the stump.
In testing the treatment, the team used myolectric pattern recognition to predict phantom movements in the stump of a chronic PLP patient. By using the patterns as inputs in an augmented setting where a virtual arm was superimposed on the patient's real-life body, as well as controlling a car racing game, the team were able to gradually reduce the pain reported by the patient to zero.
Notably, the patient, who has suffered from PLP for 48 years, had previously shown a high resistance to mirror therapy along with a multitude of treatments. While the team points out that its research is based on the study of only one patient, the success in achieving pain relief following a series of unsuccessful treatments is expected to precipitate wider studies of its efficacy. The therapy is demonstrated in the video below.
The team's research was recently published in the journal Frontiers in Neuroscience