The world's first wiki where authorship really matters (Nature Genetics, 2008). Due credit and reputation for authors. Imagine a global collaborative knowledge base for original thoughts. Search thousands of articles and collaborate with scientists around the globe.
Using mirror visual feedback and virtual reality to treat fibromyalgia.
Fibromyalgia is a condition characterized by long term body-wide pain and tender points in joints, muscles and soft tissues. Other symptoms include chronic fatigue, morning stiffness, and depression. It is well known that these symptoms are exacerbated under periods of high stress. When pain becomes severe enough, the mind can enter what is known as a dissociative state, characterized by depersonalization - the feeling of detachment from one's physical body and the illusion of watching one's physical body from outside. In evolutionary terms, dissociative states are thought to be an adaptive mechanism to mentally distance oneself from pain, often during trauma. Similar dissociative experiences are reported by subjects who have used psychoactive drugs such as ketamine. We have previously used non-invasive mirror visual feedback to treat subjects with chronic pain from phantom limbs and suggested its use for complex regional pain syndrome: once considered intractable pain. We wondered whether such methods would work to alleviate the chronic pain of fibromyalgia. We tested mirror visual feedback on one fibromyalgia patient. On 15 trials, the patient's lower limb pain rating (on a scale from 1 to 10) decreased significantly. These preliminary results suggest that non-invasive dissociative anesthetics such as VR goggles, ketamine, and mirror visual feedback could be used to alleviate chronic pain from fibromyalgia. This would furnish us with a better understanding of the mechanism by which external visual feedback interacts with the internal physical manifestation of pain.[1]References
- Using mirror visual feedback and virtual reality to treat fibromyalgia. Ramachandran, V.S., Seckel, E.L. Med. Hypotheses (2010) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Use
