transcranial direct current stimulation and chronic pain

Conditions: Chronic Pain

Summary: this clinical trial uses transcranial direct current stimulation (tdcs) using the patented tkiwi system to safely reduce self-reported chronic pain with little to no side effects to improve our understanding and ability to accurately diagnose pain disorders which would facilitate the development of pharmacologic and non-pharmacologic treatment modalities using deep learning architecture built into the tkiwi.

pain is a severe and growing problem in the united states with more than 116 million americans suffering from chronic pain and more than $635 billion is spent annually on pain and its related healthcare costs. additionally, opioid addiction has become a national crisis with nearly 50,000 deaths every year as a result of opioid-involved overdoses and nearly $78.5 billion spent annually on opioid misuse and addiction. currently available treatments for pain, namely opioid analgesics, have limited effectiveness and can lead to a significant number of side effects and complications including dependence, pharmacodynamic tolerance, sedation, gastrointestinal issues, respiratory depression, immunosuppression, and hormonal changes. effectively treating pain requires an accurate assessment of pain, however current methods of diagnosing and evaluating pain depend on subjective self-reporting including the use of visual and numerical pain scales. the subjective nature of describing pain makes it virtually impossible to quantify and therefore difficult to treat and monitor. to overcome this subjectivity, through a non-invasive neuromodulation technique called transcranial direct current stimulation (tdcs) and deep learning, pain can be measured objectively using electroencephalograph (eeg) to assess and personalize treatment. the overarching goal of this project is to apply transcranial direct current stimulation (tdcs) as an alternative to opioids for the reduction in chronic pain. the investigator's long-term goal is to use these data to analyze eeg signals and generate personalized tdcs treatment in real time.

Eligibility criteria:
inclusion criteria: * age: 18-79 years old * gender: any * ethnicity: any * chronic pain (\> 3-months); no current use of nonprescription opioids (\< 1 month); able and willing to comply with scheduled visits and other study-related procedures to complete the study; willing and able to give informed consent. exclusion criteria: * diagnosis (as defined by dsm-iv) of: any psychotic disorder (lifetime); eating disorder (current or within the past year); obsessive compulsive disorder (lifetime)); mental retardation. * history of drug or alcohol abuse or dependence (as per dsm-iv criteria) within the last 3 months (except nicotine and caffeine). * subject is on regular benzodiazepine medication which it is not clinically appropriate to discontinue. * subject requires a rapid clinical response due to inanition, psychosis or high suicide risk. * neurological disorder or insult, e.g., recent stroke (cva), which places subject at risk of seizure or neuronal damage with tdcs. * subject has metal in the cranium, skull defects, or skin lesions on scalp (cuts, abrasions, rash) at proposed electrode sites. * female subject who is pregnant. * participants who are not fluent in english will not be included in the trial for safety reasons: a) it is usually not possible to have an interpreter reliably available every weekday for up to 4 weeks and it is not safe to give tdcs to a subject who cannot tell us immediately of any side effects; note that translation of the proposed act activity into english has not been validated and that we cannot be confident that they would be accurately translated and validated. * minors * older than 79 years old * last use \>24 months * history of eeg or any electrical implant (i.e. pacemaker) * history of parkinson's, diagnosis of bipolar, schizophrenia/schizo-affective d/o, ocd, epilepsy, alzheimers * taking antipsychotic drugs

Keywords: chronic pain transcranial direct current stimulation