Design and Validation of an FPGA-Based Configurable Transcranial Doppler Neurofeedback System for Chronic Pain Patients
Neurofeedback is a self-regulation technique that can be applied to learn to voluntarily control cerebral activity in specific brain regions. In this work, a Transcranial Doppler-based configurable neurofeedback system is proposed and described. The hardware configuration is based on the Red Pitaya...
| Autores: | , , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Conselleria de Salut i Consum del Govern de les Illes Balears |
| Repositorio: | Docusalut |
| Idioma: | inglés |
| OAI Identifier: | oai:docusalut.com:20.500.13003/9230 |
| Acceso en línea: | https://hdl.handle.net/20.500.13003/9230 |
| Access Level: | acceso abierto |
| Palabra clave: | Adolescent Chronic Pain Ultrasonography, Doppler, Transcranial Young Adult Adult Humans Female Aged Cerebrovascular Circulation Middle Aged Blood Flow Velocity Male Neurofeedback Ultrasonografía Doppler Transcraneal Dolor Crónico Femenino Adolescente Masculino Circulación Cerebrovascular Velocidad del Flujo Sanguíneo Humanos Persona de Mediana Edad Adulto Joven Anciano Adulto Neurorretroalimentación transcranial doppler ultrasound neurofeedback digital signal processing chronic pain fibromyalgia FPGA System on Chip |
| Sumario: | Neurofeedback is a self-regulation technique that can be applied to learn to voluntarily control cerebral activity in specific brain regions. In this work, a Transcranial Doppler-based configurable neurofeedback system is proposed and described. The hardware configuration is based on the Red Pitaya board, which gives great flexibility and processing power to the system. The parameter to be trained can be selected between several temporal, spectral, or complexity features from the cerebral blood flow velocity signal in different vessels. As previous studies have found alterations in these parameters in chronic pain patients, the system could be applied to help them to voluntarily control these parameters. Two protocols based on different temporal lengths of the training periods have been proposed and tested with six healthy subjects that were randomly assigned to one of the protocols at the beginning of the procedure. For the purposes of the testing, the trained parameter was the mean cerebral blood flow velocity in the aggregated data from the two anterior cerebral arteries. Results show that, using the proposed neurofeedback system, the two groups of healthy volunteers can learn to self-regulate a parameter from their brain activity in a reduced number of training sessions. |
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