Sistema para sincronização automática de estimulação elétrica no tratamento de insuficiência respiratória em pessoas com lesão medular

• Ano de defesa: 2015
• Autor(a) principal: Costa, Taisa Daiana da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Programa de Pós-Graduação em Engenharia Elétrica e Informática Industrial
• Palavras-chave em Português: Estimulação elétrica transcutânea do nervo; Medula espinhal - Ferimentos e lesões; Insuficiência respiratória; Processamento de sinais - Técnicas digitais; Algorítmos; Métodos de simulação; Engenharia biomédica; Engenharia elétrica; Transcutaneous electrical nerve stimulation; Spinal cord - Wounds and injuries; Respiratory insufficiency; Signal processing - Digital technique; Algorithms; Simulation methods; Biomedical engineering; Electric engineering
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/1271

The respiratory failure, caused by spinal cord injury in people with high thoracic paraplegia and tetraplegia, has been the major cause of death for those individuals. The total or partial paralysis of the abdominal muscles and the diaphragm hinders the production of cough and decreases tidal volume. This problem can be alleviated by treatment with transcutaneous functional electrical stimulation (TFES), on diaphragm and abdominal muscles synchronized with the spontaneous respiration. Few studies have been conducted on this matter, and it was found that is of great scientific interest the development of a system capable of automatically triggering the electrical stimulation with inspiration (diaphragmatic stimulation) and expiration events (abdominal stimulation). Therefore, in this work, a respiratory signal acquisition system was developed for the detection of inspiration and expiration events for triggering the electrical stimulation during quiet breathing. The system employs an elastic belt attached to a load cell based on strain gauges for acquiring the respiratory signal. An algorithm based on signal statistical analysis was developed for the detection of inspiration and expiration events. Tests were carried out in eight healthy volunteers. The belt was positioned at the last rib region, and signals were obtained with the aid of a digital oscilloscope. A physical therapist helped in the analysis of the signals by counting the inspiratory and expiratory events. The results reached the accuracy of 82% in the detection of inspiratory events, and 96% for expiratory events. The results indicate that the developed system is effective for the acquisition of respiratory signals and the created algorithm can provide synchronization of TFES with the patient in quasi-static situation during treatment.