Análise biomecânica-computacional de movimentos do ombro por meio do uso de acelerômetro

• Autor(a) principal: Vicenzi, Gustavo
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
• Texto Completo: http://tede.unioeste.br/handle/tede/4672
• topic: Biomecânica do ombro; Cinemática do ombro; Juntura escápulo-umeral; Shoulder biomechanical; Shoulder kinematics; Scapula-humerus joint; CIÊNCIAS DA SAÚDE

The measurement of range of motion is an important stage in the orthopedic physical examination. Considering that joints movements are based on physical quantities, this study presents a new method to determine and analyze the standard curves representing the shoulder motion of healthy individuals through a smartphone with an accelerometer app. The casuistry was represented by ten healthy subjects, which was confirmed by physical examination and ultrasonography; six of these individuals were female and four males with an average age of 24,5 ± 2,1 years old. The kinematic evaluation was executed in the subject´s right shoulder by an observer, who positioned the smartphone in the back part of the subjects´ wrists. These subjects performed ten repetitions of each one of the ten movements characterized by elevation, abduction, adduction, flexion, extension, internal rotation, external rotation, internal and external rotation with the member abducted and circumduction of the right upper member. The biomechanical data collected was used to outline Acceleration vs. Time graphics, which were employed to determine and study the physical quantities of acceleration, time, velocity, displacement and energy of the movements using a computer. First, the curves of each movement for each subject were discretized and mathematically modeled to reduce noise and smoothing through the polynomial method. The quality of the adjustments was certified by the mean, and respective standard deviation of the coefficients of determination (R2), and a standard curve was obtained for each movement performed by the subject (pvalue>0,05). The same method – means, and respective standard deviations of R2 – were considered to verify the quality of the standard model when comparing the model of each subject with the average model of the movement (p-value>0,05). By these models, it was possible to determine the region of the movement that characterizes a healthy individual. It is concluded that the use of accelerometers present in the smartphones enables, in a precise and accurate way, to determine and analyze the physical-mechanical parameters belonging to biomechanical behavior of shoulder movement in healthy individuals.