2026-05-30T21:16:18Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/345432026-02-03T11:33:27Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Roldán-Jiménez, Cristina author Bennett, Paul author Ortiz-García, Andrés author Cuesta-Vargas, Antonio author 2019-09-27 The latest studies of the 30-second sit-to-stand (30-STS) test aim to describe it by employing kinematic variables, muscular activity, or fatigue through electromyography (EMG) instead of a number of repetitions. The aim of the present study was to develop a detection system based on acceleration measured using a smartphone to analyze fatigue during the 30-STS test with surface electromyography as the criterion. This case study was carried out on one woman, who performed eight trials. EMG data from the lower limbs and trunk muscles, as well as trunk acceleration were recorded. Both signals from eight trials were preprocessed, being averaged and temporarily aligned. The EMG signal was processed, calculating the spectral centroid (SC) by Discrete Fourier Transform, while the acceleration signal was processed by Discrete Wavelet Transform to calculate its energy percentage. Regarding EMG, fatigue in the vastus medialis of the quadriceps appeared as a decrease in SC, with a descending slope of 12% at second 12, indicating fatigue. However, acceleration analysis showed an increase in the percentage of relative energy, acting like fatigue firing at second 19. This assessed fatigue according to two variables of a different nature. The results will help clinicians to obtain information about fatigue using an accessible and inexpensive device, i.e., as a smartphone. Roldán Jiménez, C.; Bennett, P.; Ortiz García, A.; Cuesta Vargas, A.I. Fatigue Detection during Sit-To-Stand Test Based on Surface Electromyography and Acceleration: A Case Study. Sensors 2019, 19, 4202. https://doi.org/10.3390/s19194202 https://hdl.handle.net/10630/34543 10.3390/s19194202 Fatiga (Fisiología)-Medición-Aparatos e instrumentos Fatigue detection during sit-to-stand test based on surface electromyography and acceleration: A case study