The present research aimed to investigate the interrelationships between thermal and muscular variables, in order to provide the choice of the most representative forms of data from patients with fibromyalgia. The clinical protocol included 2 female subjects clinically diagnosed with fibromyalgia aged between 18 and 59 years and 3 healthy women in a second group. All of them underwent physiotherapeutic evaluation and acquisition of thermographic images of the pectoral muscles and a pectoral strength test in isometry using mechanomyography (MMG), with the signals processed by the online softwares Flir tools® and MATLAB®, respectively. Statistical analysis was performed using PAST 3. For thermography, the results obtained in the study were expressed by the mean temperature in the analyzed regions, while for MMG the results refer to calculations produced from online MMG signal processing in MATLAB®, both in time and spectral domains (MMGRMS and MMGFM). Principal component analysis (PCA) divided the data into components 1 (97.52%) and 2 (2.47%), placing healthy participants (1, 2 and 3) in the upper quadrants with higher values, while volunteers with fibromyalgia (4 and 5) were in the lower quadrants, presenting lower temperatures and values, showing a clear distinction between the two groups. MMG data showed that healthy participants 2 and 3 had the highest MMGRMS values, while fibromyalgia participant 5 had high values in component 1 (99.99%). Participants 4 (fibromyalgia) and 1 (healthy) showed similarities in component 2 (2.47%). For MMGFM, healthy women 2 and 3 had the lowest values in component 1 (58.74%), and woman with fibromyalgia 5 presented higher values in both components (Component 2 = 38.27%). Participant with fibromyalgia 4 had the lowest values in both components. The obtained results indicate interrelationships between the studied variables according to their inherent dimensions, with patterns recognition that can guide the existence of the possible differences between groups in larger samples.