Stuttering is a common speech disorder that can impact in the quality of life of adults who stutter (AWS). In order to manage this condition, it is necessary to measure and assess the stuttering severity before, during and after any therapeutic process. To evaluate it, monitoring biosignals-included the respiratory patterns-could be an option; however is not clear the difference between speech conditions. Therefore, we compare the respiratory patterns and biosignals during speech of adults who stutter (AWS) and who not stutter (AWNS) to describe the differences and patterns of blocks and fluent speech. Sixty-six participants (AWS=33, AWNS=33) were asked to perform a reading task. We record the respiratory patterns and biosignals (pulse, saturation and galvanic response) using standardized system. We assess the differences among three conditions: fluent speech from ANWS, blocks from AWS and fluent speech from AWS. A higher number of expiratory volume peaks and amplitudes were found during the blocks segments compared to the fluent speech segments. These different patterns could be used to differentiate speech conditions using a recognition algorithm to automate evaluations in a real-Time environment for stuttering diagnosis or follow-up.