This paper presents a practice-based exploration of affective bodily awareness through the sonification of muscle tonicity. We utilize Joakinator, a wearable interface combining electromyogram (EMG) and force-sensing resistor (FSR). Originally developed for performative applications, the system employs machine learning to flexibly map internal physiological activity to auditory parameters. Between 2023 and 2024, the interface was deployed across diverse artistic and academic workshops in the BODYinTRANSIT project framework. Engaging dancers, visual artists, musicians, and HCI/NIME researchers, the study utilized an exploratory methodology combining somatic practices, situated sound stimuli, and qualitative evaluation tools like BodyMaps. Findings indicate a shift in participants’ experience: rather than primarily producing new movement vocabularies or enhancing performative expressivity, the closed-loop sonification heightened interoceptive awareness regarding muscle tension, relaxation, and affective states. These results show that EMG-based sonification operates as a perceptual interface for sensory transformation. By highlighting how situated auditory feedback shapes somatic attention and affective awareness, this research opens new design spaces for affective computing within creative practices, somatic exploration, dance education, and physical rehabilitation.