This project contains data pertaining to the following citation: Haynes CA, Tenan MS, Passaro AD, Tweedell AJ. (in press) Investigating Imperceptible Vibrotactile Stimulation during a Force Stability Task. *Communications in Kinesiology*. **Abstract**: Imperceptible vibratory noise stimulation has shown to improve stability for both whole body postural control and simple motor control tasks. Noise stimulation is theorized to elicit a stochastic resonance-like effect within the somatosensory system, but there is disagreement in the literature regarding an optimal stimulation level for motor stability in humans. To explore vibrotactile stimulation, eighteen (18) participants performed an isometric finger flexion task with visual feedback while receiving noise stimulation scaled to varying percentages of their sub-sensory threshold level. Performance was quantified as the root-mean-square (RMS) error between the target force and the actual generated force values. The goals of the study were to determine: 1) whether force stability is significantly better when receiving their custom “principal” stimulation compared to other sub-sensory stimulation levels, and 2) if an individual’s principal stimulation level may be predicted by either their maximal voluntary contraction (MVC) or sub-sensory threshold level. A main effect of noise stimulation was observed (p < .001) indicating significantly better performance (lower RMS error) during the force stability task when individualized principal noise stimulation was applied. At the group level, task performance was significantly improved with principal noise stimulation compared to other stimulation levels (p ≤ .019). At the individual level, however, performance at the principal stimulation level was only significantly different than the distribution of errors for other stimulation levels for two individuals. Moderate to strong Spearman correlations (rs = .56 and rs = .65, respectively) suggest principal stimulation level increases with MVC and sub-sensory threshold. Files: See the document entitled "OSF Data Codebook.docx" for a description of the data files and analysis codes included for this project. This document includes descriptions of columns and variables contained within data sheets. Analysis codes were written in R, but comments within the scripts should aid users in translating the script to another statistical language if preferred.