<p dir="ltr">Sensory feedback is a critical component for controlling neuroprosthetic devices and brain-machine interfaces (BMIs). A lack of sensory pathways can result in slow, coarse movements when using either of these technologies and, in addition, the user is unable to fully interact with the environment around them. Spinal cord stimulation (SCS) has shown potential for restoring these pathways, but traditional stimulation patterns with constant parameters fail to reproduce the complex neural firing necessary for conveying sensory information. Recent studies have proposed various biomimetic stimulation patterns as a more effective means of evoking naturalistic neural activity and, in turn, communicating meaningful sensory information to the brain. Unlike conventional patterns, biomimetic waveforms vary in frequency, amplitude, or pulse-width over the duration of the stimulation. To better understand the role of these parameters in sensory perception, this thesis worked to investigate the effects of SCS patterns utilizing stochastic frequency modulation, linear frequency modulation, and linear amplitude modulation. By calculating sensory detection thresholds and just-noticeable differences, the null hypothesis for stochastically-varied frequency and linear amplitude modulation techniques was rejected.</p>