The complexity of factors underlying an individual’s gait behavior and overall biomechanical strategy dictate that the methods we use to assess, diagnose, and intervene in walking biomechanics are tailored to the individual. Here we assume a human-centered approach to the observational gait analysis of simulated walking patterns as well as the development of lower-limb assistive mobility interventions optimized for the individual. By understanding the unique movements, geometries, dynamics, and control strategies that underly an individual’s walking behaviors, as well as how these behaviors are characterized, we can better design gait analysis methods and interventions to fit the individual. In Chapter 1, we investigate the capacity of novice observers to characterize gait behavior corresponding with the biomechanical performance objectives underlying an individual’s motor control strategy using a lexicon of contrasting adjective pairs. We test the hypothesis that visual characterization of physics-based musculoskeletal predictive simulations of walking would be sensitive to the biomechanical objective used by individuals, as well as the visual perspective. A pool of 100 crowd workers rated each of 75 full-body predictive gait simulation videos—including five subject models, five biomechanical objectives, and three visual perspectives—on a 1-5 scale using stylistic labels corresponding to each objective. The crowd worker response styles present in Chapter 1 indicated the lexicon may have used unclear terminology. Chapter 2 describes the proposed methodology for a follow-up qualitative case study to derive emergent terminology and improve lexicon clarity for future assessment of videotaped observational gait analysis using the wisdom of crowds. In Chapter 3, we investigate the biomechanics of seven children with spastic, diplegic cerebral palsy walking independently with a crouch gait. The excess flexion work performed at the hip, knee, and ankle joints without intervention was evaluated alongside the power-generating potential of soft exosuit bands applied about the spanned joints. We modeled the soft exosuit’s interactions with the user’s body surface to map how their unique walking patterns, anthropometrics, and adipose distribution affect the device’s efficacy to estimate the optimal soft exosuit intervention approach.