Self-reported functional mobility, balance confidence, and prosthetic use predict short-term average daily step counts as determined from research-grade accelerometers.

Both monitors accurately counted steps during forward linear walking. StepWatch appears to be more accurate than FitBit during complex walking but a larger sample size may confirm these findings. FitBit consistently counted fewer steps than StepWatch during free-living walking. Clinical relevance The StepWatch and FitBit are acceptable tools for assessing forward, linear walking for individuals with transtibial amputation. Given the results' consistenty in the free-living enviorment, both tools may ultimiately be able to be used to count steps in the real world, but more research is needed to confirm these findings.

Clinicians involved in prosthetic prescription may consider including the TUG, 10MWT, AMPPRO, and 6MWT during their clinical evaluations to help differentiate between individuals of higher functional mobility. The LCI and PEQ-MS may be less useful in classifying individuals as K3 versus K4 because of a ceiling effect.

A prosthetic limb should closely replicate the mechanical energy profiles of anatomical limbs. The unified deformable (UD) analysis may be valuable to facilitate future clinical prescription and guide fine adjustments of prosthetic componentry to optimize gait outcomes.

Introduction The ability to walk with different cadences (cadence variability) is considered an important factor for determining the functional ability of individuals with lower-limb amputation and making prosthetic recommendations. However, a method to quantify cadence variability of these individuals has never been presented before, so there are no standardized methodologies or values to guide prosthesis prescription. The purpose of this study was to develop and demonstrate feasibility of a method to quantify real-world cadence variability. Materials and Methods The method utilizes step-count data collected by an accelerometer-based activity monitor. Cadence at each minute is calculated. Then, the spread of the cadence data distribution during a 7-day observation period is measured to quantify cadence variability. To demonstrate feasibility, this method was applied to a set of step-count data for individuals with unilateral lower-limb amputation classified by their health care provider as a K2 or K3 ambulator. Results Results showed that this method was able to differentiate the cadence characteristics of individuals classified as K2 versus K3. On average, individuals classified as K2 walked with significantly less cadence variability than those classified as K3. Conclusions This study provides a novel method for objectively determining cadence variability and provides a foundation for ultimately developing normative cadence characteristic values for K2 and K3 levels.