Normalization of the hip abductors rate of activation during a voluntary step task in older adults: Reliability and differences among approaches.
Marcel B Lanza, Nathan Frakes, Vicki L Gray
PMID 39024986WHAT IT FOUND
Different ways of scaling muscle activity data during a stepping test produce different numbers, but all methods are consistent across trials.
Researchers should use the peak muscle activity during the step to normalize data, as this method was reliable for all muscles and sides.
Key findings
01Normalizing rate of activation using different reference values (baseline, mean, or peak) resulted in significantly different percentage values for the hip muscles.
02The reference values used for normalization were reliable across trials for almost all conditions, with only two exceptions for the tensor fascia latae muscle.
03Using the peak EMG value during the trial as the reference is recommended because it showed excellent reliability across all conditions and provides an intuitive index of performance.
STILL TO COME
How it was doneWhat they found
Read the rest of this summary
You get three full summaries a month, free, and we do not ask for a card. Search, the TL;DRs and your library stay unlimited either way.
What it does not show
The study only assessed reliability within a single session (inter-trial), not across different days (between-day), which is more relevant for tracking patient progress over time. The sample consisted of healthy older adults, so results may not apply to those with significant mobility impairments or conditions like stroke. The task was a voluntary step with predictable timing; reliability might differ during reactive or perturbation-based stepping tasks.
Declared interests
The authors declare no conflicts of interest. The study was supported by an NIH Extramural grant.
The easy way to misread this
Do not interpret the different percentage values produced by each normalization method as evidence that the muscle performance changed. The underlying muscle activity was the same; only the mathematical scaling differed. Use the same normalization method when comparing studies or data sets.