On the use of approximate entropy and sample entropy with centre of pressure time-series.
Luis Montesinos, Rossana Castaldo, Leandro Pecchia
PMID 30541587WHAT IT FOUND
For quiet-standing sway, sample entropy was more stable across analysis settings than approximate entropy.
It separated older adults with and without recent falls only for selected settings, mainly in 60-second front-to-back data.
Key findings
01Approximate entropy values for quiet-standing sway changed significantly depending on the analysis settings used.
02Sample entropy behaved more consistently than approximate entropy across combinations of analysis settings and data length.
03Sample entropy separated older adults with and without recent falls only for selected settings, while traditional sway displacement measures did not.
STILL TO COME
How it was doneWhat they foundWhat it means for PTs
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What it does not show
The faller group was small, with only 18 participants, so differences between fallers and non-fallers are fragile. The study compared people by past fall history, not future falls, so it does not show that entropy values predict falls. Entropy values changed a lot with analysis settings, so values from different studies may not be comparable. The data were filtered, and previous filtering has lowered sample entropy, so absolute values may not apply to unfiltered clinic data. Participants with physical disabilities were excluded, including poliomyelitis and cerebral palsy, so results may not apply to patients with those conditions.
Declared interests
The supplied text lists funding from Consejo Nacional de Ciencia y Tecnología and the Engineering and Physical Sciences Research Council. It does not report a commercial sponsor or author conflicts.
The easy way to misread this
Do not read entropy values as a validated fall-risk test. The study found faller and non-faller differences only for selected analysis settings, and only 18 fallers were analysed.