Possible predictive formulas for quantitative and time-based estimation of muscle strength during motion.
Umi Matsumura, Ayana Kai, Miku Numata and 3 others
PMID 32082024WHAT IT FOUND
Wearable sensors and limb length and weight formulas estimated knee joint moments during half squat and single-leg knee bending fairly closely, but walking knee prediction was less close and ankle estimates were poor during half squat and peak values often differed.
Key findings
01During half squat, knee joint moment prediction had good to excellent agreement with actual moments (reported correlation coefficient 0.93), while ankle joint moment prediction had little correlation (0.34).
02During single-leg knee flexion and extension, predicted ankle and knee moments showed good to excellent agreement, with reported correlation coefficients of 0.89, 0.78, and 0.94.
03During walking, predicted ankle moment was 0.79 and predicted knee moment was 0.51, and the paper rated both as moderate to good.
STILL TO COME
How it was doneWhat they foundWhat it means for PTs
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What it does not show
The formulas were created and tested in only 29 young healthy adults, and people with orthopedic conditions were excluded, so they do not show accuracy in patients. The method can estimate only ankle and knee joint moments in the sagittal plane, not other joints or movement directions. It cannot measure joint moments with the same accuracy as large laboratory devices. Peak predicted moments often differed from actual moments. The ankle prediction had little correlation during half squat (0.34), and walking knee prediction was only 0.51. Only vertical components were used to keep the method simple rather than strictly accurate.
Declared interests
There were no funding or conflicts of interest to this research.
The easy way to misread this
Do not assume these formulas are ready for clinical muscle strength estimation. They were tested only in young healthy adults, only sagittal plane ankle and knee moments were modeled, and predicted peak values often differed from actual values.