Establishing Reference Data for Electromyographic Activity in Gait: Age and Gender Variations
Source abstract
Abstract
Instrumented gait analysis provides objective data for clinical assessment, with surface electromyography (EMG) serving as a key tool in identifying abnormal muscle activation. However, reliable reference data considering both age and gender remain limited. Age- and gender-related differences in lower-limb EMG during gait in typically developing individuals were examined in this study using statistical parametric mapping (SPM). We also determined the minimum sample size required for robust clinical reference data. Our findings revealed significant differences in muscle activation patterns across age and gender. Children exhibited increased rectus femoris activation in initial swing and greater hamstring activation in the midstance, whereas adults demonstrated greater semimembranosus activity at initial contact, increased soleus activation at push-off, and greater rectus femoris activity in late swing. Gender-based differences included greater tibialis anterior activation in females during the terminal stance and increased vastus lateralis activity during swing, whereas males showed greater vastus lateralis and biceps femoris activation during terminal swing. Additionally, significant age–gender interaction effects were observed in the biceps femoris and semimembranosus, with gender-related differences becoming more pronounced in adulthood. Power analysis indicates that at least 47 participants, with a minimum of 12 per subgroup (male children, female children, male adults, and female adults), are required to detect age–gender interactions reliably. We strongly recommend incorporating both age and gender in clinical norm bands to enhance the accuracy of gait assessments and improve clinical and research comparisons.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Muscle activation and electromyography studies · Balance, Gait, and Falls Prevention · Cerebral Palsy and Movement Disorders
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Clinic for Orthopaedics, Heidelberg University Hospital, Schlierbacher Landstr. 200a, 69118 Heidelberg, Germany
Funding
German Research Foundation (DFG)
References (36)
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