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ORIGINAL ARTICLE Table of Contents   
Year : 2022  |  Volume : 15  |  Issue : 2  |  Page : 106-113
Using traditional typologies to understand posture movement and cognitive performance - A cross sectional study


1 National Resource Centre for Value Education in Engineering, Indian Institute of Technology, Delhi, India
2 National Resource Centre for Value Education in Engineering, Indian Institute of Technology; Department of Computer Science and Engineering, Indian Institute of Technology Delhi; Amar Nath and Shashi Khosla School of Information Technology, Indian Institute of Technology Delhi, New Delhi, India
3 Department of Humanities and Social Sciences, Indian Institute of Technology, New Delhi, India

Correspondence Address:
Ankit Gupta
Room No. 401, NRCVEE, Third Floor, Block V, IIT Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijoy.ijoy_12_22

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Context: We employed two classification methods that characterize psycho-somatotype categorization to understand motor and cognitive performance. The Trunk Index produces three somatotypes/body type categories: ectomorphs, mesomorphs, and endomorphs, and Prakriti classifications categorizes people into three categories: Vata, Pitta, and Kapha. Comparing these two categorization methods offers insights into anthropometric measures that combine psychological and physical characteristics to account for motor and cognitive behavior. Aims: The present study examined variations in cognitive and motor performances using the two typologies – prakriti and somato body types using cross-sectional study design. Subjects and Methods: The study employed fifty-eight healthy young adults, classified into prakriti (vata, pitta, kapha) and ecto-, meso-, endo- morph body types, to examine their cognitive performance (reaction time [RT] and accuracy), and motor performance (posture stability and posture accuracy) in standing yoga postures. Statistical Analysis Used: Analysis of covariance was performed to compare the cognitive and postural performance across the three somato and prakriti types after adjusting for age and gender as covariates. Post-hoc analysis of Bonferroni was performed with the consideration of Levene's test. Partial correlations were employed to investigate the correlation between postural stability and cognitive performance measures for each of the prakriti- and somato-body types as well as between the prakriti typology (scores) and trunk index values (adjusting the effects of age and gender as control variables). A P < 0.05 was selected at the statistical significance level. SPSS 26.0 version was used for the analysis. Results: Cognitive performance was observed to vary in terms of RT across somato- and prakriti body types (P < 0.05). Postural stability and cognitive performance are positively connected only for ectomorph body types (P < 0.05). Variations in motor performance were not significant. Barring ectomorph type, no other somato- and prakriti body types showed significant relationships between postural stability and cognitive performance. Likewise, the association between the features used for prakriti classification, and the trunk index scores showed marginal significance, only for a small subset of physical features of prakriti assessment (P = 0.055) (P1). Conclusions: Comparing classifications that use psychophysical attributes might offer insights into understanding variations in measures of motor and cognitive performance in a sample of healthy individuals.


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