Related Experiment Video
Updated: Jul 30, 2026
Measurement of Spatial Stability in Precision Grip
Published on: June 4, 2020
Predictive analysis of dominant hand grip strength among young children aged 6-15 years using machine learning
Mastour Saeed Alshahrani1, Resmi Ann Thomas2, Paul Silvian Samuel1
1Department of Medical Rehabilitation Sciences, King Khalid University, Abha, Saudi Arabia.
Insights
Anthropometric and demographic factors significantly influence children's hand grip strength. Age, weight, and hand span are key for boys, while body mass index and hand dimensions are crucial for girls.
Area of Science:
- Pediatrics
- Biometrics
- Human Physiology
Background:
- Hand grip strength (HGS) is a key indicator of overall health and functional capacity in children.
- Understanding the factors influencing HGS is crucial for monitoring child development and identifying potential health issues.
Purpose of the Study:
- To investigate predictor variables influencing hand grip strength in young children.
- To determine the specific roles of anthropometric and demographic factors in HGS.
Main Methods:
- Collected anthropometric data (age, height, weight, hand dimensions) from 304 children.
- Utilized decision tree and regression machine learning models to analyze predictor variables.
- Developed separate predictive models for boys and girls to assess HGS determinants.
Main Results:
- For boys, age, hand span, and weight were significant predictors of HGS. Weight was the primary predictor for younger boys, while hand span became more important for older boys.
- For girls, backward regression identified body mass index (BMI), hand length, hand span, and palm length as significant predictors of HGS, explaining 66.46% of the variance.
Conclusions:
- Anthropometric factors significantly impact HGS in children.
- Predictors of HGS differ between genders, with distinct variables being most influential for boys and girls.
Background:
This study aimed to investigate and understand predictor variables and isolate the exact roles of anthropometric and demographic variables in the hand grip strength of young children.
Material And Methods:
In total, 315 male and female children participated in the study and 11 participants were excluded, therefore, 304 participants completed the assessments. Anthropometric measurements were collected at the time of study, along with age, height, weight, circumference of the hand, hand span, hand length, palm length, and hand grip strength (HGS) was measured. Both decision tree and regression machine learning analyses were used to isolate the relative contribution of independent features in predicting the targeted grip strength of children.
Results:
Two predictive models were developed to understand the role of predictor variables in dominant hand HGS for both boys and girls. For boys, the decision tree was found to be the best model with the lowest error in predicting HGS. The respondents' age, hand span, and weight were the most significant contributors to male hand grip strength. For the boys under 9.5 years of age, based on the decision tree analysis, weight (split at 27.5 kg) was found to be the most significant predictor. Furthermore, for the boys under 14.5 years of age, weight (split at 46.7 kg) remained the most important predictor. For boys 14.5 years and older, hand span was important in predicting handgrip strength. Backward regression was found to be the best model for predicting female hand grip strength. The R 2 value for the model was 0.6646 and the significant variables were body mass index (BMI), hand length, hand span, and palm length, showing significance at a p-value of ≤0.05. This model predicted 66.46% of the variance in handgrip strength among the girls.
Conclusion:
Anthropometric factors played a significant role in hand grip strength. Age, weight, and a larger hand span were found to be significant in impacting male HGS, while BMI, hand length, and palm length contributed to higher grip strength among the girls.
Related Concept Videos
01:14Decision Making: Traditional Method
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
01:19Survival Tree
Building a Survival Tree
Constructing a survival tree begins...