Frontiers in Bioengineering and Biotechnology

Effects of age, body height, body weight, body mass index and handgrip strength on the trajectory of the plantar pressure stance-phase curve of the gait cycle

Christian Wolff, Patrick Steinheimer, Elke Warmerdam, Tim Dahmen, Philipp Slusallek, Christian Schlinkmann, Fei Chen, Marcel Orth, Tim Pohlemann, Bergita Ganse

German Research Center for Artificial Intelligence (DFKI), Saarbrücken


ageing, gait, ground reaction (forces), handgrip strengh, insoles, motion analysis, obesity, smart healthcare


The analysis of gait patterns and plantar pressure distributions via insoles is increasingly used to monitor patients and treatment progress, such as recovery after surgeries. Despite the popularity of pedography, also known as baropodography, characteristic effects of anthropometric and other individual parameters on the trajectory of the stance phase curve of the gait cycle have not been previously reported. We hypothesized characteristic changes of age, body height, body weight, body mass index and handgrip strength on the plantar pressure curve trajectory during gait in healthy participants. Thirty-seven healthy women and men with an average age of 43.65 ± 17.59 years were fitted with Moticon OpenGO insoles equipped with 16 pressure sensors each. Data were recorded at a frequency of 100 Hz during walking at 4 km/h on a level treadmill for 1 minute. Data were processed via a custom-made step detection algorithm. The loading and unloading slopes as well as force extrema-based parameters were computed and characteristic correlations with the targeted parameters were identified via multiple linear regression analysis. Age showed a negative correlation with the mean loading slope. Body height correlated with Fmeanload and the loading slope. Body weight and the body mass index correlated with all analyzed parameters, except the loading slope. In addition, handgrip strength correlated with changes in the second half of the stance phase and did not affect the first half, which is likely due to stronger kick-off. However, only up to 46% of the variability can be explained by age, body weight, height, body mass index and hand grip strength. Thus, further factors must affect the trajectory of the gait cycle curve that were not considered in the present analysis. In conclusion, all analyzed measures affect the trajectory of the stance phase curve. When analyzing insole data, it might be useful to correct for the factors that were identified by using the regression coefficients presented in this paper.

Moticon's Summary

In this study the authors aimed to investigate the influence of multiple anthropometric and individual factors on gait patterns. Investigated influencing factors included age, body height, body weight, BMI and handgrip strength. Differences in gait patterns were investigated based on the total force and related gait metrics which was collected using Moticon's OpenGo sensor insoles. The relationship between target factors and gait metrics was assessed using multiple linear regression analysis. The authors found correlations between all influencing factors and various gait metrics. Within the scope of this investigation 46% of the variability in gait could be explained by these factors.

Contact Us
Book a free online demo or use the contact form to get in touch
Subscribe to our newsletter for regular updates

Select your desired system

The cutting edge test based outcome assessment system for health professionals and trainers

The most versatile toolkit for free data acquisition and comprehensive analytics in research

Have a general inquiry?

Write us a message for general questions about products and solutions or if you’d like to discuss other topics.

The form was sent successfully.

You will be contacted shortly.


Stay one step ahead!

Subscribe to our newsletter for the latest information on case studies, webinars, product updates and company news

Get support

Check our FAQ database for answers to frequently asked questions

Describe your issue in as much detail as possible. Include screenshots or files if applicable.

Need help?
Want a live demo?
Interested in prices?
Want to say hello?
Always just a call away
+49 89 2000 301 60