Journal of Medical Internet Research 2024

Characteristic changes of the stance-phase plantar pressure curve when walking uphill and downhill – implications for long-term monitoring of gait patterns via insoles for smart healthcare

Wolff C., Steinheimer P., Warmerdam E., Dahmen T., Slusallek P., Schlinkmann C., Chen F., Orth M., Pohlemann T., Ganse B.

German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany


podiatry, podiatric medicine, movement analysis, ground reaction forces, wearables, slope, gait analysis, monitoring, gait, rehabilitation, treatment, sensor, injury, postoperative treatment, sensors, personalized medicine, movement, digital health, pedography, baropedography

podiatry, podiatric medicine, movement analysis, ground reaction forces, wearables, slope, gait analysis, monitoring, gait, rehabilitation, treatment, sensor, injury, postoperative treatment, sensors, personalized medicine, movement, digital health, pedography, baropedography


Background: Monitoring of gait patterns by insoles is popular to study behavior and activity in the daily life of people and throughout the rehabilitation process of patients. Live data analyses may improve personalized prevention and treatment regimens, as well as rehabilitation. The M-shaped plantar pressure curve during the stance phase is mainly defined by the loading and unloading slope, 2 maxima, 1 minimum, as well as the force during defined periods. When monitoring gait continuously, walking uphill or downhill could affect this curve in characteristic ways. Objective: For walking on a slope, typical changes in the stance phase curve measured by insoles were hypothesized. Methods: In total, 40 healthy participants of both sexes were fitted with individually calibrated insoles with 16 pressure sensors each and a recording frequency of 100 Hz. Participants walked on a treadmill at 4 km/h for 1 minute in each of the following slopes: −20%, −15%, −10%, −5%, 0%, 5%, 10%, 15%, and 20%. Raw data were exported for analyses. A custom-developed data platform was used for data processing and parameter calculation, including step detection, data transformation, and normalization for time by natural cubic spline interpolation and force (proportion of body weight). To identify the time-axis positions of the desired maxima and minimum among the available extremum candidates in each step, a Gaussian filter was applied (σ=3, kernel size 7). Inconclusive extremum candidates were further processed by screening for time plausibility, maximum or minimum pool filtering, and monotony. Several parameters that describe the curve trajectory were computed for each step. The normal distribution of data was tested by the Kolmogorov-Smirnov and Shapiro-Wilk tests. Results: Data were normally distributed. An analysis of variance with the gait parameters as dependent and slope as independent variables revealed significant changes related to the slope for the following parameters of the stance phase curve: the mean force during loading and unloading, the 2 maxima and the minimum, as well as the loading and unloading slope (all P

Moticon's Schlussfolgerungen

This study investigates the impact of walking on slopes on the plantar pressure stance phase curve measured by sensor insoles. Forty healthy participants walked on a treadmill with slopes ranging from -20% to 20%, using OpenGo sensor insoles to collect plantar pressure. Data were processed using Moticon software and a custom-developed data platform to analyze gait parameters. Results indicated significant changes in the stance phase curve due to slope variations. Downhill walking showed increased loading slopes and mean loading force, while uphill walking exhibited the opposite. The minimum force parameter was not effective in distinguishing slope directions. The study concludes that while long-term gait patterns are influenced by patient-specific factors, walking on slopes induces short-term characteristic changes.

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