Evidence map›Paper›PMID 40622825›Full record

ArticleIEEE transactions on bio-medical engineering2026

An Active Spring Mass Model With Biomimetic Ground Reaction Forces for Multiple Terrains.

Saurav Kumar, Hartmut Geyer

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Saurav Kumar
Hartmut Geyer

Funding

CPS: Medium: Collaborative Research: User and Environment Interactive Planning and Control of Artificial Lower Limbs for Resilient Locomotion R01EB029765 · NIBIB · CARNEGIE-MELLON UNIVERSITY · PI GEYER, HARTMUT, SU, HAO · 2019 to 2021
$1.1M
NIBIB NIH HHS R01 EB029765
6 · The paper itself

Abstract

Common activities of daily living naturally blend walking on level ground, stairs, and slopes. Predicting human locomotion behavior across these environments is critical for control design in lower-limb assistive devices. One approach to achieving this goal is to use feedforward simulation of conceptual gait models that capture the whole body dynamics of human locomotion. So far, however, these models have mainly been developed to predict human walking and running dynamics on level ground.

objectiveTo develop a conceptual gait model that can walk on level ground as well as negotiate stairs and ramps of different inclinations (up to $\pm 42^\circ$) while producing biomimetic ground reaction forces (GRFs).

methodsWe extended the passive bipedal spring mass model by incorporating active elements, introducing seven control parameters. These parameters were then tuned to match the human GRFs for stairs.

resultsBy optimizing these control parameters, we found that the resultant model's GRF correlates strongly with human data with median Pearson correlation coefficients $R_{x}>0.89$ and $R_{y}>0.96$ for stair walking. Furthermore, we observe its predictive capabilities are not limited to stairs, as it can also mimic the GRFs of human slope walking. Finally, we conducted a parameter analysis to assess how model parameters affect GRFs and identified a reduced, five parameter model that can reproduce human GRFs with a fidelity similar to the seven parameter model. SIGNIFICANCE: The model may help to predict human locomotion behavior in more complex terrain, for instance, when planning foot placements in the interactive control of powered lower-limb exoskeletons and prostheses.

Indexed as

BiomimeticsGaitModels, BiologicalWalkingBiomechanical PhenomenaComputer SimulationHumans

Identifiers

PMID40622825
PMCPMC13052190

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.