Researchers from the University of Florida have developed a computational walking model to improve the gait of patients recovering from stroke, according to a press release.
“This modeling effort is an excellent example of how computer models can make predictions of complex processes and accelerate the integration of knowledge across multiple disciplines,” Grace Peng, PhD, director of the National Institute of Biomedical Imaging and Bioengineering Program in Mathematical Modeling, Simulation and Analysis, said in a press release.
The program uses mathematics, physics and computer science to construct a model of the patient from the patient’s walking data collected on a treadmill. The model predicts how the patient will walk after different planned rehabilitation treatments.
According to the release, the team tested the model on a patient who had a stroke. The group measured how the patient walked at his preferred speed on a treadmill. Using those measurements, the team constructed a unique neuromusculoskeletal computer model personalized to the patient’s skeletal anatomy, foot contact pattern, muscle force generating ability and neural control limitations.
Researchers found the model could accurately predict the patient’s gait at a faster walking speed, even though no measurements at that speed were used for constructing the model, according to the release.
According to the release, the researchers hope this will be the first step in creating personalized neurorehabilitation prescriptions, which they said would fill a gap in the current treatment planning process for patients who have had a stroke.
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Disclosure: The researchers report funding from the National Institute of Biomedical Imaging and Bioengineering.
