@inproceedings{Rokhmanova2023Wearable,
title = {Wearable Biofeedback for Knee Joint Health},
author = {Nataliya Rokhmanova (Haptic Intelligence Department, Max Planck Institute for Intelligent Systems)},
url = {https://hi.is.mpg.de/, Website},
doi = {10.1145/3544549.3577063},
year = {2023},
date = {2023-04-28},
urldate = {2023-04-28},
abstract = {The human body has the tremendous capacity to learn a new way of walking that can reduce risk of musculoskeletal disease progression. Wearable haptic biofeedback has been used to teach this new gait to patients with knee osteoarthritis, enabling reductions in pain and improvement in function. However, this promising gait retraining therapy is not yet a part of standard clinical practice. Here, I propose a two-pronged approach to improving the design and implementation of biofeedback for gait retraining. The first section concerns prescription, with the aim of providing clinicians with a model that predicts the mechanical outcome of gait retraining in order to best guide their treatment decisions. The second section concerns learning, by seeking to understand how internal physiological state and external environmental factors influence the process of learning a therapeutic gait. This work aims to address the challenges keeping this intervention from being widely used to maintain pain-free mobility throughout the lifespan. },
keywords = {Doctoral Consortium},
pubstate = {published},
tppubtype = {inproceedings}
}