BibTex
@inproceedings{Kattoju:2022:10.20380/GI2022.20,
author = {Kattoju, Ravi Kiran and Taranta, Eugene M and Ghamandi, Ryan and Laviola, Joseph},
title = {Automatic Asymmetric Weight Distribution Detection and Correction Utilizing Electrical Muscle Stimulation},
booktitle = {Proceedings of Graphics Interface 2022},
series = {GI 2022},
year = {2022},
issn = {0713-5424},
location = {Montr{\'e}al, Quebec},
pages = {195 -- 208},
numpages = {13},
doi = {10.20380/GI2022.20},
publisher = {Canadian Information Processing Society},
}
Abstract
Postural control is a constant re-establishment process for the maintenance of balance and stability. Asymmetric weight distribution (AWD), characterized by uneven leg loading, leads to increased instability, injury, and progressive deterioration of posture and gait. Postural self-correction is automatically affected by the human body in response to visual, vestibular, and proprioceptive sensory information. However, simultaneous cognitive loads can increase the demand for extra resources and require balance monitoring and correction techniques. We address these issues with a novel physiological feedback system that utilizes load sensors for AWD detection, and electrical muscle stimulation (EMS) for automatic correction and restoration of balance by affecting a counter-weight shift. In a user study involving 36 participants, we compare our automatic approach against two alternative feedback systems (Audio and Vibro-tactile). We find that our automatic approach delivered faster correction and outperformed alternative feedback mechanisms and perceived to be interesting, comfortable and a potential commercial product.