Authors:
Iman Ismail
and
Ernest Kamavuako
Affiliation:
Department of Engineering, King’s College London, London WC2R 2LS, U.K.
Keyword(s):
Dehydration, Electromyography Sensors, Fluid Intake, Volume Quantifying, Swallowing.
Abstract:
Insufficient fluid intake in older adults, in particular, is a worrying problem and an actual concern that warrants
scrutiny. Monitoring fluid intake is essential to avoid dehydration and overhydration problems. This paper
presents an investigation to estimate the fluid intake volume using surface Electromyographic (sEMG) sensors.
Eleven subjects participated in the experiment, and sEMG recordings of swallows from cups, bottles, and
straws were collected. Four features were extracted from the EMG signals. Seven regression algorithms were
implemented for quantifying the volume of swallowed fluid: Random Forest (RF), Support Vector Regressor,
K-nearest neighbour (KNN), Linear Regressor (LR), Decision Tree (DT), Lasso and Ridge. The mean sip
volume across subjects was 14.85 ± 5.05 ml. Results showed that using Random Forest, the root mean
square (RMSE) for estimating fluid intake volume using one the Mean Absolute Value feature gave 1.37 ±
1.1 ml. These results indicate a step forward i
n estimating fluid intake volume based on sEMG for hydration
monitoring.
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