Comparative study of machine learning algorithms to classify hand gestures from deployable and breathable kirigami-based electrical impedance bracelet

Comparative study of machine learning algorithms to classify hand gestures from deployable and breathable kirigami-based electrical impedance bracelet

10.3390/mti4030047

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Bibliographic Details
Main Authors: Vedhagiri, G.P.J., Wang, X.Z., Kumar, K.S., Ren, H.
Other Authors: BIOMEDICAL ENGINEERING
Format: Article
Published: MDPI AG 2021
Subjects:
Electrical impedance tomography
Gesture classification
Kirigami wearable device
Machine learning
Online Access:https://scholarbank.nus.edu.sg/handle/10635/197561
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Institution: National University of Singapore
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Summary:10.3390/mti4030047

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