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

Wearable devices are gaining recognition for their use as a biosensor platform. Electrical impedance tomography (EIT) is one of the sensing techniques that utilizes wearable sensors as its primary data acquisition system. It measures the impedance or resistance at the peripheral (skin) level and cal...

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Bibliographic Details
Main Authors: Godwin Ponraj Joseph Vedhagiri, Xin Zhi Wang, Kirthika Senthil Kumar, Hongliang Ren
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Multimodal Technologies and Interaction
Subjects:
kirigami wearable device
gesture classification
machine learning
electrical impedance tomography
Online Access:https://www.mdpi.com/2414-4088/4/3/47

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