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Sensoring the Neck: Classifying Movements and Actions with a Neck-Mounted Wearable Device
Content Provider | MDPI |
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Author | Lacanlale, Jonathan Isayan, Paruyr Mkrtchyan, Katya Nahapetian, Ani |
Copyright Year | 2022 |
Description | Sensor technology that captures information from a user’s neck region can enable a range of new possibilities, including less intrusive mobile software interfaces. In this work, we investigate the feasibility of using a single inexpensive flex sensor mounted at the neck to capture information about head gestures, about mouth movements, and about the presence of audible speech. Different sensor sizes and various sensor positions on the neck are experimentally evaluated. With data collected from experiments performed on the finalized prototype, a classification accuracy of 91% in differentiating common head gestures, a classification accuracy of 63% in differentiating mouth movements, and a classification accuracy of 83% in speech detection are achieved. |
Starting Page | 4313 |
e-ISSN | 14248220 |
DOI | 10.3390/s22124313 |
Journal | Sensors |
Issue Number | 12 |
Volume Number | 22 |
Language | English |
Publisher | MDPI |
Publisher Date | 2022-06-07 |
Access Restriction | Open |
Subject Keyword | Sensors Wearable Computing Interaction Design Neck-mounted Interface Flex Sensor Machine Learning (ml) |
Content Type | Text |
Resource Type | Article |