Activity recognition in manufacturing: the roles of motion capture and sEMG+inertial wearables in detecting fine vs gross motion
In safety-critical environments, robots need to reliably recognize human activity to be effective and trust-worthy partners. Since most human activity recognition (HAR) approaches rely on unimodal sensor data (e.g. motion capture or wearable sensors), it is unclear how the relationship between the s...
Main Authors: | Kubota, Alyssa, Iqbal, Tariq, Shah, Julie A, Riek, Laurel D. |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Language: | English |
Published: |
IEEE
2020
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Online Access: | https://hdl.handle.net/1721.1/125890 |
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