Classifying interpersonal synchronization states using a data-driven approach: implications for social interaction understanding
Abstract This study presents a data-driven approach to identifying interpersonal motor synchrony states by analyzing hand movements captured from a 3D depth camera. Utilizing a single frame from the experiment, an XGBoost machine learning model was employed to differentiate between spontaneous and i...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-37316-5 |