NICER: A New and Improved Consumed Endurance and Recovery Metric to Quantify Muscle Fatigue of Mid-Air Interactions
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866917692559065088 |
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| author | Li, Yi Tag, Benjamin Dai, Shaozhang Crowther, Robert Dwyer, Tim Irani, Pourang Ens, Barrett |
| author_facet | Li, Yi Tag, Benjamin Dai, Shaozhang Crowther, Robert Dwyer, Tim Irani, Pourang Ens, Barrett |
| contents | Natural gestures are crucial for mid-air interaction, but predicting and managing muscle fatigue is challenging. Existing torque-based models are limited in their ability to model above-shoulder interactions and to account for fatigue recovery. We introduce a new hybrid model, NICER, which combines a torque-based approach with a new term derived from the empirical measurement of muscle contraction and a recovery factor to account for decreasing fatigue during rest. We evaluated NICER in a mid-air selection task using two interaction methods with different degrees of perceived fatigue. Results show that NICER can accurately model above-shoulder interactions as well as reflect fatigue recovery during rest periods. Moreover, both interaction methods show a stronger correlation with subjective fatigue measurement (r = 0.978/0.976) than a previous model, Cumulative Fatigue (r = 0.966/ 0.923), confirming that NICER is a powerful analytical tool to predict fatigue across a variety of gesture-based interactive applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_08875 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | NICER: A New and Improved Consumed Endurance and Recovery Metric to Quantify Muscle Fatigue of Mid-Air Interactions Li, Yi Tag, Benjamin Dai, Shaozhang Crowther, Robert Dwyer, Tim Irani, Pourang Ens, Barrett Human-Computer Interaction Natural gestures are crucial for mid-air interaction, but predicting and managing muscle fatigue is challenging. Existing torque-based models are limited in their ability to model above-shoulder interactions and to account for fatigue recovery. We introduce a new hybrid model, NICER, which combines a torque-based approach with a new term derived from the empirical measurement of muscle contraction and a recovery factor to account for decreasing fatigue during rest. We evaluated NICER in a mid-air selection task using two interaction methods with different degrees of perceived fatigue. Results show that NICER can accurately model above-shoulder interactions as well as reflect fatigue recovery during rest periods. Moreover, both interaction methods show a stronger correlation with subjective fatigue measurement (r = 0.978/0.976) than a previous model, Cumulative Fatigue (r = 0.966/ 0.923), confirming that NICER is a powerful analytical tool to predict fatigue across a variety of gesture-based interactive applications. |
| title | NICER: A New and Improved Consumed Endurance and Recovery Metric to Quantify Muscle Fatigue of Mid-Air Interactions |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2406.08875 |