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DTSTART;TZID=America/Denver:20240728T180000
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UID:siggraph_SIGGRAPH 2024_sess211_papers_1115@linklings.com
SUMMARY:NICER: A New and Improved Consumed Endurance and Recovery Metric t
 o Quantify Muscle Fatigue of Mid-air Interactions
DESCRIPTION:Yi Li, Benjamin Tag, and Shaozhang Dai (Monash University); Ro
 bert Crowther (University of New England); Tim Dwyer (Monash University); 
 Pourang Irani (The University of British Columbia, Okanagan); and Barrett 
 Ens (The University of British Columbia, Okanagan; Monash University)\n\nN
 atural gestures are crucial for mid-air interactions, but predicting and m
 anaging muscle fatigue is challenging. We present a new computational mode
 l, NICER, which combines a correction term for 3D interaction and a recove
 ry factor for a rest period to predict fatigue across a variety of gesture
 -based interactive applications.\n\nInterest Area: Arts & Design, Producti
 on & Animation, Research & Education\n\nRecording: Livestreamed, Recorded\
 n\nRegistration Category: Full Conference, Full Conference Supporter, Virt
 ual Access, Experience, Exhibitor Full Conference, Exhibitor Experience, S
 unday\n\n
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