OpenZilo：人間中心センシングとロボットインタラクションのためのオープンなスマートリングプラットフォーム
OpenZilo: An Open Smart-Ring Platform for Human-Centric Sensing and Interaction with Robots
マイク・IMU・脈波・皮膚温センサを搭載したオープンなスマートリングで音声・ジェスチャによるロボット操作を評価し、認識精度と実タスク成功率・応答時間の両面からウェアラブルインタフェースを検証した。
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著者: Qianggang Ding, Xingyao Wang, Rui Feng, Chi Qin, Weijian Lin, Lizhi Ding, Jiankai Tang, Yuntao Wang, Xiangke Liu, Bang Liu
分類: cs.RO, cs.HC
原文アブストラクト
Wearable robot interfaces must connect user input to timely physical action. We present the proposed platform, an open smart-ring platform for studying this connection across task stages. The ring integrates a microphone, an inertial measurement unit, photoplethysmography, and skin-temperature sensing. Its software architecture separates acquisition, event interpretation, interaction policy, and robot execution. We characterize seven operating modes and evaluate speech and gesture control with 10 participants. Across five commands and 250 trials per modality, speech and gestures achieved task success rates of 90.4% and 88.8%, respectively. Recognition accuracy exceeded task success for both modalities. Gaussian hidden Markov models achieved higher accuracy than a support vector machine across three vocabulary sizes, with longer scoring times. Following a shared spoken task start, gesture-based adjustments had shorter median response times than speech. Whole-task success was 70.0% with gestures and 64.0% with speech. We further examine physiological-event-triggered robot interaction using simulated event notifications. Mean notification-receipt-to-arrival times were 11.71 s for the robot and 9.20 s for an on-site person. These descriptive findings support evaluating wearable robot interfaces through both recognition and physical outcomes, with timing measures appropriate to each task stage.