Abstract-This paper presents the development of an intelligent microsurgical instrument to perform real-time tremor compensation within a handheld tool. The intelligent instrument senses its own motion, distinguishes between voluntary and erroneous motion, and manipulates its tip to cancel the undesired component in real-time. The on-board sensing unit is made up of a magnetometer-aided allaccelerometer inertial measurement unit and sensor fusion is performed via a quaternion-based Kalman filtering. Tremor is modeled and filtered by an adaptive zero-phase notch filter. The intraocular shaft manipulator is a three DOF piezoelectric actuated mechanism driven by a feedforward controller with inverse rate-dependent hysteresis model. Laboratory experimental results of the system will be presented.
Crowdsourcing and weak supervision offer methods to efficiently label large datasets. Our work builds on existing weak supervision models to accommodate ordinal target classes, in an effort to recover ground truth from weak, external labels.
We define a parameterized factor function and show that our approach improves over other baselines.
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