Advancements in biophotonics have driven the development of miniaturized imaging probes for high-resolution in vivo imaging. Probe-based confocal laser endomicroscopy (pCLE) enables cellular-level visualization of tissues but remains challenging for retinal imaging due to the need for non-contact operation, tremor compensation, and precise focal control. This study introduces a novel handheld confocal endomi-croscope system that integrates a custom-built imaging probe, an optical coherence tomography (OCT) distance sensor, and motor-assisted tremor suppression to improve imaging stability and resolution. The system employs a fiber-based common-path swept-source OCT (CPSS-OCT) sensor to maintain a stable focal distance while compensating for involuntary hand tremors using motorized stabilization. A gated recurrent unit (GRU)-based tremor prediction algorithm further enhances image stability. The imaging probe features a PZT tube-driven fiber cantilever resonance for Lissajous scanning, providing a wide field of view with minimal image distortion. In experiments using bovine eye samples, the CR score improved from 0.318 to 0.472, with a 48.43% increase in the in-focus condition when tremor compensation was activated, confirming enhanced image clarity and stability. Experimental results demonstrate that the system effectively stabilizes imaging, reduces motion artifacts, and ensures high-resolution, non-contact retinal imaging. By addressing the limitations of conventional pCLE devices, this system represents a significant advancement in ophthalmic imaging and can potentially improve retinal diagnostics and precision-guided interventions.

Diseases affecting the retina, such as retinal detachment, diabetic retinopathy, and macular degeneration, are significant contributors to blindness globally, with a substantial risk of vision loss among those afflicted. Surgical treatment of these conditions is complex due to the delicate nature of retinal tissue and the challenges posed by involuntary hand movements. While existing methods aim to compensate for hand tremors using sensor-based systems, they are hindered by limitations in accurately tracking retinal surface movement during surgery, particularly in response to patient movements under anesthesia. To address these issues, this study proposes a novel handheld micro-surgical tool equipped with a 1-degree of freedom (DOF) mechanism and a 3-axis Hall sensor to mitigate physiological hand tremors effectively. By utilizing magnetic flux density measurements, the tool can pinpoint the position of a magnet embedded within the surgical instrument, enabling precise tremor compensation without reliance on a global coordinate system. The design incorporates a piezoelectric (PZT) linear actuator and a Hall sensor for compactness and sensitivity. Optimization of the magnet’s dimensions through simulation ensures optimal sensor performance. Experimental validation using artificial and ex-vivo porcine eye models demonstrates the tool’s effectiveness in reducing hand tremors, suggesting potential enhancements in the safety and accuracy of retinal surgeries. For the desired positions from 4000 µm to 1000 µm, the RMS error of the synthetic eye model and porcine eye decreased from 71.10 µm to 33.27 µm and 71.36 µm to 33.39 µm, respectively.

Human-robot interaction (HRI) demands efficient time performance along the tasks. However, some interaction approaches may extend the time to complete such tasks. Thus, the time performance in HRI must be enhanced. This work presents an effective way to enhance the time performance in HRI tasks with a mixed reality (MR) method based on a gaze-speech system. In this paper, we design an MR world for pick-and-place tasks. The hardware system includes an MR headset, the Baxter robot, a table, and six cubes. In addition, the holographic MR scenario offers two modes of interaction: gesture mode (GM) and gaze-speech mode (GSM). The input actions during the GM and GSM methods are based on the pinch gesture and gaze with speech commands, respectively. The proposed GSM approach can improve the time performance in pick-and-place scenarios. The GSM system is 21.33 % faster than the traditional system, GM. Also, we evaluated the target- to-target time performance against a reference based on Fitts' law. Our findings show a promising method for time reduction in HRI tasks through MR environments.