Results and complications of surgeons-in-training learning bimanual microincision cataract surgery

PURPOSE: To evaluate visual outcomes and complications of bimanual microincision cataract surgery performed by surgeons in training. SETTING: Institute of Ophthalmology, University of Modena and Reggio Emilia, Modena, Italy. DESIGN: Prospective case series. METHODS: The corrected distance visual acuity (CDVA), astigmatism, corneal pachymetry, and endothelial cell count were evaluated before and 7 and 30 days after bimanual MICS performed by surgeons in training. Intraoperative and postoperative complications were also recorded. RESULTS: Three surgeons in training performed bimanual MICS in 150 eyes of 131 patients. There were 18 intraoperative complications (12.0%) (10 iris traumas [6.6%]; 4 capsule ruptures without vitreous loss [2.7%]; 3 capsule ruptures with vitreous loss [2.0%]; 1 intraocular lens [IOL] implantation in the sulcus due to zonular laxity [0.7%]). There were 5 postoperative complications (3.3%) (2 iris prolapses [1.3%]; 1 IOL loop malposition [0.7%]; 1 narrowing of anterior chamber [0.7%]; 1 capsulorhexis phimosis [0.7%]). Thirty days postoperatively, the mean CDVA improvement was 0.53 ± 0.20 (Snellen decimal) (P < .05), the mean decrease in astigmatism was 0.09 ± 0.54 diopter (P = .29), and the mean increase in corneal pachymetry was 7.42 ± 22.01 μm (P = .12). There was statistically significant endothelial cell loss (mean 496.50 ± 469.66 cells/mm(2)) (P < .05). CONCLUSIONS: Bimanual MICS performed by surgeons in training was safe and effective. Visual outcomes and complication rates were similar to those reported for coaxial cataract surgery performed by surgeons in training

Long-term follow-up for bimanual microincision cataract surgery: Comparison of results obtained by surgeons in training and experienced surgeons

Purpose: To determine the efficacy of bimanual microincision cataract surgery (B-MICS) performed by surgeons in training, evaluating clinical results, posterior capsule opacification (PCO) incidence, and clear corneal incision (CCI) architecture in a long-term follow-up and comparing results with those obtained by experienced surgeons. Patients and methods: Eighty eyes of 62 patients operated on by three surgeons in training who used B-MICS technique for the first time were included in the study (Group A). Eighty eyes of 59 patients who underwent B-MICS by three experienced surgeons were included as a control group (Group B). Best corrected visual acuity, astigmatism, corneal pachymetry, and endothelial cell count were evaluated before surgery and at 1 month and 18 months after surgery. Anterior segment optical coherence tomography images were obtained to study the morphology of CCIs. PCO incidence was evaluated using EPCO2000 software. Results: Out of 160 surgeries included in the study, mean best-corrected visual acuity improvement at 18 months was 0.343\ub10.246 logMAR for Group A, and 0.388\ub10.175 logMAR for Group B, respectively. We found no statistically significant induced astigmatism nor corneal pachymetry changes in either group, while we noticed a statistically significant endothelial cell loss postoperatively in both groups (P < 0.05). In Group A, mean PCO score was 0.163\ub10.196, while for Group B, it was 0.057\ub10.132 (P=0.0025). Mean length and inclination of the CCIs for Group A and Group B were, respectively, 1,358\ub1175 \ub5m and 1,437\ub1256 \ub5m and 141.8\ub0\ub16.4\ub0 and 148.7\ub0\ub15.1\ub0. As regards corneal architecture in the 320 CCIs considered, we found posterior wound retractions and endothelial gaps, respectively, 9.8% and 11.6% for Group A and 7.8% and 10.8% for Group B. Conclusion: B-MICS performed by surgeons in training is an effective surgical technique even when assessed after a long-term follow-up. PCO incidence resulted in being higher for less experienced surgeons. Corneal incisions were shorter and less angled in surgeons in training in comparison with results obtained by expert surgeons

Wide-Field Landers Temporary Keratoprosthesis in Severe Ocular Trauma: Functional and Anatomical Results after One Year

Purpose. To evaluate longitudinal functional and anatomical results after combined pars plana vitrectomy (PPV) and penetrating keratoplasty (PKP) using a wide-field Landers intraoperative temporary keratoprosthesis (TKP) in patients with vitreoretinal pathology and corneal opacity due to severe ocular trauma. Material and Methods. Medical records of 12 patients who had undergone PPV/PKP/KP due to severe eye trauma were analyzed. Functional (best-corrected visual acuity) and anatomic outcomes (clarity of the corneal graft, retinal attachment, and intraocular pressure) were assessed during the follow-up (mean 16 months). Results. Final visual acuities varied from NLP to CF to 2 m. Visual acuity improved in 7 cases, was unchanged in 4 eyes, and worsened in 1 eye. The corneal graft was transparent during the follow-up in 3 cases and graft failure was observed in 9 eyes. Silicone oil was used as a tamponade in all cases and retina was reattached in 92% of cases. Conclusions. Combined PPV and PKP with the use of wide-field Landers TKP allowed for surgical intervention in patients with vitreoretinal pathology coexisting with corneal wound. Although retina was attached in most of the cases, corneal graft survived only in one-fourth of patients and final visual acuities were poor

Human-Centered Design of a Collaborative Robotic System for the Shoe-Polishing Process

Demand for automated processes in the manufacturing industry is now shifting toward flexible, human-centered systems that combine productivity and high product quality, thus combining the advantages of automated and robotic systems with the high-value-added skills of operators and craftsmen. This trend is even more crucial for small and medium-sized enterprises operating in the “Made in Italy” fashion industry. The paper presents the study, simulation, and preliminary testing of a collaborative robotic system for shoe polishing that can reduce manual labor by limiting it to the finishing stage of the process, where the aesthetic result is fully achieved, with a benefit also in terms of ergonomics for the operator. The influence of process parameters and design solutions are discussed by presenting preliminary test results and providing hints for future developments

Chemical injury treated with autologous limbal epithelial stem cell transplantation and subconjunctival bevacizumab

Limbal stem cell (LSC) deficiency leads to corneal opacity due to a conjunctivalization of the corneal surface. LSC transplantation, which can be followed by corneal keratoplasty, is an effective procedure to restore corneal transparency; however, a common cause of failure of this procedure is neovascularization (NV)

Visual outcomes of posterior chamber intraocular lens intrascleral fixation in the setting of postoperative and posttraumatic aphakia

BACKGROUND: Several techniques for fixation of the posterior chamber intraocular lens (IOL) have been developed. We evaluate long-term functional outcomes and safety of posterior chamber IOL implantation using Hoffman scleral haptic fixation and sutureless Sharioth technique in patients with posttraumatic and postoperative aphakia. METHODS: This retrospective case-series included 42 eyes operated by one surgeon. The data including demographic data, ocular history, preoperative, early postoperative and final best corrected visual acuity (BCVA), rate of complications as well as postoperative IOL position were collected. The mean follow-up was 14.5 months. Hoffman haptic scleral fixation was performed in 31 eyes, Sharioth technique—in 11 eyes. Aphakia was due to eye trauma (19) or complicated cataract surgery (23). RESULTS: Overall, the final BCVA improved in 26 eyes, did not change in 5 eyes, and worsened in 11 eyes. No significant differences in BCVA were found between groups operated with Hoffman scleral fixation and Sharioth technique. Postoperatively, we noticed two dislocations of IOL fixated using Sharioth technique and none after Hoffman technique. No severe complications were observed. CONCLUSION: Both transscleral fixation techniques are feasible methods of secondary IOL implantation in posttraumatic and postoperative aphakia. with low incidence of complications, however visual outcomes are diverse

AI-Based Techniques for Enhancing Human-Robot Collaboration

Questa tesi di dottorato promuove la collaborazione tra umani e robot sviluppando un assistente robotico adattivo capace di garantire un’interazione sicura, fluida e produttiva. Nell’industria contemporanea ci sono processi dove non è possibile avere un’automazione totale, gli operatori apportano competenze e conoscenze indispensabili a processi specializzati, mentre i robot possono ridurre lo sforzo fisico, migliorare l’efficienza del flusso di lavoro e contribuire al benessere dell’operatore. Questa ricerca utilizza tecniche di intelligenza artificiale, tra cui machine learning, deep learning e large multimodal models, per creare postazioni di lavoro collaborative in cui umani e robot lavorano fianco a fianco in modo intuitivo, condividendo compiti e spazi operativi. I sistemi robotici sviluppati sono dotati di capacità di percezione, che consentono loro di rilevare, interpretare e rispondere agli input e umani in tempo reale. Grazie all’uso di dati provenienti da sensori e telecamere, il robot si adatta dinamicamente ai movimenti e alle intenzioni dell’operatore, dando priorità alla sicurezza e alla fluidità dell’interazione, ottimizzando allo stesso tempo il flusso di lavoro e riducendo lo sforzo umano. Queste capacità sono state testate in diverse postazioni robotiche, come in operazioni di assemblaggio e produzione, dimostrando come il robot possa migliorare la sicurezza e l’efficienza. Un aspetto chiave di questo lavoro è stato lo sviluppo di un sistema di percezione della postura del corpo umano mediante telecamere RGB-D, capace di monitorare in tempo reale la posizione delle articolazioni a una frequenza di 18 Hz, con una precisione verificata attraverso un sistema basato su IMU. Identificando la posizione dell’operatore, il robot può mantenere una distanza di sicurezza e adattarsi dinamicamente per evitare collisioni in diversi scenari operativi. Basandosi su questo sistema di tracciamento e di evitamento degli ostacoli, la tesi integra ulteriori funzionalità come la selezione di strumenti tramite gesti e il recupero automatico del tool usato dall’operatore, consentendo al robot di rispondere ai comandi dell’operatore in modo fluido e di prevenire collisioni, ribaltando così il tradizionale modello di interazione uomo-macchina. In collaborazione con l’Università di Coimbra, la ricerca ha inoltre sviluppato il sistema D-RMGPT, che utilizza large multimodal models per migliorare le attività di assemblaggio. Questo sistema permette di ridurre i tempi di assemblaggio del 33% per operatori principianti e offre una grande flessibilità grazie a prompt basati su immagini, eliminando la necessità di un ampio addestramento dei dati. Inoltre, un caso di studio che riguarda l’esecuzione di un processo, in questo caso la preparazione di una pizza, dimostra l’uso del modello GPT per comporre la sequenza del processo e gestire le azioni da far compiere al robot. Infatti, ricevendo gli input dell’operatore, come la selezione degli ingredienti tramite voce/gesti, e riconoscendo le azioni umane, il robot può decidere le sue azioni di risposta di conseguenza per fornire assistenza all’operatore durante il processo. Complessivamente, questi contributi stabiliscono un quadro robusto per una collaborazione uomo-robot adattabile, in tempo reale, e intuitiva, che migliora così il benessere dell’operatore e la produttività.This PhD thesis advances human-robot collaboration by developing an adaptive robotic assistant that ensures safe, seamless, and productive collaboration between humans and machines. In modern industry is not possible to apply full automation in some contests, humans contribute with essential knowledge and skills to specialized processes, while robots can assist by reducing physical strain, improving workflow, and enhancing operator well-being. This research leverages artificial intelligence techniques such as machine learning, deep learning, and large multimodal models to create a collaborative workstations where humans and robots work together intuitively, sharing tasks and workspace as one team. The proposed robotics systems are equipped with advanced perception capabilities, allowing them to detect, interpret, and respond to human actions and inputs in real time. Using sensors and cameras data, the robot adapts dynamically to the operator’s movements and intentions, prioritizing safety and fluency while optimizing workflow and minimizing the human effort. This capability was tested in various real-world robotic workstations, such as assembly and manufacturing tasks, where the robot provided safety and efficiency enhancements. A starting point of this work includes a human body pose perception system using RGB-D cameras, tracking joint positions in real time at 18 Hz with accuracy validated against an IMU wearable based system. By identifying the operator’s position, the robot maintains a safe distance and dynamically avoids collisions in various scenarios. Building on this skeleton tracking and obstacle avoidance framework, the thesis further integrates gesture-based tool selection and automatic tool retrieval, allowing the robot to respond fluidly to operator commands and to avoid it, effectively reversing the traditional human-machine interaction model. The research further developed, in collaboration with the University of Coimbra, D-RMGPT, a system employing large multimodal models for assembly tasks. This system reduces assembly time by 33% for novices and offers high flexibility through viiimage-based prompts without the need for extensive data training. Additionally, a case study involving a process execution, in this circumstance as an example a pizza preparation, demonstrates the use of a GPT model to compose the process sequence and manage the robot actions. In fact, receiving the operator’s inputs such as ingredient selection via voice/gestures and recognizing the human actions, the robot can adjust its responses accordingly to provide assistance to the operator during the process. Together, all these contributions establish a robust framework for adaptable, intuitive real-time human-robot collaboration that improves the human wellbeing and productivit