Abstract: A robotic surgical system includes a control processor, surgeon console, and one or more robotic instruments. A procedure tracking module monitors surgical instrument activity, surgeon commands, imaging data, and system logs in real-time. An artificial intelligence (AI)-driven workflow optimization engine comprises at least one trained machine learning model and a data processing subsystem. The engine analyzes intraoperative data to detect inefficiencies or deviations from optimized surgical sequences and generates real-time workflow recommendations based on procedural urgency, risk assessment, and surgeon-specific behavior. A multimodal interface presents these recommendations via visual, auditory, or haptic cues and captures surgeon feedback for continuous AI refinement.

Abstract: A robotic surgical system is disclosed incorporating artificial intelligence (AI)-driven haptic feedback to enhance surgical precision and safety. The system includes a surgeon console, robotic arms with surgical tools, imaging devices, and sensors configured to acquire intraoperative data. A processor executes an AI model trained to infer anatomical context and generate haptic control parameters. A haptic feedback interface delivers force, vibration, shear, or thermal stimuli, while a controller applies haptic signals in real time with latency below 50 milliseconds. Feedback is dynamically modulated according to AI-inferred interaction classifications. The system utilizes real-time data, including video, imaging, force, and biometric inputs, to support intraoperative decision-making, trajectory refinement, and surgeon performance assessment.

Abstract: A urinary catheter system includes one or more sensors positioned in an interior of a catheter tube and positioned to be in contact with patient's urine An artificial intelligence system has an AI system with an AI engine. A plurality of machine learning algorithms are used with a machine learning model. The machine learning model processes the sensor data using constructive learning to train the machine learning model to distinguish between clean and noisy data of the sensor data, and uses labeled data with a known noise level to classify the sensor data as either clean or noisy, allowing for the removal of one or more noisy data points from a sensor data dataset. The AI system splits the sensor data into a training set and a testing set with the training used to train and the testing set for analysis of the sensor data. Cryptography algorithms that at least a portion of one or more of the sensor data.

Abstract: A robotic surgical system, a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system, one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

Abstract: A robotic surgical system includes a surgeon consol coupled to a patient console and coupled to one or more surgical instruments. The surgeon consol is used by a surgeon to perform a surgical procedure. A surgeon computer is coupled to or at the surgeon console. The surgeon consol is coupled to the one or more surgical instruments (manipulators). A surgical robot is coupled to a robotic surgery control system and a feedback loop. The feedback loop monitors and collects data from one or more sensors used to provide feedback to the robotic surgical system. An AI system has an AI architecture that uses input data for producing an AI model. A surgical robot is coupled to a robotic surgical control system that is coupled to or includes: the feedback loop, and the artificial intelligence AI system.

Abstract: A robotic surgical system is disclosed that integrates a simulation module, artificial intelligence (AI), and a multimodal sensor array to enhance intraoperative decision-making and execution. The system generates a dynamic, patient-specific digital twin representing anatomical, physiological, and thermal data, continuously updated during surgery. Real-time sensor inputs, including force feedback, imaging, and biomarkers, are analyzed by an AI module to characterize tissue conditions, predict responses, and guide tool trajectories. The system adapts tool movement based on AI confidence scoring, margin proximity, and predictive modeling. A visualization interface overlays augmented insights onto live surgical views. The platform enables surgeon-specific and population-based learning, real-time feedback, and intraoperative handoff based on biometric or performance indicators. Embedded modules provide simulation, planning, deviation tracking, and control adjustment.

Abstract: A robotic surgical system is configured to provide dynamic legal and ethical compliance. A control processor executes surgical procedures based on artificial intelligence (AI)-generated guidance. A compliance module is associated with the control processor and configured to: receive jurisdiction-specific surgical requirements and patient-specific consent data room external or internal sources; monitor surgical actions and AI-generated decisions in real time; analyze decision pathways using rule-based logic, predictive models, or both to detect potential legal or ethical conflicts; and initiate at least one of: issuing a conflict alert, inhibiting automated execution of the decision, or prompting a confirmation action by a human operator. A policy ingestion component interprets compliance directives expressed in natural or semi-structured language, including regulatory standards, institutional protocols, and cultural norms.

Abstract: A robotic surgical system is disclosed that integrates real-time surgeon behavior monitoring, biometric feedback, and adaptive AI-based decision support to enhance intraoperative performance and post-procedural analysis. The system includes a user behavior monitoring module to track surgeon interaction patterns, a biometric data aggregator collecting inputs such as heart rate variability, electrodermal activity, and eye tracking, and a feedback modulation engine operatively coupled to an AI inference engine. A phase classifier evaluates surgical criticality based on tool telemetry and contextual signals, enabling the system to dynamically escalate, suppress, or defer feedback. Surgeon-specific profiles guide system behavior across procedures, while a summary dashboard provides insights into feedback efficacy and surgeon responsiveness.

Abstract: A robotic surgical system incorporates artificial intelligence to enhance intraoperative performance and surgical decision-making. The system includes a surgeon console, one or more robotic arms, and a control module with an AI-driven model generalization engine. The AI engine leverages cross-procedure transfer learning, enabling it to apply models trained on one type of surgery to others exhibiting latent procedural similarity. Intraoperative data including endoscopic video, robotic arm kinematics, force and haptic feedback, biometric signals, and audio commands is analyzed to support real-time guidance, anomaly detection, and adaptive control. The system comprises modules for surgical planning, predictive analytics, autonomous task execution, and surgeon fatigue monitoring. Feedback from multimodal sensors informs dynamic trajectory adjustment and surgical decision support. Continuous learning from both historical and live surgical data refines the AI model over time.

Abstract: A robotic surgical system includes a surgeon console coupled to a patient console. The surgeon console is coupled to a surgical robot and one or more robotic surgical instruments. A robotic surgery control system is coupled to a feedback loop. The control system includes an artificial intelligence (AI) architecture configured to process intraoperative input data, and generate an AI model for positioning the surgical instruments during a surgical procedure. A deviation detection module is configured to identify intraoperative discrepancies between a predefined surgical action sequence and an actual robotic execution using deviation thresholds based on one or more of: trajectory variance, motion drift, or multimodal image inconsistency. The deviation detection module employs a trained machine learning model to enhance sensitivity to context-specific deviations without triggering autonomous inference chains.

Abstract: A robotic surgical system includes a robotic instrument coupled to a controller and configured to interact with biological tissue. A physiologic sensing subsystem has one or more sensors configured to detect real-time physiological parameters. The sensors include at least one of: tissue oxygenation sensors, perfusion sensors, bioimpedance sensors, or neural conductivity sensors.

Abstract: A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (“AI”) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures.

Abstract: A robotic surgical system integrates artificial intelligence (AI) to enable dynamic inference arbitration and risk-driven autonomy. The system includes a surgeon console, robotic arms, and a control system with memory and processors configured to execute real-time surgical workflows. AI modules analyze intraoperative data, such as imaging, sensor input, and instrument telemetry, and compute context alignment scores to guide module selection, forecasting, and fallback execution. Confidence metrics are monitored, with thresholds triggering surgeon alerts, handoff, or autonomous continuation. The system supports intraoperative adaptation, surgeon fatigue detection, and real-time annotation of AI outputs for traceability. It enables improved tissue recognition, predictive planning, and context-aware adjustments through training on historical surgical data. AI-assisted decision support, deviation handling, and performance monitoring enhance safety and personalization across diverse procedures.

Abstract: A robotic surgical system includes one or more robotic actuators configured to interact with biological tissue during a surgical procedure. A plurality of sensors include at least one of fiber Bragg grating sensors, piezoelectric strain sensors, or magnetostrictive sensors to capture real-time mechanical, elasticity, or deformation data from biological tissues. deep learning engine trained on a dataset comprising tissue mechanical responses across multiple tissue types, pathological states, and patient demographics. Pre-contact predictive adjustment profiles are generated for anticipated tissue interactions using preoperative imaging data registered to intraoperative coordinates. Intraoperative deviations are detected from predicted mechanical behavior and autonomously recalibrate actuator forces. Upcoming surgical maneuvers are anticipated based on prior task sequences and adjust actuator stiffness or damping properties in preparation for anticipated contact.

Abstract: A surgical robot is coupled to the surgeon console. The surgical robot performs a robotic surgical procedure. The surgical robot includes one or more robotic surgical arms. A control system is coupled to the one or more robotic surgical arms. An artificial intelligence (“AI”) system includes a plurality of machine learning algorithms. The robotic surgical arms are at least partially controlled by the AI system and the control device to process intraoperative data including images captured by cameras and sensor inputs. The machine learning algorithms analyze the intraoperative data in real time, comparing it with stored images and procedural information in image recognition and procedure databases. The one or more machine algorithms enable at least partial identification of anatomical structures.

Abstract: A robotic surgical system network includes a plurality of robotic surgical systems. Each system includes robotic arms, sensors, a surgeon console, and a control system with an integrated AI module. A network interface is associated with robotic surgical system and provides secure data communication. A central or distributed data repository securely stores surgical data aggregated from the robotic surgical systems. The surgical data includes at least one of procedural data, sensor readings, imaging data, AI decision logs, surgical outcomes, or user interaction data. A training module utilizes aggregated surgical data to train or update AI models for the robotic surgical systems using unsupervised learning, transfer learning, or federated learning techniques. A cybersecurity module implements security measures for data transmission and system access, the measures comprising at least one of encryption, multi-factor authentication, or real-time threat detection.

Abstract: A robotic surgical system includes a robotic manipulator configured to perform surgical procedures under direct surgeon control. A surgical camera system captures real-time intraoperative video. An external imaging interface receives multimodal imaging data, including preoperative and intraoperative data from at least one of magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, and fluoroscopy.

Abstract: A robotic surgical system includes a surgeon consol coupled to a patient consol, and the patient consol coupled to surgical instruments. A surgeon computer is coupled to or at the surgeon consol that is coupled to to one or more surgical instruments. A robotic surgery control system includes an artificial intelligence (AI) system with one or more deep learning algorithms. A feedback loop monitors and collects data from the one or more sensors. One or more cameras provide feedback to the robotic surgical system, and are configured to provide images of an anatomical object in at least a two dimensional (2D) arrangements of pixels/Deep learning algorithms of the AI system distinguish different anatomical objects from the images.

Abstract: A robotic surgical system. a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system. one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

Abstract: A robotic surgical system. a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system. one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.