Abstract: A radiofrequency (RF) generator for use in a medical system is disclosed. The RF generator includes and RF energy source and a controller. The RF energy source includes an active connector and a return connector. The active connector is coupled to an active electrode of an RF puncture device and the return connector is coupled to a return electrode. The active electrode and return electrode are coupled to a body. The controller is coupled to the RF energy source. The controller applies an RF puncture signal based on a feedforward control setting, asserts an electrical power control of the puncture signal based on thermal energy to the tissue applied with the RF puncture signal, and monitors the puncture signal for desiccation and fulguration of the tissue based on thermal energy applied to the tissue with the RF puncture signal.

Abstract: Methods and systems of training a machine learning model include identifying an object or person related to an action in a first video. The object or person is copied from the first video to a second video to generate a third video. A machine learning model is trained using the first video and the third video.

Abstract: Systems and methods are provided for encoding and decoding images using differentiable JPEG compression, including converting images from RGB color space to YCbCr color space to obtain a luminance and chrominance channels, and applying chroma subsampling to the chrominance channels to reduce resolution. The YCbCr image is divided into pixel blocks and a DCT is performed on the pixel blocks to obtain DCT coefficients. DCT coefficients are quantized using a scaled quantization table to reduce precision, and quantized DCT coefficients are encoded using lossless entropy coding, forming a compressed JPEG file decoded by reversing the lossless entropy coding to obtain quantized DCT coefficients, which are dequantized using the scaled quantization table to restore the precision. The dequantized DCT coefficients are converted back to a spatial domain using an IDCT, the chrominance channels are upsampled to original resolution, and the YCbCr image is converted back to the RGB color space.

Abstract: An electrosurgical generator is disclosed. The electrosurgical generator includes device terminals including an active terminal and a return terminal and a controller. The controller generates a radiofrequency (RF) energy signal for delivery to the active terminal, measures an electrical impedance between device terminals and a phase angle of the RF energy signal while the RF energy signal is applied to the active terminal, determines at least one of a sustained change in electrical impedance, a change in electrical impedance via an impedance slope, and a change in phase angle change, and generates an indication of tissue crossing based on the determined change of the electrical impedance or the phase angle.

Abstract: A radiofrequency (RF) generator for use in a tissue puncture system for puncturing a tissue in a body is disclosed. The RF generator includes an RF energy source to couple to an active electrode of an RF puncture device and to couple to a return electrode and a controller coupled to the RF energy source. The controller causes the RF energy source to generate each of a puncture signal and a test signal, the test signal having a lower power than the puncture signal, measures an impedance of the test signal, determine a state of the active electrode based on the impedance measurement, and displays the state on a display device.

Abstract: Systems and methods for self-supervised feature disentanglement for calibration-free multi-camera multi-object tracking. View-specific features and view-agnostic features of a tracked entity can be identified from different camera views by encoding masked detection features of the tracked entity. The masked detection features can be reconstructed into single-view feature representations from the view-specific features. Cross-view feature representations can be generated from the view-agnostic features that capture shared characteristics from the different camera views. The single-view feature representations and the cross-view feature representations can be combined into multi-entity multi-camera tracks that capture the characteristics of the tracked entity from the different camera views for downstream tasks.

Abstract: An electrosurgical unit for use with a crossing member is disclosed. The electrosurgical unit includes a controller and device terminals. The device terminals include an active terminal and a measurement terminal. The device terminals couple to the crossing member. The controller generates a radiofrequency (RF) energy signal that is delivered to the active terminal. The RF energy signal is configured to cross tissue. The controller also determines whether the crossing member has crossed the tissue via a determined change in a response to a measurement signal received at the measurement terminal and generates an indication of tissue crossing based on the determined change in the response to the measurement signal.

Abstract: Systems and methods are provided for optimizing video compression for remote vehicle control, including capturing, capturing video and sensor data from a vehicle using a plurality of sensors and high-resolution cameras, analyzing the captured video to identify critical regions within frames of the video using an attention-based module. Current network bandwidth is assessed and future bandwidth availability is predicted. Video compression parameters are predicted based on an analysis of the video and an assessment of the current network bandwidth using a control network, and the video is compressed based on the predicted parameters with an adaptive video compression module. The compressed video and sensor data is transmitted to a remote-control center, and received video and sensor data is decoded at the remote-control center. The vehicle is autonomously or remotely controlled from the remote-control center based on the decoded video and sensor data.

Abstract: Systems and methods are provided for optimizing video compression for remote vehicle control, including capturing, capturing video and sensor data from a vehicle using a plurality of sensors and high-resolution cameras, analyzing the captured video to identify critical regions within frames of the video using an attention-based module. Current network bandwidth is assessed and future bandwidth availability is predicted. Video compression parameters are predicted based on an analysis of the video and an assessment of the current network bandwidth using a control network, and the video is compressed based on the predicted parameters with an adaptive video compression module. The compressed video and sensor data is transmitted to a remote-control center, and received video and sensor data is decoded at the remote-control center. The vehicle is autonomously or remotely controlled from the remote-control center based on the decoded video and sensor data.

Abstract: Systems and methods are provided for optimizing video compression for remote vehicle control, including capturing, capturing video and sensor data from a vehicle using a plurality of sensors and high-resolution cameras, analyzing the captured video to identify critical regions within frames of the video using an attention-based module. Current network bandwidth is assessed and future bandwidth availability is predicted. Video compression parameters are predicted based on an analysis of the video and an assessment of the current network bandwidth using a control network, and the video is compressed based on the predicted parameters with an adaptive video compression module. The compressed video and sensor data is transmitted to a remote-control center, and received video and sensor data is decoded at the remote-control center. The vehicle is autonomously or remotely controlled from the remote-control center based on the decoded video and sensor data.

Abstract: Systems and methods are provided for optimizing video compression for remote vehicle control, including capturing, capturing video and sensor data from a vehicle using a plurality of sensors and high-resolution cameras, analyzing the captured video to identify critical regions within frames of the video using an attention-based module. Current network bandwidth is assessed and future bandwidth availability is predicted. Video compression parameters are predicted based on an analysis of the video and an assessment of the current network bandwidth using a control network, and the video is compressed based on the predicted parameters with an adaptive video compression module. The compressed video and sensor data is transmitted to a remote-control center, and received video and sensor data is decoded at the remote-control center. The vehicle is autonomously or remotely controlled from the remote-control center based on the decoded video and sensor data.

Abstract: Methods and systems for training a model include performing spatial augmentation on an unlabeled input video to generate spatially augmented video. Temporal augmentation is performed on the input video to generate temporally augmented video. Predictions are generated, using a model that was pre-trained on a labeled dataset, for the unlabeled input video, the spatially augmented video, and the temporally augmented video. Parameters of the model are adapted using the predictions while enforcing temporal consistency, temporal consistency, and historical consistency. The model may be used for action recognition in a healthcare context, with recognition results being used for determining whether patients are performing a rehabilitation exercise correctly.

Abstract: A system for performing a medical procedure using a piece of capital equipment includes a peripheral device adapter. The adapter includes a housing having a first end configured to connect to the piece of capital equipment and a second end configured to connect to a single use device. The adapter includes a connector configured to removably connect to a peripheral device. The adapter includes a peripheral device adapter memory device for storing instructions, wherein the instructions are configured to package data or information associated with the peripheral device into a format representative of a single use device to allow for communication with the piece of capital equipment. The system includes one or more processors.

Abstract: Methods and systems for temporal action localization include processing a video stream to identify an action and a start time and a stop time for the action using a neural network model that separately processes information of appearance and motion modalities from the video stream using transformer branches that include a self-attention and a cross-attention between the appearance and motion modalities. An action is performed responsive to the identified action.

Abstract: Systems and methods are provided for optimizing video compression for remote vehicle control, including capturing, capturing video and sensor data from a vehicle using a plurality of sensors and high-resolution cameras, analyzing the captured video to identify critical regions within frames of the video using an attention-based module. Current network bandwidth is assessed and future bandwidth availability is predicted. Video compression parameters are predicted based on an analysis of the video and an assessment of the current network bandwidth using a control network, and the video is compressed based on the predicted parameters with an adaptive video compression module. The compressed video and sensor data is transmitted to a remote-control center, and received video and sensor data is decoded at the remote-control center. The vehicle is autonomously or remotely controlled from the remote-control center based on the decoded video and sensor data.

Abstract: An electrosurgical generator is disclosed. The electrosurgical generator includes device terminals including an active terminal and a return terminal and a controller. The controller generates a radiofrequency (RF) energy signal for delivery to the active terminal, measures an electrical impedance between device terminals and a phase angle of the RF energy signal while the RF energy signal is applied to the active terminal, determines at least one of a sustained change in electrical impedance, a change in electrical impedance via an impedance slope, and a change in phase angle change, and generates an indication of tissue crossing based on the determined change of the electrical impedance or the phase angle.

Abstract: An electrosurgical generator and system include device terminals including an active terminal and a return terminal and a controller. The controller adjusts an amplitude of a radiofrequency (RF) energy signal provided to the active terminal. The adjusted amplitude is based on a setpoint and an input in a closed feedback loop. The input is based on a rolling sum of addends, and each addend is based on a sampled output of the RF energy signal associated with a frequency bin. The rolling sum of addends is determined over a number of frequency bins associated with a target frequency.

Abstract: Systems and methods for action detection are provided. The systems and methods include generating action prediction labels and bounding boxes for objects detected in video frames and comparing the action prediction labels and the bounding boxes with corresponding ground labels, determining a classification loss and a localization loss, and determining a reversibility action loss by comparing the action prediction labels with known actions indices and logical constraints and a speed action loss by comparing the action prediction labels with known actions indices and logical constraints. The systems and methods further include combining the classification loss, localization loss, reversibility action loss, and speed action loss to evaluate a total loss and selecting the action prediction with a lowest total loss as an action assertion and performing reactionary actions in a connected device in response to the action assertion.

Abstract: Methods and systems for filling data include extracting text from a structured document and document instructions to identify a field within the structured document. Text is extracted from a contextual document to identify information relating to the field. Information is selected from the contextual document based on a comparison between the extracted text from the contextual document and the extracted text from the structured document and document instructions. The field within the structured document is filled using the selected information to create a filled document.

Abstract: Systems and methods for optimizing multi-camera multi-entity artificial intelligence tracking systems. Visual and location information of entities from video feeds received from multiple cameras can be obtained by employing an entity detection model and re-identification model. Likelihood scores that entity detections belong to an entity track can be predicted from the visual and location information. The entity detections predicted into entity tracks can be processed by employing combinatorial optimization of the likelihood scores by identifying assumptions from the likelihood scores, entity detections, and the entity tracks, filtering the assumptions with unsatisfiable problems to obtain a filtered assumptions set, and optimizing an answer set by utilizing the filtered assumptions set and the likelihood scores to maximize an overall score and obtain optimized entity tracks. Multiple entities can be monitored by utilizing the optimized entity tracks.