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Ultra wideband real-time locating system for tracking people and devices in the operating room
(2022)
Position tracking within the OR could be one possible input for intraoperative situation recognition. Our approach demonstrates a Real-time Locating System (RTLS) using the Ultra Wideband (UWB) technology to determine the position of people or objects. The UWB RTLS was integrated into the research OR at Reutlingen University and the system’s settings were optimized regarding the four factors accuracy, susceptibility to interference, range, and latency. Therefore, different parameters were adapted and the effects on the factors were compared. Goodtracking quality could be achieved under optimal settings. These results indicate that a UWB RTLS is well suited to determine the position of people and devices in our setting. The feasibility of the system needsto be evaluated under real OR conditions.
With the progress of technology in modern hospitals, an intelligent perioperative situation recognition will gain more relevance due to its potential to substantially improve surgical workflows by providing situation knowledge in real-time. Such knowledge can be extracted from image data by machine learning techniques but poses a privacy threat to the staff’s and patients’ personal data. De-identification is a possible solution for removing visual sensitive information. In this work, we developed a YOLO v3 based prototype to detect sensitive areas in the image in real-time. These are then deidentified using common image obfuscation techniques. Our approach shows that it is principle suitable for de-identifying sensitive data in OR images and contributes to a privacyrespectful way of processing in the context of situation recognition in the OR.
What might the attendee be able to do after being in your session?
Our work shows how to connect intra-operative devices via IEEE 11073 Service-oriented Device Connectivity (SDC).
Description of the Problem or Gap
Standardized device communication is essential for interoperability, availability of device data, and therefore for the intelligent operating room (OR) and arising solutions. The SDC standard was developed to make information from medical devices available in a uniform manner and enable interoperability. Existing devices are rarely SDC-capable and need interfaces to be interoperable via SDC.
Methods: What did you do to address the problem or gap?
We conceived an SDC-based architecture consisting of a service provider and service consumer. In our concept, the service provider is connected to the medical device and capable to translate the proprietary protocol of the device into SDC and vice versa. The service consumer is used to request or send information via the SDC protocol to the service provider and can function as a uniform bidirectional interface (e.g. for displaying or controlling). This concept was exemplarily demonstrated with the patient monitor MX800 of Philips to retrieve the device data (e.g. vital parameters) via SDC and partly for the operating light marLED X of KLS Martin Group.
Results: What was the outcome(s) of what you did to address the problem or gap?
The patient monitor MX800 was connected to a Raspberry Pi (RPi) via LAN, on which the service provider is running. The python script on the RPi establishes a connection to the monitor and translates incoming and outgoing messages from the proprietary protocol to SDC and vice versa to/from the service consumer. The service consumer is running on a laptop and acts as a simulation for different kinds of systems that want to get vital parameters or other information from the patient monitor. The operating light marLED X was connected to an RPi via USB-to-RS232. A python script on the RPi establishes a connection to the light and makes it possible via proprietary commands to get information of the light (e.g. status) and to control it (e.g. toggle the light, increment the intensity). A translation to SDC is not integrated yet.
Discussion of Results
Our practical implementation shows that medical devices can be accessed via external connections to get device data and control the device via commands. The example SDC implementation of the patient monitor MX800 makes it possible to request its data via the standardized communication protocol SDC. This is also possible for the operating light marLED X if its proprietary protocol is analyzed to be translatable to/from SDC. This would allow to control the device from an external system, or automatically depending on the status of the ongoing procedure. The advantage is, that existing intra-operative devices can be extended by a service provider which is capable of translating the proprietary protocol of the device in SDC and vice versa. This enables interoperability and an intelligent OR that, for example, is aware of all devices, their status, and data and can use this information to optimally support the surgeons and their team (e.g. provision of information, automated documentation). This interoperability allows that future innovations merely need to understand the SDC protocol instead of all vendor-dependent communication protocols.
Conclusion
Standardized device communication is essential to reach interoperability, and therefore intelligent ORs. Our contribution addresses the possibility of subsequently making medical devices SDC-capable. This may eliminate the need of understanding all the different proprietary protocols when developing new innovative solutions for the OR.
This project aims to evaluate existing big data infrastructures for their applicability in the operating room to support medical staff with context-sensitive systems. Requirements for the system design were generated. The project compares different data mining technologies, interfaces, and software system infrastructures with a focus on their usefulness in the peri-operative setting. The lambda architecture was chosen for the proposed system design, which will provide data for both postoperative analysis and real-time support during surgery.
Introduction: Even if there is a standard procedure of CI surgery, especially in pediatric surgery surgical steps often differ individually due to anatomical variations, malformations or unforseen events. This is why every surgical report should be created individually, which takes time and relies on the correct memory of the surgeon. A standardized recording of intraoperative data and subsequent storage as well as text processing would therefore be desirable and provides the basis for subsequent data processing, e.g. in the context of research or quality assurance.
Method: In cooperation with Reutlingen University, we conducted a workflow analysis of the prototype of a semi-automatic checklist tool. Based on automatically generated checklists generated from BPMN models a prototype user interface was developed for an android tablet. Functions such as uploading photos and files, manual user entries, the interception of foreseeable deviations from the normal course of operations and the automatic creation of OP documentation could be implemented. The system was tested in a remote usability test on a petrous bone model.
Result: The user interface allows a simple intuitive handling, which can be well implemented in the intraoperative setting. Clinical data as well as surgical steps could be individually recorded and saved via DICOM. An automatic surgery report could be created and saved.
Summary: The use of a dynamic checklist tool facilitates the capture, storage and processing of surgical data. Further applications in clinical practice are pending.
Context-aware systems to support actors in the operating room depending on the status of the intervention require knowledge about the current situation in the intra-operative area. In literature, solutions to achieve situation awareness already exist for specific use cases, but applicability and transferability to other conditions are less addressed. It is assumed that a unified solution that can be adapted to different processes and sensors would allow for greater flexibility, applicability, and thus transferability to different applications. To enable a flexible and intervention-independent system, this work proposes a concept for an adaptable situation recognition system. The system consists of four layers with several modular components for different functionalities. The feasibility is demonstrated via prototypical implementation and functional evaluation of a first basic framework prototype. Further development goal is the stepwise extension of the prototype.
Painting galleries typically provide a wealth of data composed of several data types. Those multivariate data are too complex for laymen like museum visitors to first, get an overview about all paintings and to look for specific categories. Finally, the goal is to guide the visitor to a specific painting that he wishes to have a more closer look on. In this paper we describe an interactive visualization tool that first provides such an overview and lets people experiment with the more than 41,000 paintings collected in the web gallery of art. To generate such an interactive tool, our technique is composed of different steps like data handling, algorithmic transformations, visualizations, interactions, and the human user working with the tool with the goal to detect insights in the provided data. We illustrate the usefulness of the visualization tool by applying it to such characteristic data and show how one can get from an overview about all paintings to specific paintings.
Purpose: Medical processes can be modeled using different methods and notations.Currently used modeling systems like Business Process Model and Notation (BPMN) are not capable of describing the highly flexible and variable medical processes in sufficient detail.
Methods: We combined two modeling systems, Business Process Management (BPM) and Adaptive Case Management (ACM), to be able to model non-deterministic medical processes. We used the new Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN).
Results: First, we explain how CMMN, DMN and BPMN could be used to model non-deterministic medical processes. We applied this methodology to model 79 cataract operations provided by University Hospital Leipzig, Germany, and four cataract operations provided by University Eye Hospital Tuebingen, Germany. Our model consists of 85 tasks and about 20 decisions in BPMN. We were able to expand the system with more complex situations that might appear during an intervention.
Conclusion: An effective modeling of the cataract intervention is possible using the combination of BPM and ACM. The combination gives the possibility to depict complex processes with complex decisions. This combination allows a significant advantage for modeling perioperative processes.
Recent advances in artificial intelligence have enabled promising applications in neurosurgery that can enhance patient outcomes and minimize risks. This paper presents a novel system that utilizes AI to aid neurosurgeons in precisely identifying and localizing brain tumors. The system was trained on a dataset of brain MRI scans and utilized deep learning algorithms for segmentation and classification. Evaluation of the system on a separate set of brain MRI scans demonstrated an average Dice similarity coefficient of 0.87. The system was also evaluated through a user experience test involving the Department of Neurosurgery at the University Hospital Ulm, with results showing significant improvements in accuracy, efficiency, and reduced cognitive load and stress levels. Additionally, the system has demonstrated adaptability to various surgical scenarios and provides personalized guidance to users. These findings indicate the potential for AI to enhance the quality of neurosurgical interventions and improve patient outcomes. Future work will explore integrating this system with robotic surgical tools for minimally invasive surgeries.
Motivation
In order to enable context-aware behavior of surgical assistance systems, the acquisition of various information about the current intraoperative situation is crucial. To achieve this, the complex task of situation recognition can be delegated to a specialized system. Consequently, a standardized interface is required for the seamless transfer of the recognized contextual information to the assistance systems, enabling them to adapt accordingly.
Methods
Our group analyzed four medical interface standards to determine their suitability for exchanging intraoperative contextual information. The assessment was based on a harmonized data and service model derived from the requirements of expected context-aware use cases. The Digital Imaging and Communications in Medicine (DICOM) and IEEE 11073 for Service-oriented Device Connectivity (SDC) were identified as the most appropriate standards.
Results
We specified how DICOM Unified Procedure Steps (UPS), can be used to effectively communicate contextual information. We proposed the inclusion of attributes to formalize different granularity levels of the surgical workflow.
Conclusions
DICOM UPS SOP classes can be used for the exchange of intraoperative contextual information between a situation recognition system and surgical assistance systems. This can pave the way for vendor-independent context awareness in the OR, leading to targeted assistance of the surgical team and an improvement of the surgical workflow.