Wie weit ist Chirugie 4.0?

Teber, Doğu; Engels, Christina; Maier-Hein, Lena; Ayala, Leonardo; Onogur, Sinan; Seitel, Alexander; März, Keno

doi:10.1007/s00120-020-01272-z

Cited by 7 publications

(2 citation statements)

References 34 publications

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“…In terms of security, they often relied on countermeasures such as security by obscurity , which is considered as insecure today ( Section 1 ), or limiting the invocable functionality via the network interfaces [ 20 ]. However, in particular, robotic medical devices in the OR will need to be competitive in the future regarding their connectivity interface [ 21 ].…”

Section: Background and State Of The Artmentioning

confidence: 99%

Threat Assessment and Risk Analysis (TARA) for Interoperable Medical Devices in the Operating Room Inspired by the Automotive Industry

2023

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Prevailing trends in the automotive and medical device industry, such as life cycle overarching configurability, connectivity, and automation, require an adaption of development processes, especially regarding the security and safety thereof. The changing requirements imply that interfaces are more exposed to the outside world, making them more vulnerable to cyberattacks or data leaks. Consequently, not only do development processes need to be revised but also cybersecurity countermeasures and a focus on safety, as well as privacy, have become vital. While vehicles are especially exposed to cybersecurity and safety risks, the medical devices industry faces similar issues. In the automotive industry, proposals and draft regulations exist for security-related risk assessment processes. The medical device industry, which has less experience in these topics and is more heterogeneous, may benefit from drawing inspiration from these efforts. We examined and compared current standards, processes, and methods in both the automotive and medical industries. Based on the requirements regarding safety and security for risk analysis in the medical device industry, we propose the adoption of methods already established in the automotive industry. Furthermore, we present an example based on an interoperable Operating Room table (OR table).

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Section: Background and State Of The Artmentioning

confidence: 99%

Threat Assessment and Risk Analysis (TARA) for Interoperable Medical Devices in the Operating Room Inspired by the Automotive Industry

2023

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“…However, machine learning-based approaches bear the challenge of data acquisition in OR and healthcare settings, since conditions for proper data collection are not given [10]. Data-based models for the state estimation of sensor data may result in inadequate quality, particularly as sensor noise increases [11].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Anomaly Detection in Time Series by Combining Kalman Filters and Machine Learning Models

Puder,

Zink,

Seidel

et al. 2024

Sensors

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Due to connectivity and automation trends, the medical device industry is experiencing increased demand for safety and security mechanisms. Anomaly detection has proven to be a valuable approach for ensuring safety and security in other industries, such as automotive or IT. Medical devices must operate across a wide range of values due to variations in patient anthropometric data, making anomaly detection based on a simple threshold for signal deviations impractical. For example, surgical robots directly contacting the patient’s tissue require precise sensor data. However, since the deformation of the patient’s body during interaction or movement is highly dependent on body mass, it is impossible to define a single threshold for implausible sensor data that applies to all patients. This also involves statistical methods, such as Z-score, that consider standard deviation. Even pure machine learning algorithms cannot be expected to provide the required accuracy simply due to the lack of available training data. This paper proposes using hybrid filters by combining dynamic system models based on expert knowledge and data-based models for anomaly detection in an operating room scenario. This approach can improve detection performance and explainability while reducing the computing resources needed on embedded devices, enabling a distributed approach to anomaly detection.

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Requirement analysis for an AI-based AR assistance system for surgical tools in the operating room: stakeholder requirements and technical perspectives

Cramer,

Kucharski,

Kreimeier

et al. 2024

Int J CARS

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Purpose We aim to investigate the integration of augmented reality (AR) within the context of increasingly complex surgical procedures and instrument handling toward the transition to smart operating rooms (OR). In contrast to cumbersome paper-based surgical instrument manuals still used in the OR, we wish to provide surgical staff with an AR head-mounted display that provides in-situ visualization and guidance throughout the assembly process of surgical instruments. Our requirement analysis supports the development and provides guidelines for its transfer into surgical practice. Methods A three-phase user-centered design approach was applied with online interviews, an observational study, and a workshop with two focus groups with scrub nurses, circulating nurses, surgeons, manufacturers, clinic IT staff, and members of the sterilization department. The requirement analysis was based on key criteria for usability. The data were analyzed via structured content analysis. Results We identified twelve main problems with the current use of paper manuals. Major issues included sterile users’ inability to directly handle non-sterile manuals, missing details, and excessive text information, potentially delaying procedure performance. Major requirements for AR-driven guidance fall into the categories of design, practicability, control, and integration into the current workflow. Additionally, further recommendations for technical development could be obtained. Conclusion In conclusion, our insights have outlined a comprehensive spectrum of requirements that are essential for the successful implementation of an AI- and AR-driven guidance for assembling surgical instruments. The consistently appreciative evaluation by stakeholders underscores the profound potential of AR and AI technology as valuable assistance and guidance.

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Wie weit ist Chirugie 4.0?

Cited by 7 publications

References 34 publications

Threat Assessment and Risk Analysis (TARA) for Interoperable Medical Devices in the Operating Room Inspired by the Automotive Industry

Threat Assessment and Risk Analysis (TARA) for Interoperable Medical Devices in the Operating Room Inspired by the Automotive Industry

Hybrid Anomaly Detection in Time Series by Combining Kalman Filters and Machine Learning Models

Requirement analysis for an AI-based AR assistance system for surgical tools in the operating room: stakeholder requirements and technical perspectives

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