Dataset Information

Design and analysis of a fiber-optic sensing system for shape reconstruction of a minimally invasive surgical needle.

ABSTRACT: This paper presents the performance analysis of the system for real-time reconstruction of the shape of the rigid medical needle used for minimally invasive surgeries. The system is based on four optical fibers glued along the needle at 90 degrees from each other to measure distributed strain along the needle from four different sides. The distributed measurement is achieved by the interrogator which detects the light scattered from each section of the fiber connected to it and calculates the strain exposed to the fiber from the spectral shift of that backscattered light. This working principle has a limitation of discriminating only a single fiber because of the overlap of backscattering light from several fibers. In order to use four sensing fibers, the Scattering-Level Multiplexing (SLMux) methodology is applied. SLMux is based on fibers with different scattering levels: standard single-mode fibers (SMF) and MgO-nanoparticles doped fibers with a 35-40 dB higher scattering power. Doped fibers are used as sensing fibers and SMFs are used to spatially separate one sensing fiber from another by selecting appropriate lengths of SMFs. The system with four fibers allows obtaining two pairs of opposite fibers used to reconstruct the needle shape along two perpendicular axes. The performance analysis is conducted by moving the needle tip from 0 to 1 cm by 0.1 cm to four main directions (corresponding to the locations of fibers) and to four intermediate directions (between neighboring fibers). The system accuracy for small bending (0.1-0.5 cm) is 90[Formula: see text] and for large bending (0.6-1 cm) is approximately 92[Formula: see text].

SUBMITTER: Issatayeva A

PROVIDER: S-EPMC8060330 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:During the implementation of new interventions (i.e., surgical devices and technologies) in the operating room, surgical safety might be compromised. Current safety measures are insufficient in detecting safety hazards during this process. The aim of the study was to observe whether surgical teams are capable of measuring surgical safety, especially with regard to the introduction of new interventions. METHODS:A Surgical Safety Questionnaire was developed that had to be filled out directly postoperative by three surgical team members. A potential safety concern was defined as at least one answer between (strongly) disagree and indifferent. The validity of the questionnaire was assessed by comparison with the results from video analysis. Two different observers annotated the presence and effect of surgical flow disturbances during 40 laparoscopic hysterectomies performed between November 2010 and April 2012. RESULTS:The surgeon reported a potential safety concern in 16% (85/520 questions). With respect to the scrub nurse and anesthesiologist, this was both 9% (46/520). With respect to the preparation, functioning, and ease of use of the devices in 37.5-47.5% (15-19/40 procedures) a potential safety concern was reported by one or more team members. During procedures after which a potential safety concern was reported, surgical flow disturbances lasted a higher percentage of the procedure duration [9.3?±?6.2 vs. 2.9?±?3.7% (mean?±?SD), p?<?.001]. After procedures during which a new instrument or device was used, more potential safety concerns were reported (51.2 vs. 23.1%, p?<?.001). CONCLUSIONS:Potential safety concerns were especially reported during procedures in which a relatively high percentage of the duration consisted of surgical flow disturbances and during procedures in which a new instrument or device was used. The Surgical Safety Questionnaire can act as a validated tool to evaluate and maintain surgical safety during minimally invasive procedures, especially during the introduction of a new intervention.

Dataset Information

Design and analysis of a fiber-optic sensing system for shape reconstruction of a minimally invasive surgical needle.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets