ABSTRACT
BACKGROUND: Hand-sewn anastomosis is a crucial part of aortic reconstruction surgery and significantly affects its outcome. The present study presents a novel, bidirectional surgical needle aimed to improve aortic anastomosis in terms of speed and ease of use. Our objective was to assess the efficacy of the new design in comparison with the conventional needle. METHODS: A series of simulations were conducted with COMSOL software in order to perform a fatigue comparative analysis between the new and the conventional needle design. Ease of penetration into a piece of polydimethylsiloxane was evaluated. Lastly, the prototype was tested under in-vitro conditions in comparison with the conventional needle. RESULTS: Based on fatigue analysis, the new needle design improves durability, provided the two tips are equally used. The polytetrafluoroethylene coating improves penetration into the tissue by 7% to 17%, while electropolishing improves penetration up to 19%. When using the novel needle design, the average anastomotic task completion time was significantly reduced by 22% and the overall distance of hand movements was significantly reduced by 20%. CONCLUSIONS: The proposed design exhibited a shorter anastomotic time and seems promising in relation to ease of use and simplicity of the anastomotic technique it introduces.
ABSTRACT
The sleep apnea syndrome is a chronic condition that affects the quality of life and increases the risk of severe health conditions such as cardiovascular diseases. However, the prevalence of the syndrome in the general population is considered to be heavily underestimated due to the restricted number of people seeking diagnosis, with the leading cause for this being the inconvenience of the current reference standard for apnea diagnosis: Polysomnography. To enhance patients' awareness of the syndrome, a great endeavour is conducted in the literature. Various home-based apnea detection systems are being developed, profiting from information in a restricted set of polysomnography signals. In particular, breathing sound has been proven highly effective in detecting apneic events during sleep. The development of accurate systems requires multitudinous datasets of audio recordings and polysomnograms. In this work, we provide the first open access dataset, comprising 212 polysomnograms along with synchronized high-quality tracheal and ambient microphone recordings. We envision this dataset to be widely used for the development of home-based apnea detection techniques and frameworks.