ArticleJournal of intelligent & robotic systems2022
Research on Robotic Humanoid Venipuncture Method Based on Biomechanical Model.
Article in Journal of intelligent & robotic systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Artificial intelligence in the pre-analytical phase: State-of-the art and future perspectives.Journal of medical biochemistry · 2024Article
- Decision Method of Optimal Needle Insertion Angle for Dorsal Hand Intravenous Robot.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automatic venipuncture robots are expected to replace manual venipuncture methods owing to their high control precision, steady operation, and measurable perception. However, the lack of perception of the venipuncture status in the human body leads to an increased risk and failure rate, which further restricts the development of such robots. To address this, we propose a humanoid venipuncture method guided by a biomechanical model to imitate human sensations and feedback. This method intends to perceive the venipuncture status and improve the performance of the venipuncture robot. First, this study establishes a biomechanical venipuncture model, which thoroughly considers the elastic deformation, cutting, and friction of tissues and can be applied to different venipuncture conditions. Then, venipuncture simulations and in vitro phantom experiments are performed under various settings to analyze and validate the model. Finally, to evaluate the robotic humanoid venipuncture method, we apply the method to a self-developed six-degree-of-freedom venipuncture robot via rabbit ear veins with a success rate of approximately 90%. This work demonstrates that the humanoid venipuncture method based on the biomechanical model is practical and rapid in processing simple information in venipuncture robots.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.