Research Incubator: SIBIONS Bioinstrumentation

Organization profile

Organization profile

Topics or areas of work or research and their relevance and harmony with the research group are mainly focused on using mechanical design, electronic design and programming for:

  • Mechanical design of biomedical instruments.
  • Electronic design of biomedical instruments.
  • Acquisition of biomedical information sources.
  • Processing of biomedical information sources.

This mission is to strengthen the design and creation of biomedical systems (hardware and software) to provide alternatives for the acquisition, transmission and processing of biomedical information sources.

Research Lines: Bioinstrumentation, TinyML, Edge AI.

Objectives:

  1. To promote the mechanical design of elements for the acquisition of biomedical signals and images for the solution of health problems.
  2. To establish solutions in the area of electronic design that can help the transmission and processing of biomedical information sources.
  3. To generate new alternatives for obtaining information based on systems developed and applied according to need.

Organization profile

Topics or areas of work or research and their relevance and harmony with the research group are mainly focused on using mechanical design, electronic design and programming for:

  • Mechanical design of biomedical instruments.
  • Electronic design of biomedical instruments.
  • Acquisition of biomedical information sources.
  • Processing of biomedical information sources.

This mission is to strengthen the design and creation of biomedical systems (hardware and software) to provide alternatives for the acquisition, transmission and processing of biomedical information sources.

Research Lines: Bioinstrumentation, TinyML, Edge AI.

Objectives:

  1. To promote the mechanical design of elements for the acquisition of biomedical signals and images for the solution of health problems.
  2. To establish solutions in the area of electronic design that can help the transmission and processing of biomedical information sources.
  3. To generate new alternatives for obtaining information based on systems developed and applied according to need.

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Collaborations and top research areas from the last five years

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  • Machine learning approach for fatigue estimation in sit-to-stand exercise

    Aguirre, A., Pinto, M. J., Cifuentes, C. A., Perdomo, O., Díaz, C. A. R. & Múnera, M., Jul 23 2021, In: Sensors. 21, 15, 5006.

    Research output: Contribution to journalResearch Articlepeer-review

    Open Access
    19 Scopus citations
  • A Conditional Generative Adversarial Network-Based Method for Eye Fundus Image Quality Enhancement

    Pérez, A. D., Perdomo, O., Rios, H., Rodríguez, F. & González, F. A., Nov 20 2020, Ophthalmic Medical Image Analysis - 7th International Workshop, OMIA 2020, Held in Conjunction with MICCAI 2020, Proceedings. Fu, H., Garvin, M. K., MacGillivray, T., Xu, Y. & Zheng, Y. (eds.). Springer Science and Business Media Deutschland GmbH, Vol. 12069. p. 185-194 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12069 LNCS).

    Research output: Chapter in Book/ReportChapter (peer-reviewed)peer-review

    11 Scopus citations
  • A lightweight deep learning model for mobile eye fundus image quality assessment

    Pérez, A. D., Perdomo Charry, O. J. & González, F. A., Jan 3 2020, 15th International Symposium on Medical Information Processing and Analysis. Romero, E., Lepore, N. & Brieva, J. (eds.). SPIE, 113300K. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 11330).

    Research output: Chapter in Book/ReportChapter (peer-reviewed)peer-review

    12 Scopus citations