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CMOS Perceptron for Vesicle Fusion Classification


[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ 2 ] Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee | [ SzD ] doctoral school student

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication


Published in


Journal year: 2022 | Journal volume: vol. 11 | Journal number: iss. 6

Article type

scientific article

Publication language


  • vesicle fusion
  • exocytosis
  • edge computing
  • neural networks
  • CMOS accelerators
  • weak-inversion mode

EN Edge computing (processing data close to its source) is one of the fastest developing areas of modern electronics and hardware information technology. This paper presents the implementation process of an analog CMOS preprocessor for use in a distributed environment for processing medical data close to the source. The task of the circuit is to analyze signals of vesicle fusion, which is the basis of life processes in multicellular organisms. The functionality of the preprocessor is based on a classifier of full and partial fusions. The preprocessor is dedicated to operate in amperometric systems, and the analyzed signals are data from carbon nanotube electrodes. The accuracy of the classifier is at the level of 93.67%. The implementation was performed in the 65 nm CMOS technology with a 0.3 V power supply. The circuit operates in the weak-inversion mode and is dedicated to be powered by thermal cells of the human energy harvesting class. The maximum power consumption of the circuit equals 416 nW, which makes it possible to use it as an implantable chip. The results can be used, among others, in the diagnosis of precancerous conditions.

Date of online publication


Pages (from - to)

843-1 - 843-15





Article Number: 843

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal


Impact Factor

2.690 [List 2021]

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