Anais do Workshop de Micro-ondas (ISSN 2675-4460)
Published October 29, 2023 | Version v1
Conference paper Open

SOUND DETECTION IN THE ICU WITH TINYML: PROJECT WITH ARDUINO NANO 33 BLE SENSE AND EDGE IMPULSE

Creators

  • 1. Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
  • 2. James Clerk Maxwell Laboratory for Microwaves and Applied Electromagnetism (LABMAX)

Description

This article presents an early warning system for critical events in intensive care units (ICUs). The system uses sound detection techniques with TinyML to quickly identify potentially dangerous events such as suction noises, falls, and cardiac arrests. 

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Additional details

References

  • SCHMIDT, S., DIEKS, JK., QUINTEL, M. et al. Development and evaluation of the focused assessment of sonographic pathologies in the intensive care unit (FASP-ICU) protocol. Crit Care 25, 405
  • SCHMIDT, N., GERBER, SM, ZANTE, B. et al. Effects of intensive care unit ambient sounds on healthcare professionals: results of an online survey and noise exposure in an experimental setting. ICMx 8, 34
  • KALLIMANI, R., PAI, K., RAGHUWANSHI, P. et al. TinyML: Tools, applications, challenges, and future research directions. Multimed Tools Appl, 2023.
  • VISWANATHA V., RAMACHANDRA AC, RAGHAVENDRA PRASANNA, PREM CHOWDARY KAKARLA, VIVEKA SIMHA PJ, NISHANT MOHAN. Implementation Of Tiny Machine Learning Models on Arduino 33 BLE For Gesture And Speech Recognition. 2022.
  • HYMEL, Shawn. et al. "Edge Impulse: An Mlops Platform for Tiny Machine Learning." Proceedings of the 6h MLSys Conference, Miami Beach, 2023.
  • EDGE IMPULSE. Edge Impulse. Available at: https://www.edgeimpulse.com/. Accessed on August 25, 2023.