Respiration (RIP)

Inductive respiration sensor designed for signal acquisition even in dynamic settings.

This high-performance inductive respiration sensor has been specifically designed having dynamic conditions in mind (e.g. ambulatory sensing). The sensing element is embedded in the chest strap fabric and spans its full length.

The elastic chest-belt can be adjusted in length to be applicable on different anatomies (e.g. male and/or female), body locations (e.g. thorax and/or abdomen), and thorax/abdomen circumferences. Typical applications of this sensor include respiration monitoring to determine respiration cycles, rates, relative amplitudes, and other features.

Features
  • Inductive measurement
  • Adjustable elastic chest strap
  • Displacement measurement
  • Pre-conditioned analog output
  • Raw signal output
  • Ready-to-use & miniaturized form-factor
Type Inductive
Output 0-3V
Connector Type UC-E6 (Male)
Consumption ~1mA
Cable Length 100cm±0.5cm (customizable)

This sensor is not a standalone use sensor and requires the use of a biosignalsplux hub. It can be used with the following biosignalsplux kits and systems for data acquisition:

Respiration Analysis

The Respiration Analysis add-on for the OpenSignals (r)evolution software is the ideal software extension for the biosignalsplux Piezo-Electric Respiration (PZT) and Inductive Respiration (RIP) sensors. It is designed to extract temporal and spectral parameters to provide useful information about the breathing dynamics, such as respiratory rate, amplitude parameters, and basic spectral analysis.

Find Out More


R. Fonseca-Pinto, N. Lopes, G. Brito, M. Lages, M. Guarino, Assessing autonomic control of metabolic syndrome by principal component analysis: a data driven methodology, in Health and Technology, vol. 10, pp. 79-85, 2020

M. Shakhih, A. Wahab, M. Salim, Assessment of inspiration and expiration time using infrared thermal imaging modality, in Infrared Physics & Technology, vol. 99, pp. 129-139, 2019

A. Reiss, I. Indlekofer, P. Schmidt, K. van Laerhoven, Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks, in Sensors, vol. 19, no. 14:3079, pp. 1-27, 2019

F. Marques, A. Bernardino, J. Jorge, D. Lopes, Estimating respiratory frequency by filtering Kinect v2 skeletal data, in 2nd International Congress of CiiEM - Translational Research and Innovation in Human and Health Sciences, 2018

M. Torrado, H. Silva, S. Eusébio, A. Fred, S. Ouakinin, Alexithymia; Physiological Reactivity and Cognitive Appraisals of Emotional Stimuli in Opiate Dependents: A Pilot Study., in Journal of Neurology & Neurophysiology, vol. 6, no. 1, pp. 1-8, 2015

Looking for more?

Visit the biosignalsplux publications page for a full list of available publications.

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