Validation of a body sensor network for cardiorespiratory monitoring during dynamic activities

One of the major challenges in the field of wearable devices is to accurately measure physiological parameters during dynamic activities. The aim of this work is to present a completely wearable Wireless Body Sensor Network (WBSN) for cardio-respiratory monitoring during dynamic activities and a validation of the devices composing the WBSN against reference measurement systems. The WBSN is composed of three inertial measurement units (IMUs) to detect the respiratory rate (RR), and of a fourth unit to detect the pulse rate (PR). 30 healthy volunteers (17 men, mean age 25.9 ± 6.0 years, mean weight 68.7 ± 9.7 kg, mean height 170.9 ± 9.5 cm) were enrolled in a validation protocol consisting in walking, running, and cycling. The participants had to simultaneously wear the devices of the WBSN and reference instruments. The IMU-based system proved to be particularly effective in monitoring RR during cycling, with a RMSE of 3.77 bpm for the complete cohort, and during running. The respiratory signal during walking exhibited a frequency content like the stride, making it difficult to properly filter the desired signal content. PR showed good agreement with the reference heart rate monitor. The system exploits information regarding motion to improve RR estimation during dynamic activities thanks to an ad hoc signal processing algorithm.

Authors

Institutions

Publication Details

Journal
Journal of Applied Biomedicine
Published
2024-09-23
DOI
https://doi.org/10.1016/j.bbe.2024.09.002
Citations
13
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
2.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Validation of a body sensor network for cardiorespiratory monitoring during dynamic activities

Federica Dotti, Alessandra Angelucci, Manuela Galli, Filippo Bertozzi et al.
13 citations
Journal of Applied Biomedicine
Non-Invasive Vital Sign Monitoring
2.40
article

Validation of a body sensor network for cardiorespiratory monitoring during dynamic activities

Federica Dotti, Alessandra Angelucci, Manuela Galli, Filippo Bertozzi, Marco Tarabini, Federica Camuncoli, Andréa Aliverti
article en
13 citations

Abstract

One of the major challenges in the field of wearable devices is to accurately measure physiological parameters during dynamic activities. The aim of this work is to present a completely wearable Wireless Body Sensor Network (WBSN) for cardio-respiratory monitoring during dynamic activities and a validation of the devices composing the WBSN against reference measurement systems. The WBSN is composed of three inertial measurement units (IMUs) to detect the respiratory rate (RR), and of a fourth unit to detect the pulse rate (PR). 30 healthy volunteers (17 men, mean age 25.9 ± 6.0 years, mean weight 68.7 ± 9.7 kg, mean height 170.9 ± 9.5 cm) were enrolled in a validation protocol consisting in walking, running, and cycling. The participants had to simultaneously wear the devices of the WBSN and reference instruments. The IMU-based system proved to be particularly effective in monitoring RR during cycling, with a RMSE of 3.77 bpm for the complete cohort, and during running. The respiratory signal during walking exhibited a frequency content like the stride, making it difficult to properly filter the desired signal content. PR showed good agreement with the reference heart rate monitor. The system exploits information regarding motion to improve RR estimation during dynamic activities thanks to an ad hoc signal processing algorithm.

Journal of Applied BiomedicineVol. 44(4)
Politecnico di Milano (IT)
Openalex Percentile: Top 11%
Non-Invasive Vital Sign Monitoring
2.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.