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

IF 5.3 2区医学 Q1 ENGINEERING, BIOMEDICAL

Biocybernetics and Biomedical Engineering Pub Date : 2024-09-23 DOI:10.1016/j.bbe.2024.09.002

Alessandra Angelucci , Federica Camuncoli , Federica Dotti , Filippo Bertozzi , Manuela Galli , Marco Tarabini , Andrea Aliverti

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引用次数: 0

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.

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验证用于动态活动期间心肺监测的人体传感器网络

在可穿戴设备领域，准确测量动态活动中的生理参数是一大挑战。这项工作的目的是提出一个完全可穿戴的无线人体传感器网络（WBSN），用于动态活动中的心肺监测，并根据参考测量系统对组成 WBSN 的设备进行验证。WBSN 由三个用于检测呼吸频率（RR）的惯性测量单元（IMU）和一个用于检测脉搏频率（PR）的第四个单元组成。30 名健康志愿者（17 名男性，平均年龄（25.9 ± 6.0）岁，平均体重（68.7 ± 9.7）公斤，平均身高（170.9 ± 9.5）厘米）参加了由步行、跑步和骑自行车组成的验证方案。参与者必须同时佩戴 WBSN 设备和参考仪器。事实证明，基于 IMU 的系统对骑车和跑步时的 RR 监测特别有效，整个组群的 RMSE 为 3.77 bpm。步行时的呼吸信号显示出与步幅相似的频率内容，因此很难正确过滤所需的信号内容。PR 与参考心率监测仪显示出良好的一致性。该系统利用有关运动的信息，通过一种特殊的信号处理算法改进了动态活动中的呼吸频率估计。

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来源期刊

Biocybernetics and Biomedical Engineering ENGINEERING, BIOMEDICAL-

CiteScore

16.50

自引率

6.20%

发文量

审稿时长

38 days

期刊介绍： Biocybernetics and Biomedical Engineering is a quarterly journal, founded in 1981, devoted to publishing the results of original, innovative and creative research investigations in the field of Biocybernetics and biomedical engineering, which bridges mathematical, physical, chemical and engineering methods and technology to analyse physiological processes in living organisms as well as to develop methods, devices and systems used in biology and medicine, mainly in medical diagnosis, monitoring systems and therapy. The Journal''s mission is to advance scientific discovery into new or improved standards of care, and promotion a wide-ranging exchange between science and its application to humans.