Research Unit of Measurements and Biomedical Instrumentation, Departmental of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy.
Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Rome, Italy.
Sensors (Basel). 2024 Mar 21;24(6):2018. doi: 10.3390/s24062018.
Respiratory rate (fR) monitoring through wearable devices is crucial in several scenarios, providing insights into well-being and sports performance while minimizing interference with daily activities. Strain sensors embedded into garments stand out but require thorough investigation for optimal deployment. Optimal sensor positioning is often overlooked, and when addressed, the quality of the respiratory signal is neglected. Additionally, sensor metrological characterization after sensor integration is often omitted. In this study, we present the design, development, and feasibility assessment of a smart t-shirt embedded with two flexible sensors for fR monitoring. Guided by a motion capture system, optimal sensor design and position on the chest wall were defined, considering both signal magnitude and quality. The sensors were developed, embedded into the wearable system, and metrologically characterized, demonstrating a remarkable response to both static (sensitivity 9.4 Ω⋅%-1 and 9.1 Ω⋅%-1 for sensor A and sensor B, respectively) and cyclic loads (min. hysteresis span 20.4% at 36 bpm obtained for sensor A). The feasibility of the wearable system was assessed on healthy volunteers both under static and dynamic conditions (such as running, walking, and climbing stairs). A mean absolute error of 0.32 bpm was obtained by averaging all subjects and tests using the combination of the two sensors. This value was lower than that obtained using both sensor A (0.53 bpm) and sensor B (0.78 bpm) individually. Our study highlights the importance of signal amplitude and quality in optimal sensor placement evaluation, as well as the characterization of the embedded sensors for metrological assessment.
通过可穿戴设备监测呼吸频率（fR）在多个场景中至关重要，可深入了解健康状况和运动表现，同时最大限度地减少对日常活动的干扰。嵌入服装中的应变传感器引人注目，但需要进行彻底的研究，以实现最佳部署。最佳传感器位置通常被忽视，而在解决这个问题时，呼吸信号的质量也被忽视了。此外，传感器集成后的计量特性通常也被忽略。在这项研究中，我们展示了一款智能 t 恤的设计、开发和可行性评估，该 t 恤嵌入了两个用于监测 fR 的柔性传感器。通过运动捕捉系统的指导，定义了传感器在胸壁上的最佳设计和位置，同时考虑了信号幅度和质量。开发了传感器，并将其嵌入可穿戴系统中，进行了计量特性评估，结果表明传感器对静态（传感器 A 和传感器 B 的灵敏度分别为 9.4 Ω⋅%-1和 9.1 Ω⋅%-1）和循环负载（在 36 bpm 时，传感器 A 的最小滞后跨度为 20.4%）均有显著响应。在静态和动态条件（如跑步、步行和爬楼梯）下，对健康志愿者进行了可穿戴系统的可行性评估。使用两个传感器的组合，通过对所有受试者和测试进行平均，获得了 0.32 bpm 的平均绝对误差。该值低于单独使用传感器 A（0.53 bpm）和传感器 B（0.78 bpm）时获得的值。我们的研究强调了在最佳传感器放置评估中信号幅度和质量的重要性，以及嵌入传感器进行计量评估的重要性。
