Abstract

This article presents a novel three-dimensional-printable optical fiber force sensor used to guide the rehabilitation of patients with heart failure (HF), and builds the corresponding sleeping posture monitoring system. The designed sensing probe is mainly composed of a lamina emergent spring (LES), a prismatic-tip optical fiber, and a wireless-based signal collection module including WiFi and Bluetooth. A data and theoretical model-driven method has been proposed to derive the stiffness model of the LES with a small error of less than 10% compared with the experimental stiffness. To better obtain the sleeping posture characteristics, a herringbone sensing probe layout scheme with eight sensors has been proposed with consideration of the fiber bending-induced light loss. The calibration and performance experiments have been implemented to validate the reliability of the sensing probe including the wireless transmission function. A Sparrow Search Algorithm optimized back propagation neural network has been designed to distinguish the typical six sleeping postures with a high recognition accuracy of 98.1%. Several experiments have been carried out to verify the real-time performance, the feasibility of mutibed remote monitoring, and the long-term monitoring capability of the sleeping posture monitoring system. The monitoring results can be shared with the user's family member mobile phone or monitoring center to check their sleeping postures. Such merits indicate that fusing the wireless technique optical fiber force sensor has huge potential to guide the rehabilitation of HF patients

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