Advances in medicine and improvements in life quality has led to an increase in the life expectancy of the general population. An ageing world population have placed demands on the use of assistive technology and, in particular, towards novel healthcare devices and sensors. Besides the electromagnetic field immunity, polymer optical fiber (POF) sensors have additional advantages due to their material features such as high flexibility, lower Young’s modulus (enabling high sensitivity for mechanical parameters), higher elastic limits, and impact resistance. Such advantages are well-aligned with the instrumentation requirements of many healthcare devices and in movement analysis. Aiming at these advantages, this review paper presents the state-of-the-art developments of POF sensors for healthcare applications. A plethora of healthcare applications are discussed, which include movement analysis, physiological parameters monitoring, instrumented insoles, as well as instrumentation of healthcare robotic devices such as exoskeletons, smart walkers, actuators, prostheses, and orthosis. This review paper shows the feasibility of using POF sensors in healthcare applications and, due to the aforementioned advantages, it is possible to envisage a further widespread use of such sensors in this research field in the next few years.

This paper presents the development and application of a multiparameter, quasi-distributed smart textile based on embedded highly stretchable polymer optical fiber (POF) sensors. The POF is fabricated using the light polymerization spinning process, resulting a highly stretchable optical fiber, so-called LPS-POF, with Young’s modulus and elastic limits of 15 MPa and 17%, respectively. The differential scanning calorimetry shows a thermal stability of the LPS-POF in temperature range of 13–40 °C. The developed sensors are based on the optical power variation, which results in a fully portable and low-cost technique. In order to obtain a multiplexed sensor system, a technique based on flexible light emitting diodes (LEDs) on–off keying modulation is applied, where each LED represents the response of one sensor. The smart textile comprises of LPS-POF and three flexible LEDs embedded in neoprene textile fabric. The performance of the system is evaluated for temperature, transverse force and angular displacement detection at different planes. The sensors presented high linearity (mean determination coefficient of 0.99) and high repeatability (inter-measurement deviations below 5%). The sensor is also applied in activity detection, where the principal component analysis (PCA) was applied in the sensors responses and, in conjunction with clustering techniques such as k-means, indicate the possibility of detecting basic activities such as walking, sitting on a chair and squatting.

This paper proposes a fiber optic liquid level sensor system based on a silica fiber Bragg grating embedded into an epoxy resin diaphragm coupled to a temperature reference sensor, used to compensate the temperature cross-sensitivity for improving the liquid level measurement accuracy. The proposed system was tested in an industrial water tank with heating and recirculation. The results demonstrated a temperature cross-sensitivity reduction, enhancing the liquid level measurement thermal stability by a factor of nine, when compared with some single head sensor configurations reported in literature. Our system presents high linearity ( $R>0.999$ ), superior sensitivity (2.8 pm/mm), and much lower temperature related error (1.04 mm/°C), when compared with the other diaphragm-based sensors recently reported in the literature.

This paper presents a novel calibration procedure as a simple, yet powerful, method to place and align inertial sensors with body segments. The calibration can be easily replicated without the need of any additional tools. The proposed method is validated in three different applications: a computer mathematical simulation; a simplified joint composed of two semi-spheres interconnected by a universal goniometer; and a real gait test with five able-bodied subjects. Simulation results demonstrate that, after the calibration method is applied, the joint angles are correctly measured independently of previous sensor placement on the joint, thus validating the proposed procedure. In the cases of a simplified joint and a real gait test with human volunteers, the method also performs correctly, although secondary plane errors appear when compared with the simulation results. We believe that such errors are caused by limitations of the current inertial measurement unit (IMU) technology and fusion algorithms. In conclusion, the presented calibration procedure is an interesting option to solve the alignment problem when using IMUs for gait analysis.