Abstract

Regarding high-sensitivity human wrist joint motion monitoring in exercise rehabilitation; we develop a pair of novel wearable and sensitivity-enhanced plastic optical fiber (POF) strain sensors consisting of an etched grating fiber and a side-polished fiber stitched into a polyamide wrist brace. The two flexible and surface-treated fibers are; respectively; featured with an etched periodic gratings with a pitch of 6 mm and a depth of 0.5 mm and a D-shaped side-polished zone of ~300 µm depth and ~30 mm length; which, correspondingly, show the sensitivities of around 0.0176/° and 0.0167/° in a normalized bending angle by far larger than a conventional commercial POF, because it achieves a more sensitive strain-induced evanescent field interaction with the side-machined fibers. Moreover, in terms of the sensor response to bending deformation in the range of −40°~+40°, the former exhibits a better sensitivity in lower angle change, while the latter is superior as the bending angle increases; thereby arranging the two modified POFs separately at the side and back of the human wrist, in order to decouple the wrist joint behaviors induced by typical flexion-extension or abduction-adduction movements. Then, the circular and pentagonal wrist motion trajectory patterns are investigated, to demonstrate the maximum average single-axis motion error of 2.94° via the transformation of spatial angle to plane coordinate for the fabricated couple of POF sensors, which is lower than a recognized standard of 5°, thus suggesting the great potential in wearable exercise rehabilitation of human joints in the field of medical treatment and healing.

Highlights

  • Today, stroke is one of the leading causes of mortality in adults age 15 years and over throughout the world, and the worldwide incidence of stroke is set to escalate from 15.3 million to 23 million by2030 [1]

  • Despite a relatively lower sensitivity (~0.018/◦ ) to the abduction-adduction movement than the expected value for the etched grating plastic optical fiber (POF), wrist motion behaviors could be well decoupled by coordinating the use of the two types of designed POF sensors, in combination with the corresponding appropriate mounting positions in wrist brace

  • In comparison with the conventional POF, which is nearly insensitive to the normalized bending angle, the fabricated

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Summary

Introduction

Stroke is one of the leading causes of mortality in adults age 15 years and over throughout the world, and the worldwide incidence of stroke is set to escalate from 15.3 million to 23 million by. From the perspective of characterizing bending strain induced by wrist movements, we report a simple, flexible and wearable dual-sensor measurement scheme using a side-polished POF without external coatings and an etched grating POF with periodic cutting grooves, in virtue of the combination of enhanced macro-bend loss and intensity attenuation of the luminous wave transmitting in the optical fiber This novel scheme can offer higher sensitivity to bending deformation than a conventional POF sensor, due to more sensitive strain-induced interactions with the fiber, and implement more complicated wrist activities, such as wrist motion pattern recognition, compared with single-degree-of-freedom movement only by the side-polished POF sensors, as described earlier. Along with the use of an angle turntable for characterizing the sensor sensitivity to the bending angle, wrist circular and pentagonal motion trajectory test reveals the average resultant angle errors of 3.06◦ and 4.29◦ , in terms of the regressive normalized angle sensitivity in the corresponding flexion-extension and abduction-adduction ranges of −35◦ ~+35◦ and −20◦ ~+30◦ , along with a maximum resultant absolute error of 4.29◦ , which is comparable to the reliably accepted movement evaluation performance of 5◦ , according to the American Medical Association [21]

Fabrication of the Etched and D-Shaped POF Sensors
Optical Power Loss in Bent Fiber
Angle Calibration Experiment of POF Sensor
Wrist Movement Angle Detection
Wrist Movement Trajectory Detection
Findings
Conclusions
Full Text
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