We report on the calibration and testing of a fiber Bragg grating (FBG)-based 2D-shape sensing strip for real-time monitoring of the position and orientation of the human spine during gait. The strip is evaluated for its use as an input for control of an exoskeleton for patients with spinal cord injury. By measuring the torsion and bending of the back, walking movements can be reconstructed. The 3D-printed strip has nine embedded fiber Bragg gratings that are located at specific places with respect to the vertebral column. Three FBGs are placed opposite to the thoracic vertebrae T6–T9, these FBGs are sensitive for measuring the bending of the spine during the gait cycle. Torsion is measured at two locations: at thoracic vertebra, T3 and at lumbar vertebra, L3. At these locations, the width of the strip is reduced to have a larger sensitivity for torsion. The strain at each FBG is measured using an interrogator. This leads to the radius of curvature and torsion as a function of time. The Frenet-Serret formulae are used to calculate the shape of the strip during the gait cycle. We have calibrated this FBG strip for curvature by bending it at known radius of different curvatures. We found a linear dependence between the strain and curvature. For torsion calibration we have rotated the strip with a stepper motor at different angles and monitored the strain. We, again, found a linear dependence with a small hysteresis. We mounted the strip on a healthy test subject and monitored their gait cycle. The FBG strip shows similar results when compared to a motion capture system based on multiple cameras. Although the fixation of the strip to a garment or on the back directly strongly influences the measured response, it does show a periodic and reproducible signal during the gait cycle.
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In order to achieve a level of community involvement and physical independence, being able to walk is the primary aim of many stroke survivors. It is therefore one of the most important goals during rehabilitation. Falls are common in all stages after stroke. Reported fall rates in the chronic stage after stroke range from 43 to 70% during one year follow up. Moreover, stroke survivors are more likely to become repeated fallers as compared to healthy older adults. Considering the devastating effects of falls in stroke survivors, adequate fall risk assessment is of paramount importance, as it is a first step in targeted fall prevention. As the majority of all falls occur during dynamic activities such as walking, fall risk could be assessed using gait analysis. It is only recent that technology enables us to monitor gait over several consecutive days, thereby allowing us to assess quality of gait in daily life. This thesis studies a variety of gait assessments with respect to their ability to assess fall risk in ambulatory chronic stroke survivors, and explores whether stroke survivors can improve their gait stability through PBT.
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Introduction: Falling causes long term disability and can even lead to death. Most falls occur during gait. Therefore improving gait stability might be beneficial for people at risk of falling. Recently arm swing has been shown to influence gait stability. However at present it remains unknown which mode of arm swing creates the most stable gait. Aim: To examine how different modes of arm swing affect gait stability. Method: Ten healthy young male subjects volunteered for this study. All subjects walked with four different arm swing instructions at seven different gait speeds. The Xsens motion capture suit was used to capture gait kinematics. Basic gait parameters, variability and stability measures were calculated. Results: We found an increased stability in the medio-lateral direction with excessive arm swing in comparison to normal arm swing at all gait speeds. Moreover, excessive arm swing increased stability in the anterior–posterior and vertical direction at low gait speeds. Ipsilateral and inphase arm swing did not differ compared to a normal arm swing. Discussion: Excessive arm swing is a promising gait manipulation to improve local dynamic stability. For excessive arm swing in the ML direction there appears to be converging evidence. The effect of excessive arm swing on more clinically relevant groups like the more fall prone elderly or stroke survivors is worth further investigating. Conclusion: Excessive arm swing significantly increases local dynamic stability of human gait.
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