In non-invasive ventilation, continuous monitoring of respiratory volumes is essential. Here, we present a method for the measurement of respiratory volumes by a single fiber-grating sensor of bending and provide the proof-of-principle by applying a calibration-test measurement procedure on a set of 18 healthy volunteers. Results establish a linear correlation between a change in lung volume and the corresponding change in a local thorax curvature. They also show good sensor accuracy in measurements of tidal and minute respiratory volumes for different types of breathing. The proposed technique does not rely on the air flow through an oronasal mask or the observation of chest movement by a clinician, which distinguishes it from the current clinical practice.

Abstract.A series of in-line curvature sensors on a garment are used to monitor the thoracic and abdominal movements of a human during respiration. These results are used to obtain volumetric tidal changes of the human torso in agreement with a spirometer used simultaneously at the mouth. The curvature sensors are based on long-period gratings ͑LPGs͒ written in a progressive three-layered fiber to render the LPGs insensitive to the refractive index external to the fiber. A curvature sensor consists of the fiber long-period grating laid on a carbon fiber ribbon, which is then encapsulated in a low-temperature curing silicone rubber. The sensors have a spectral sensitivity to curvature, d / dR from ϳ7-nm m to ϳ9-nm m. The interrogation technique is borrowed from derivative spectroscopy and monitors the changes in the transmission spectral profile of the LPG's attenuation band due to curvature. The multiplexing of the sensors is achieved by spectrally matching a series of distributed feedback ͑DFB͒ lasers to the LPGs. The versatility of this sensing garment is confirmed by it being used on six other human subjects covering a wide range of body mass indices. Just six fully functional sensors are required to obtain a volumetric error of around 6%. © 2007 Society of Photo-Optical Instrumentation Engineers.

No abstract

Abstract. An array of in-line curvature sensors on a garment is used to monitor the thoracic and abdominal movements of a human during respiration. The results are used to obtain volumetric changes of the human torso in agreement with a spirometer used simultaneously at the mouth. The array of 40 in-line fiber Bragg gratings is used to produce 20 curvature sensors at different locations, each sensor consisting of two fiber Bragg gratings. The 20 curvature sensors and adjoining fiber are encapsulated into a low-temperature-cured synthetic silicone. The sensors are wavelength interrogated by a commercially available system from Moog Insensys, and the wavelength changes are calibrated to recover curvature. A three-dimensional algorithm is used to generate shape changes during respiration that allow the measurement of absolute volume changes at various sections of the torso. It is shown that the sensing scheme yields a volumetric error of 6%. Comparing the volume data obtained from the spirometer with the volume estimated with the synchronous data from the shape-sensing array yielded a correlation value 0.86 with a Pearson's correlation coefficient p < 0.01.

A real-time three-dimensional (3D) object sensing and reconstruction scheme is presented that can be applied on any arbitrary corporeal shape. Operation is demonstrated on several calibrated objects. The system uses curvature sensors based upon in-line fiber Bragg gratings encapsulated in a low-temperature curing synthetic silicone. New methods to quantitatively evaluate the performance of a 3D object-sensing scheme are developed and appraised. It is shown that the sensing scheme yields a volumetric error of 1% to 9%, depending on the object. © 2012 Optical Society of America OCIS codes: 060.2370, 060.3735, 120.4820, 110.6880, 280.4788. One of the main goals driving forward the research and development of fiber-optic sensing systems is their application in the field of structural health monitoring [1,2] and shape sensing [3,4]. There are several applications for shape-sensing, such as spatial awareness and control of robots in hazardous conditions (e.g., deep-water semisubmersible drilling platform and subsea production systems) [5,6] or profiling minimally invasive (keyhole) surgery [7], to name a few.There are a large number of shape sensing systems that have fiber Bragg gratings (FBG) as the sensing elements that monitor the strain experienced by the sensors that are adhered to the object and use a shape determination algorithm based upon a strain mapping technique [1,3]. Other sensing systems include fiber-optic loop sensors based on bend-induced loss; this technique is used in the commercially available system called ShapeTape [2] with others based upon distributed sensing, such as intrinsic Rayleigh backscattering employing optical frequency domain reflectometry [8]. Alternative approaches to shape sensing include employing camera systems using complex, shape-sensing recognition algorithms [9].The three-dimensional (3D) shape-sensing system demonstrated in this Letter is based upon fiber bidirectional sensing elements that have the ability to distinguish both positive and negative curvature variation upon a twodimensional (2D) plane. The element consists of two FBGs that are temperature self-compensating due to the fact that the difference in wavelength is measured and calibrated to curvature (concave and convex) (see Fig. 1). The curvature information deduced from all sensing nodes within the scheme is processed by bespoke algorithms to construct a 3D representation of the object in question. As we will show, our method offers advantages in comparison to previously existing approaches, the most important of which is the real-time 3D shape reconstruction through tailor-made algorithms. The volumetric error of the sensing system was found for shapes with known volumes (i.e., arcs, ellipsoidal cylinders, and spheres) and ranged from 1% to 9% depending upon the shape being used. In addition, we present an efficient and, to the extend of our knowledge, entirely new approach to the evaluation of the performance of a 3D object shape sensing system, obtaining a figure-of-merit that should be a useful tool for...