Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
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Conf Proc IEEE Eng Med Biol Soc · Jan 2015
Estimating instantaneous respiratory rate from the photoplethysmogram.
The photoplethysmogram (PPG) obtained from pulse oximetry shows the local changes of blood volume in tissues. Respiration induces variation in the PPG baseline due to the variation in venous blood return during each breathing cycle. We have proposed an algorithm based on the synchrosqueezing transform (SST) to estimate instantaneous respiratory rate (IRR) from the PPG. ⋯ The median RMS error was 0.39 breaths/min for all subjects which ranged from the lowest error of 0.18 breaths/min to the highest error of 13.86 breaths/min. A Bland-Altman plot showed an agreement between the IRR obtained from PPG and reference respiratory rate with a bias of -0.32 and limits agreement of -7.72 to 7.07. Extracting IRR from PPG expands the functionality of pulse oximeters and provides additional diagnostic power to this non-invasive monitoring tool.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2015
A high-accuracy surgical augmented reality system using enhanced integral videography image overlay.
Image guided surgery has been used in clinic to improve the surgery safety and accuracy. Augmented reality (AR) technique, which can provide intuitive image guidance, has been greatly evolved these years. As one promising approach of surgical AR systems, integral videography (IV) autostereoscopic image overlay has achieved accurate fusion of full parallax guidance into surgical scene. ⋯ Preliminary experiments validated that the image accuracy and resolution are improved with the proposed methods. The resolution of the IV image could be promoted to 1 mm for a micro lens array with pitch of 2.32 mm and IES magnification value of 0.5. The relative deviation of accuracy in depth and lateral directions are -4.68 ± 0.83% and -9.01 ± 0.42%.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2015
Estimation of physiological sub-millimeter displacement with CW Doppler radar.
Doppler radar physiological sensing has been studied for non-contact detection of vital signs including respiratory and heartbeat rates. This paper presents the first micrometer resolution Wi-Fi band Doppler radar for sub-millimeter physiological displacement measurement. A continuous-wave Doppler radar working at 2.4GHz is used for the measurement. ⋯ A mechanical mover was used as target, and programmed to conduct sinusoidal motions to simulate pulse motions. Measured displacements were compared with a reference system, which indicates a superior performance in accuracy for having absolute errors less than 10μm, and relative errors below 4%. It indicates the feasibility of highly accurate non-contact monitoring of physiological movements using Doppler radar.
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Catheters and flexible endoscopes are usually steered by mechanical wires that are driven from their base. Due to friction and buckling there is a need to place the driving actuator of the catheter at the catheter's tip. Such active catheter's manoeuvrability is much higher than wire-driven ones. ⋯ The magnitude of the bending torque of our actuator is created by internal hydraulic pressure in the tube and the steering direction is controlled by the thermal micro-actuator embedded in the wall of the tube. In this paper we present the modelling, optimization, design and testing of an initial prototype of such an actuator. We found that a 4 mm OD actuator made of TPU can bend to ±12°.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2015
Sleep apnea detection using time-delayed heart rate variability.
Sleep apnea is a sleep disorder distinguished by repetitive absence of breathing. Compared with the traditional expensive and cumbersome methods, sleep apnea diagnosis or screening with physiological information that can be easily acquired is needed. This paper describes algorithms using heart rate variability (HRV) to automatically detect sleep apneas as long as it can be easily acquired with unobtrusive sensors. ⋯ Experiments were conducted with a data set of 23 sleep apnea patients using support vector machine (SVM) classifiers and cross validations. Results show that using eleven HRV features with a time delay of 1.5 minutes rather than the features without time delay for SA detection, the overall accuracy increased from 74.9% to 76.2% and the Cohen's Kappa coefficient increased from 0.49 to 0.52. Further, an accuracy of 94.5% and a Kappa of 0.89 were achieved when applying subject-specific classifiers.