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
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
Seizure detection using regression tree based feature selection and polynomial SVM classification.
This paper presents a novel patient-specific algorithm for detection of seizures in epileptic patients with low hardware complexity and low power consumption. In the proposed approach, we first compute the spectrogram of the input fragmented EEG signals from three or four electrodes. Each fragmented data clip is one second in duration. ⋯ The algorithm is tested using the intra-cranial EEG (iEEG) from the UPenn and Mayo Clinic's Seizure Detection Challenge database. It is shown that the proposed algorithm can achieve a sensitivity of 100.0%, an average area under curve (AUC) of 0.9818, a mean detection horizon of 5.8 seconds, and a specificity of 99.9% on using half of the training data for classification. The proposed approach also achieved a mean AUC of seizure detection and early seizure detection of 0.9136 on the testing data.
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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.