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 2013
Development of a smart backboard system for real-time feedback during CPR chest compression on a soft back support surface.
The quality of cardiopulmonary resuscitation (CPR) is often inconsistent and frequently fails to meet recommended guidelines. One promising approach to address this problem is for clinicians to use an active feedback device during CPR. ⋯ Based on adult CPR manikin tests it was found that the accuracy of the estimated CC depth for a dual accelerometer feedback system is significantly better (7.3% vs. 24.4%) than for a single accelerometer system on soft back support surfaces, in the absence or presence of a backboard. In conclusion, the algorithm used was found to be suitable for a real-time, dual accelerometer CPR feedback application since it yielded reasonable accuracy in terms of CC depth estimation, even when used on a soft back support surface.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Demonstrating the accuracy of an in-hospital ambulatory patient monitoring solution in measuring respiratory rate.
This paper presents clinical testing conducted to evaluate the accuracy of Aingeal, a wireless in-hospital patient monitor, in measuring respiration rate via impedance pneumography. Healthy volunteers were invited to simultaneously wear a CE Marked Aingeal vital signs monitor and a capnograph, the current gold standard in respiration rate measurement. ⋯ Statistical analysis of the data collected shows a mean difference of -0.73, a standard deviation of 1.61, limits of agreement of -3.88 and +2.42 bpm and a P-value of 0.22. This testing demonstrates comparable performance of the Aingeal device in measuring respiration rate with a well-accepted and widely used alternative method.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
A new method to increase the quality of cardiopulmonary resuscitation in hospital.
In order to ensure that high-quality cardio-pulmonary-resuscitation (CPR) is performed, many kinds of feedback devices have been developed that are helpful for achieving correct chest compression (CC) in manikin studies. However, the mattress compression depth (MCD) can cause overestimation of chest compression depth (CCD) during CPR using a feedback device. Herein, we propose a new method using a vinyl cover that encloses the foam mattress and is compressed by vacuum pump just before performing CPR, which could increase the performance of CCs during CPR.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Fully automatic rapid DNA Ploidy Analyzer for intraoperative rapid diagnosis support.
Frozen section studies are a useful method to rapidly define tumor malignancy and identify the extent of surgical resection. However, diagnosis with a frozen section is qualitative and sometimes difficult. Therefore a quantitative method for grading tumors is desired. ⋯ We also obtained a good correlation between the MI and histological grade (WHO grading). Our new system also enabled finishing the process from sample preparation to the end of analysis in ten minutes or less. These results demonstrate that our fully automatic rapid DNA ploidy analyzer is feasible for rapid determination of glioma presence in a surgical biopsy sample.
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Conf Proc IEEE Eng Med Biol Soc · Jan 2013
Combined use of sEMG and accelerometer in hand motion classification considering forearm rotation.
Hand motion classification using surface electromyography (sEMG) has been widely studied for its applications in upper-limb prosthesis and human-machine interface etc. Pattern-recognition based control methods have many advantages, and the reported classification accuracy can meet the requirements of practical applications. ⋯ In this paper, we give a pilot study of the reverse effect of forearm rotations on hand motion classification, and the results show that the forearm rotations can substantially degrade the classifier's performance: the average intra-position error is only 2.4%, but the average interposition classification error is as high as 44.0%. To solve this problem, we use an extra accelerometer to estimate the forearm rotation angles, and the best combination of sEMG data and accelerometer outputs can reduce the average classification error to 3.3%.