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We hypothesize that our smartphone-based fingertip image-based heart rate detection methods reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively.

Background: Patients' expectations can influence antibiotic prescription by primary healthcare physicians. We assessed knowledge, attitude and practices towards antibiotic use for upper respiratory tract infections (URTIs), and whether knowledge is associated with increased expectations for antibiotics among patients visiting primary healthcare services in Singapore., Methods: Data was collected through a cross-sectional interviewer-assisted survey of patients aged ≥21 years waiting to see primary healthcare practitioners for one or more symptoms suggestive of URTI (cough, sore throat, runny nose or blocked nose) for 7 days or less, covering the demographics, presenting symptoms, knowledge, attitudes, beliefs and practices of URTI and associated antibiotic use. Univariate and multivariate logistic regression was used to assess independent factors associated with patients' expectations for antibiotics., Results: Nine hundred fourteen out of 987 eligible patients consulting 35 doctors were recruited from 24 private sector primary care clinics in Singapore. A third (307/907) expected antibiotics, of which a substantial proportion would ask the doctor for antibiotics (121/304, 40 %) and/or see another doctor (31/304, 10 %) if antibiotics were not prescribed. The majority agreed "antibiotics are effective against viruses" (715/914, 78 %) and that "antibiotics cure URTI faster" (594/912, 65 %). Inappropriate antibiotic practices include "keeping antibiotics stock at home" (125/913, 12 %), "taking leftover antibiotics" (114/913, 14 %) and giving antibiotics to family members (62/913, 7 %). On multivariate regression, the following factors were independently associated with wanting antibiotics (odds ratio; 95 % confidence interval): Malay ethnicity (1.67; 1.00-2.79), living in private housing (1.69; 1.13-2.51), presence of sore throat (1.50; 1.07-2.10) or fever (1.46; 1.01-2.12), perception that illness is serious (1.70; 1.27-2.27), belief that antibiotics cure URTI faster (5.35; 3.76-7.62) and not knowing URTI resolves on its own (2.18; 1.08-2.06), while post-secondary education (0.67; 0.48-0.94) was inversely associated. Those with lower educational levels were significantly more likely to have multiple misconceptions about antibiotics., Conclusion: Majority of patients seeking primary health care in Singapore are misinformed about the role of antibiotics in URTI. Agreeing with the statement that antibiotics cure URTI faster was most strongly associated with wanting antibiotics. Those with higher educational levels were less likely to want antibiotics, while those with lower educational levels more likely to have incorrect knowledge.

Background: Atrial fibrillation (AF) is a common and dangerous rhythm abnormality. Smartphones are increasingly used for mobile health applications by older patients at risk for AF and may be useful for AF screening., Objectives: To test whether an enhanced smartphone app for AF detection can discriminate between sinus rhythm (SR), AF, premature atrial contractions (PACs), and premature ventricular contractions (PVCs)., Methods: We analyzed two hundred and nineteen 2-minute pulse recordings from 121 participants with AF (n = 98), PACs (n = 15), or PVCs (n = 15) using an iPhone 4S. We obtained pulsatile time series recordings in 91 participants after successful cardioversion to sinus rhythm from preexisting AF. The PULSE-SMART app conducted pulse analysis using 3 methods (Root Mean Square of Successive RR Differences; Shannon Entropy; Poincare plot). We examined the sensitivity, specificity, and predictive accuracy of the app for AF, PAC, and PVC discrimination from sinus rhythm using the 12-lead EKG or 3-lead telemetry as the gold standard. We also administered a brief usability questionnaire to a subgroup (n = 65) of app users., Results: The smartphone-based app demonstrated excellent sensitivity (0.970), specificity (0.935), and accuracy (0.951) for real-time identification of an irregular pulse during AF. The app also showed good accuracy for PAC (0.955) and PVC discrimination (0.960). The vast majority of surveyed app users (83%) reported that it was "useful" and "not complex" to use., Conclusion: A smartphone app can accurately discriminate pulse recordings during AF from sinus rhythm, PACs, and PVCs., (© 2015 Wiley Periodicals, Inc.)

We hypothesize that our smartphone-based arrhythmia discrimination algorithm with data acquisition approach reliably differentiates between normal sinus rhythm (NSR), atrial fibrillation (AF), premature ventricular contractions (PVCs) and premature atrial contraction (PACs) in a diverse group of patients having these common arrhythmias. We combine root mean square of successive RR differences and Shannon entropy with Poincare plot (or turning point ratio method) and pulse rise and fall times to increase the sensitivity of AF discrimination and add new capabilities of PVC and PAC identification. To investigate the capability of the smartphone-based algorithm for arrhythmia discrimination, 99 subjects, including 88 study participants with AF at baseline and in NSR after electrical cardioversion, as well as seven participants with PACs and four with PVCs were recruited. Using a smartphone, we collected 2-min pulsatile time series from each recruited subject. This clinical application results show that the proposed method detects NSR with specificity of 0.9886, and discriminates PVCs and PACs from AF with sensitivities of 0.9684 and 0.9783, respectively.

We introduce a new method to reconstruct motion and noise artifact (MNA) contaminated photoplethysmogram (PPG) data. A method to detect MNA corrupted data is provided in a companion paper. Our reconstruction algorithm is based on an iterative motion artifact removal (IMAR) approach, which utilizes the singular spectral analysis algorithm to remove MNA artifacts so that the most accurate estimates of uncorrupted heart rates (HRs) and arterial oxygen saturation (SpO2) values recorded by a pulse oximeter can be derived. Using both computer simulations and three different experimental data sets, we show that the proposed IMAR approach can reliably reconstruct MNA corrupted data segments, as the estimated HR and SpO2 values do not significantly deviate from the uncorrupted reference measurements. Comparison of the accuracy of reconstruction of the MNA corrupted data segments between our IMAR approach and the time-domain independent component analysis (TD-ICA) is made for all data sets as the latter method has been shown to provide good performance. For simulated data, there were no significant differences in the reconstructed HR and SpO2 values starting from 10 dB down to -15 dB for both white and colored noise contaminated PPG data using IMAR; for TD-ICA, significant differences were observed starting at 10 dB. Two experimental PPG data sets were created with contrived MNA by having subjects perform random forehead and rapid side-to-side finger movements show that; the performance of the IMAR approach on these data sets was quite accurate as non-significant differences in the reconstructed HR and SpO2 were found compared to non-contaminated reference values, in most subjects. In comparison, the accuracy of the TD-ICA was poor as there were significant differences in reconstructed HR and SpO2 values in most subjects. For non-contrived MNA corrupted PPG data, which were collected with subjects performing walking and stair climbing tasks, the IMAR significantly outperformed TD-ICA as the former method provided HR and SpO2 values that were non-significantly different than MNA free reference values.

Motion and noise artifacts (MNA) are a serious obstacle in utilizing photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a MNA detection method which can provide a clean vs. corrupted decision on each successive PPG segment. For motion artifact detection, we compute four time-domain parameters: (1) standard deviation of peak-to-peak intervals (2) standard deviation of peak-to-peak amplitudes (3) standard deviation of systolic and diastolic interval ratios, and (4) mean standard deviation of pulse shape. We have adopted a support vector machine (SVM) which takes these parameters from clean and corrupted PPG signals and builds a decision boundary to classify them. We apply several distinct features of the PPG data to enhance classification performance. The algorithm we developed was verified on PPG data segments recorded by simulation, laboratory-controlled and walking/stair-climbing experiments, respectively, and we compared several well-established MNA detection methods to our proposed algorithm. All compared detection algorithms were evaluated in terms of motion artifact detection accuracy, heart rate (HR) error, and oxygen saturation (SpO2) error. For laboratory controlled finger, forehead recorded PPG data and daily-activity movement data, our proposed algorithm gives 94.4, 93.4, and 93.7% accuracies, respectively. Significant reductions in HR and SpO2 errors (2.3 bpm and 2.7%) were noted when the artifacts that were identified by SVM-MNA were removed from the original signal than without (17.3 bpm and 5.4%). The accuracy and error values of our proposed method were significantly higher and lower, respectively, than all other detection methods. Another advantage of our method is its ability to provide highly accurate onset and offset detection times of MNAs. This capability is important for an automated approach to signal reconstruction of only those data points that need to be reconstructed, which is the subject of the companion paper to this article. Finally, our MNA detection algorithm is real-time realizable as the computational speed on the 7-s PPG data segment was found to be only 7 ms with a Matlab code.

Aim: To study the pathology of two cases of human Hendra virus infection, one with no clinical encephalitis and one with relapsing encephalitis., Methods: Autopsy tissues were investigated by light microscopy, immunohistochemistry and in situ hybridization., Results: In the patient with acute pulmonary syndrome but not clinical acute encephalitis, vasculitis was found in the brain, lung, heart and kidney. Occasionally, viral antigens were demonstrated in vascular walls but multinucleated endothelial syncytia were absent. In the lung, there was severe inflammation, necrosis and viral antigens in type II pneumocytes and macrophages. The rare kidney glomerulus showed inflammation and viral antigens in capillary walls and podocytes. Discrete necrotic/vacuolar plaques in the brain parenchyma were associated with antigens and viral RNA. Brain inflammation was mild although CD68(+) microglia/macrophages were significantly increased. Cytoplasmic viral inclusions and antigens and viral RNA in neurones and ependyma suggested viral replication. In the case of relapsing encephalitis, there was severe widespread meningoencephalitis characterized by neuronal loss, macrophages and other inflammatory cells, reactive blood vessels and perivascular cuffing. Antigens and viral RNA were mainly found in neurones. Vasculitis was absent in all the tissues examined., Conclusions: The case of acute Hendra virus infection demonstrated evidence of systemic infection and acute encephalitis. The case of relapsing Hendra virus encephalitis showed no signs of extraneural infection but in the brain, extensive inflammation and infected neurones were observed. Hendra virus can cause acute and relapsing encephalitis and the findings suggest that the pathology and pathogenesis are similar to Nipah virus infection.

Purpose: Local anesthetic wound infusion has been investigated in recent years as a potential alternative to standard analgesic regimens after major surgery. This study investigates the efficacy of a continuous wound infusion of ropivacaine in conjunction with best practice postoperative analgesia after midline laparotomy for abdominal colorectal surgery., Methods: We performed a randomized, participant and outcome assessor-blinded, placebo-controlled trial on patients presenting for major abdominal colorectal surgery at our institution between December 2003 and February 2006. Patients were allocated to receive ropivacaine 0.54 percent or normal saline via a dual catheter Painbuster Soaker (I-Flow Corporation, OH, USA) continuous infusion device into their midline laparotomy wound for 72 hours postoperatively., Results: A total of 310 patients were included in this study. The continuous wound infusion of ropivacaine after abdominal colorectal surgery conveys minimal benefit compared with saline wound infusion. No statistically significant difference could be shown for: pain at rest, morphine usage, length of stay, mobility, nausea, or return of bowel function. There was a small, statistically significant difference in mean pain on movement on Day 1 for the ropivacaine group (adjusted mean difference -0.6 (range, -1.08 to -0.13)). Although this trend continued on Days 2 and 3, the differences between groups were no longer statistically significant., Conclusions: Management of pain after major abdominal colorectal surgery is best achieved through adopting a multimodal approach to analgesia. Delivery of ropivacaine to midline laparotomy wounds via a Painbuster Soaker device is safe, but we have not demonstrated any significant clinical advantage over current best practice.

We have developed a small scintillation camera dedicated to breast imaging and have evaluated the performance of the system. In order to increase the limited field of view (FOV) determined by the size of a position-sensitive photomultiplier tube (PSPMT), the imaging characteristics of a diverging hole collimator (DHC) were also investigated. The small scintillation camera system consists of an NaI(Tl) crystal (60 mm x 60 mm x 6 mm) coupled to a Hamamatsu R3941 PSPMT, a resistor chain circuit, preamplifiers, nuclear instrument modules, an analogue to digital converter and a PC for control and display. The intrinsic energy resolution of the system was 12.9% FWHM at 140 keV. The spatial resolution was measured using a line-slit mask and 99mTc point sources and was 3.1 mm FWHM. The intrinsic sensitivity of the system was approximately 162 counts/s kBq(-1). The DHC made it possible to image a larger FOV (75 x 75 mm2 at the surface of collimator) than a parallel-hole collimator (60 x 60 mm2). The system sensitivity obtained using the DHC gradually decreased with distance (3% at 1 cm, 6% at 2 cm and 9% at 3 cm). The results demonstrate that the system developed in this study could be utilized clinically to image malignant breast tumours. A DHC can be employed to expand the FOV of the system confined by the size of PSPMT with a modest compromise in the performance of the system.