Photoplethysmography temporal marker-based machine learning classifier for anesthesia drug detection

Anesthesia drug overdose hazards and lack of gold standards in anesthesia monitoring lead to an urgent need for accurate anesthesia drug detection. To investigate the PPG waveform features affected by anesthesia drugs and develop a machine-learning classifier with high anesthesia drug sensitivity. This study used 64 anesthesia and non-anesthesia patient data (32 cases each), extracted from Queensland and MIMIC-II databases, respectively. The key waveform features (total area, rising time, width 75%, 50%, and 25%) were extracted from 16,310 signal recordings (5-s duration). Discriminant analysis, support vector machine (SVM), and K-nearest neighbor (KNN) were evaluated by splitting the dataset into halve training (11 patients, 8570 segments) and halve testing dataset (11 patients, 7740 segments). Significant differences exist between PPG waveform features of anesthesia and non-anesthesia groups (p  0.05). The KNN classifier achieved 91.7% (AUC = 0.95) anesthesia detection accuracy with the highest sensitivity (0.88) and specificity (0.90) as compared to other classifiers. Kohen’s kappa also shows almost perfect agreement (0.79) with the KNN classifier. The KNN classifier trained with significant PPG features has the potential to be used as a reliable, non-invasive, and low-cost method for the detection of anesthesia drugs for depth analysis during surgical operations and postoperative monitoring. GRAPHICAL ABSTRACT: [Image: see text

Low dose albumin for the prevention of renal impairment following large volume paracentesis in cirrhosis.

OBJECTIVES: To evaluate the effect of low dose Albumin i.e. 4 grams per litre of ascitic fluid after large volume paracentesis (LVP) for the prevention of paracentesis induced circulatory dysfunction (PICD) related renal impairment in cirrhosis. METHODS: Case records of all patients with cirrhosis who underwent LVP from January 12(th), 2011 till December 29(th), 2013 were reviewed. Patients were excluded if they had spontaneous bacterial peritonitis, creatinine \u3e1.5 mg/dl, hepatoma or if volume of ascitic fluid removed was \u3c5 litres. Data including age, gender, cause of cirrhosis, CTP score and volume of ascitic fluid drained were noted. In addition serum creatinine and serum sodium at baseline and one week post paracentesis were recorded. RESULTS: Two hundred and fourteen patients with cirrhosis underwent LVP during the study period. One hundred and thirty nine patients met the inclusion criteria and were analyzed. Patients were divided into two groups based on the amount of albumin given. The amount of albumin given was 25 grams and 50 grams while the volume of ascitic fluid removed were 6.2±1 litres and 10.4±1.5 litres in groups A and B respectively. One hundred and eight patients were in group A while thirty one patients were in group B respectively. Both groups received albumin at a dose of 4 grams per litre of ascitic fluid removed. Mean age in both groups were 53 years. Hepatitis C was the commonest etiology in both the groups, followed by Hepatitis B. More than 70% patients in both the groups were in child class C. Serum creatinine at baseline and one week post LVP was 1.04±0.24 mg/dl and 1.07±0.35 mg/dl in GROUP A while 1.11±0.23 mg/dl and 1.41±0.94 mg/dl in GROUP B. (P value 0.35). Similarly, serum sodium at baseline and one week post LVP was 130 ±5.6 meq/lit and 129.6±5.9 meq/lit in GROUP A while 127.6±5.8 meq/lit and 128±6.2 meq/lit in GROUP B respectively. (P value 0.14). CONCLUSION: This study suggests that 4 grams of albumin per litre of ascitic fluid drained is effective in preventing the PICD related renal impairment following large volume paracentesis in cirrhosis

Consistency in Geometry Among Coronary Atherosclerotic Plaques Extracted From Computed Tomography Angiography

Background: The three-dimensional (3D) geometry of coronary atherosclerotic plaques is associated with plaque growth and the occurrence of coronary artery disease. However, there is a lack of studies on the 3D geometric properties of coronary plaques. We aim to investigate if coronary plaques of different sizes are consistent in geometric properties.Methods: Nineteen cases with symptomatic stenosis caused by atherosclerotic plaques in the left coronary artery were included. Based on attenuation values on computed tomography angiography images, coronary atherosclerotic plaques and calcifications were identified, 3D reconstructed, and manually revised. Multidimensional geometric parameters were measured on the 3D models of plaques and calcifications. Linear and non-linear (i.e., power function) fittings were used to investigate the relationship between multidimensional geometric parameters (length, surface area, volume, etc.). Pearson correlation coefficient (r), R-squared, and p-values were used to evaluate the significance of the relationship. The analysis was performed based on cases and plaques, respectively. Significant linear relationship was defined as R-squared > 0.25 and p < 0.05.Results: In total, 49 atherosclerotic plaques and 56 calcifications were extracted. In the case-based analysis, significant linear relationships were found between number of plaques and number of calcifications (r = 0.650, p = 0.003) as well as total volume of plaques (r = 0.538, p = 0.018), between number of calcifications and total volume of plaques (r = 0.703, p = 0.001) as well as total volume of calcification (r = 0.646, p = 0.003), and between the total volumes of plaques and calcifications (r = 0.872, p < 0.001). In plaque-based analysis, the power function showed higher R-squared values than the linear function in fitting the relationships of multidimensional geometric parameters. Two presumptions of plaque geometry in different growth stages were proposed with simplified geometric models developed. In the proposed models, the exponents in the power functions of geometric parameters were in accordance with the fitted values.Conclusion: In patients with coronary artery disease, coronary plaques and calcifications are positively related in number and volume. Different coronary plaques are consistent in the relationship between geometry parameters in different dimensions

Quantification of Hyperhidrosis using Electronic Sudometer

Human skin has various pathologies in the form of acute and chronic diseases. Some are only cosmetic diseases which are not harmful for life but they can affect mental health and disrupt daily activities. Hyperhidrosis is one of these cosmetic diseases which may be caused by diabetes, infections, or thyroid hyper activity, or can be inherited. There are some examinations for testing hyperhidrosis, e.g. gravimetric and minor starch-iodine test. There are some devices that can measure sweat but are not specifically used or even intended for use on hyperhidrosis. A non-invasive prototype instrument called Electronic Sudometer using the principle of electrical impedance measurement has been developed. The philosophy behind this prototype is to make an instrument which can detect hyperhidrosis during homeostasis as well as in pathological condition. The device injects a sinusoid electric current and detects the ensuing voltage, which is proportional to the impedance of sweat on top of the skin during hyperhidrosis. For this prototype, the electrode system is made of brass rings mounted on a handle. The signal is then processed in electronic assembly. Processed output is transferred to a Laptop with specially made connecting wire. Computer having Sound Card Oscilloscope (Lab View based software) plots the signal and shows voltage level corresponding to sudor level. The signal output can also be displayed on a SmartPhone having software called Osciprime, requiring another specially made interface. Laboratory test results in the form of a plot of output voltage vs. impedance show accuracy of the device. The impedance results can be translated to sweat level because impedance decreases with increasing sweat during hyperhidrosis. The Sudometer was also calibrated using fixed precision resistors over its working range. Laboratory tests were carried out using an artificial skin at various sweat levels and to a yeast tissue model. Hydration of the artificial skin was quantified by weighing precision cut samples on a laboratory balance. Results from two test persons (the author and a student friend) are also included in this Master Thesis. During these experiments, the laptop computer and SmartPhone, respectively, were on internal battery to eliminate electric hazard. Any clinical device must be validated for accuracy and evaluated for safety before applying it on patients – the latter has not been done with the prototype. The author is aware of potential electrical risks, and thus the whole system was disconnected from mains 230V during measurements on himself and a student friend. The device output seems to be well correlated to sweat level although electrolytes were not taken into account. Being a palmar hyperhidrosis patient himself, the author applied the Electronic Sudometer on his palms and the results look quite promising. At different environmental temperatures, the author checked elicited sweat responses. Patient safety is always a concern for clinicians regarding new devices. For this reason, the device itself has been made battery operated, and a new version will be entirely powered from a SmartPhone

Comparative Analysis of Photoplethysmography Signal Quality from Right and Left Index Fingers

Photoplethysmography (PPG) has emerged as an increasingly attractive signal for non-invasive physiological measurements, owing to its simplicity, cost-effectiveness, and broad applicability spanning cardiovascular to respiratory systems. The burgeoning interest in PPG signal processing has facilitated its extensive incorporation in wearable devices, thus stimulating active research in this field. The present study undertakes a comprehensive evaluation to discern the optimal index finger (right or left) for PPG data acquisition and subsequent filtration, appraised through the lens of the signal-to-noise ratio (SNR) of the filtered signal. An analysis conducted on signals contaminated with white Gaussian noise unveiled that the Savitzky-Golay filter (a polynomial filter) with a window size of three outperformed other window lengths, rendering the highest SNR. Among the Infinite Impulse Response (IIR) filters compared; the Chebyshev I filter emerged as superior. Interestingly, the right index finger consistently demonstrated a higher mean SNR across filters: 0.49% for the Savitzky-Golay filters, 4.32% for the Butterworth (order 6), 7.71% for the Chebyshev I (order 10), and 4.02% for the Chebyshev II (order 4), relative to the left index finger for PPG signals perturbed by white Gaussian noise. These findings provide an insightful perspective for future research and development in wearable devices, suggesting potential superiority of the right index finger for PPG signal acquisition and filtration