http://localhost:8080/xmlui/handle/123456789/3362 2026-06-23T06:32:43Z 2026-06-23T06:32:43Z Shinde, Santosh RajaRajeswari, Pothuraju http://localhost:8080/xmlui/handle/123456789/3432 2022-08-27T07:43:22Z 2021-07-05T00:00:00Z

Title: Cuff-Less BP Stratification based on Bio-Signals processing using Machine Learning : An Investigative Study Authors: Shinde, Santosh; RajaRajeswari, Pothuraju Abstract: Cuff-Less Blood Pressure Stratification using Signal Processing with Machine Learning has gained immense attraction in the past decade among the research community. Blood Pressure, one of the most vital parameter of the human body representing overall well being of an individual. Most of the cardiovascular and cerebrovascular diseases (CCVD) including Hypertension are highly correlated to Blood Pressure. Existing BP measurement approaches are highly inconvenient and intermittent and do not allow continuous measurement of BP. Continuous BP measurement could prove to be significant indicator to most of the medicinal conditions and will lead to breakthrough achievement in the field of medical science. Cuff-Less Blood Pressure estimation hopefully can enable continuous blood pressure measurements in the time to come. A Plethora of methods for Cuff-Less BP Stratification have been experimented out by using Vital Bio Signals such PTT based, nPTT based, Machine Learning and Deep Learning based. Most of these methods leading to satisfactory beliefs that Cuff-Less BP estimation could be possible to the utmost accuracy for the diagnosis of most of the CCVD diseases as well as to monitor the overall well being of humans. However, most of the approaches still needs improvements, needs to be tested on a larger population with varying demographic features and real time application. This paper presents an investigative study of existing Cuff-Less BP Estimation approaches and discusses the merits and opportunities for improvements of the Cuff-Less BP Estimation methods.

2021-07-05T00:00:00Z Shinde, Santosh RajaRajeswari, Pothuraju http://localhost:8080/xmlui/handle/123456789/3431 2022-08-27T04:47:50Z 2021-07-05T00:00:00Z

Title: Time Line Correlative Spectral Processing for Stratification of Blood Pressure using Adaptive Signal Conditioning Authors: Shinde, Santosh; RajaRajeswari, Pothuraju Abstract: —Stratification of Blood Pressure is essential input in most of the cardiovascular diseases detection and prediction and is also a great aid to medical practitioners in dealing with Hypertension. Denoising based on spectral coding is developed based on frequency spectral decomposition and a spectral correlative approach based on wavelet transform. The existing approaches perform a standard deviation and mean of peak correlation in signal conditioning. The artifact filtrations were developed based on thresholding. Filtration of coefficients has an impact on accuracy of estimation and hence proper signal conditioning is a primal need. Wherein threshold is measured with discrete monitoring, time line observation could improve the accuracy of filtration efficiency under varying interference condition. Dynamic interference due to capturing or processing source results in jitter type noises which are short period deviations with varying frequency component. Hence a time frequency analysis for filtration is adapted for filtration. This paper presents an approach of spectral correlation approach for signal condition in stratification of blood pressure under cuff less monitoring. This presented approach operates on the spectral distribution of finer resolution bands for monitoring signal in denoising and decision making. Existing approaches lacks the capability of loss-less denoising which is efficiently worked out in this paper.

2021-07-05T00:00:00Z Priyadarshini, I Rathi, Anjali Patil, Trupti http://localhost:8080/xmlui/handle/123456789/3383 2022-08-05T09:50:15Z 2022-04-04T00:00:00Z

Title: Visulgorithm: Easy Conceptualization of Data Structures and Algorithms Authors: Priyadarshini, I; Rathi, Anjali; Patil, Trupti Abstract: There are various Data Structure Algorithms that we use to find solutions to standard problems and to obtain an insight into how efficient it is to use each one of them. However, these algorithms can be complex and difficult to understand, differentiate and select an efficient algorithm. As a solution to this, visualizing these algorithms will aid in understanding them. The working of various algorithms like path finding algorithms, tree based algorithms, sorting algorithms and searching algorithms can be demonstrated using examples to understand what happens at each stage in the processing of the algorithm. This system is very useful for Educational purposes to demonstrate while teaching and can also be used by researchers and coders to find the best algorithm to solve their problems. In recent time path finding algorithms are also used by Space rovers to navigate on foreign planets, they can be visualized to select the best path. The System uses Express Framework (Node JS), HTML, CSS, JavaScript and JQuery to create attractive visual animations which make the visualization more attractive and easy to understand.

2022-04-04T00:00:00Z Shahare, Aditya Sharma, Sneha Sonawane, Ranjeet Wadhavane, Poorva Mahajan, Monali http://localhost:8080/xmlui/handle/123456789/3382 2022-08-05T07:59:16Z 2022-05-20T00:00:00Z

Title: QUALITY CHECK USING IMAGE PROCESSING Authors: Shahare, Aditya; Sharma, Sneha; Sonawane, Ranjeet; Wadhavane, Poorva; Mahajan, Monali Abstract: : In traditional ways of quality control of hardware steel products (regular rectangular shape), the industrial experts use Vernier Caliper for error checking. Usually, this is done manually which takes a lot of time and cost, and this might have some error while checking. To avoid this problem, there should be an automated system which will not require any man power and perform this task fast as well as accurately. The proposed system will allow users to make accurate non-contact measurement detect a fault in product’s shape and dimensions. The proposed system will measure dimension of hardware steel products. An image of the product captured from the specified height will be used to measure the dimension. The proposed system will use image segmentation, area detection and then size measurement. The dimensions obtain from the process is compared with the expected dimensions. Based on this, if the obtained dimensions and expected dimensions match, the product will be classified as correct else fault. The proposed system aims for fault detection process which will detect faults quickly and precisely.

2022-05-20T00:00:00Z