ECG signal play important role in diagnosis of cardiac conditions. The ECG is the graphical repre... more ECG signal play important role in diagnosis of cardiac conditions. The ECG is the graphical representation of the potential difference between two points on the body surface, versus time. Each heartbeat is a complex of distinct cardiological events, represented by distinct features in the ECG waveform. Therefore the recognition and analysis of the ECG signals is a very important task. This could be difficult, because the size and form of these signals may change eventually and can be noised. Therefore, this paper focuses on an efficient system of ECG detection and analysis using a DSP based system which would be understandable to and easily handled by both medical practitioners and common man alike. The heart sound is recorded using a DSP Processor kit(TMS320C6713) and denoised at various steps using WAVELET transform .Implementing various algorithms and methods the ECG signal is detected and analysed further. All of them were developed under Matlab, using Signal processing and Wavelet Toolboxes.
ECG signal play important role in diagnosis of cardiac conditions. The ECG is the graphical repre... more ECG signal play important role in diagnosis of cardiac conditions. The ECG is the graphical representation of the potential difference between two points on the body surface, versus time. Each heartbeat is a complex of distinct cardiological events, represented by distinct features in the ECG waveform. Therefore the recognition and analysis of the ECG signals is a very important task. This could be difficult, because the size and form of these signals may change eventually and can be noised. Therefore, this paper focuses on an efficient system of ECG detection and analysis using a DSP based system which would be understandable to and easily handled by both medical practitioners and common man alike. The heart sound is recorded using a DSP Processor kit(TMS320C6713) and denoised at various steps using WAVELET transform .Implementing various algorithms and methods the ECG signal is detected and analysed further. All of them were developed under Matlab, using Signal processing and Wavelet Toolboxes.
ECG signal play important role in diagnosis of cardiac conditions. The ECG is the graphical repre... more ECG signal play important role in diagnosis of cardiac conditions. The ECG is the graphical representation of the potential difference between two points on the body surface, versus time. Each heartbeat is a complex of distinct cardiological events, represented by distinct features in the ECG waveform. Therefore the recognition and analysis of the ECG signals is a very important task. This could be difficult, because the size and form of these signals may change eventually and can be noised. Therefore, this paper focuses on an efficient system of ECG detection and analysis using a DSP based system which would be understandable to and easily handled by both medical practitioners and common man alike. The heart sound is recorded using a DSP Processor kit and denoised at various steps using WAVELET transform .Implementing various algorithms and methods the ECG signal is detected and analysed further. All of them were developed under Matlab, using Signal processing and Wavelet Toolboxes.
With the advancement of web technology and its growth, there is a huge volume of data present in ... more With the advancement of web technology and its growth, there is a huge volume of data present in the web for internet users and a lot of data is generated too. Social networking sites like Twitter, Facebook are rapidly gaining popularity as they allow people to share and express their views about topics, have discussion with different communities, or post messages across the world. In this paper, we investigate the linguistic feature for detecting the sentiment of twitter message related to a geolocation.The tweets has been downloaded via Twitter Streaming API (location based approach) and filter by geo-locations (coordinate of a city) and location indicative words (LIWs) via feature selection. In this paper, we describe a method for geo-spatial tweets detection on Social Media streams. We monitor all posts on Twitter issued in a given geographic region and then analyzed the sentiment of the tweets. A novel approach is adopted for automatically classifying the sentiment of Twitter messages. Therefore, in this paper we focus on sentiment polarity analysis .This is useful for consumers who want to research the sentiment of products before purchase, or companies that want to monitor the public sentiment of their brands in a region. Only geo-location specific data has been collected from Twitter to predict sentiment of the people related to that geo-location.
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