Stress Recognition Using Photoplethysmogram Signal
This study proposed a novel method of stress recognition using photopletysmogram (PPG) signal. PPG devices are now widely used because it is convenient, low powered, cheap and also easy to handle due to its small size. A total of 5 subjects were involved in this study. The PPG signals were taken in resting condition using pulse oximetry. The subject then goes through a stressor test in order to record the physiological changes. The data were collected before and after the test was conducted and later extracted. These samples were then categorised using classification techniques to differentiate between normal and stress condition. Based on the experimentation results, the systolic peak value differences of normal and stress conditions are evident.Therefore, the outcome of this study suggest the reliability of implementing PPG signal for stress recognition.
Mental Health and Wellbeing in England: the Adult Psychiatric Morbidity Survey 2014
This report presents findings of a survey of mental illness and wellbeing among people aged 16 and over living in private households in England. The survey was commissioned by NHS Digital and funded by the Department of Health, and is the fourth in a series of surveys of adult mental health.
Pre-processing of ECG Signals Using Filters
The ECG signal is abruptly changing and continuous in nature. The heart disease such as paroxysmal of heart, arrhythmia diagnosing, are related with the intelligent health care decision this ECG signal need to be pre-process accurately for further action on it such as extracting the features, wavelet decomposition, distribution of QRS complexes in ECG recordings and related information such as heart rate and RR interval, classification of the signal by using various classifiers etc. Filters plays very important role in analyzing the low frequency components in ECG signal. The biomedical signals are of low frequency, the removal of power line interference and baseline wander is a very important step at the pre-processing stage of ECG. In these paper we deal with the study of Median filtering and FIR(Finite Impulse Response)filtering of ECG signals under noisy condition. Keywords— ECG, FIR filter, Median filter, Pre-processing