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A COST EFFECTIVE REAL TIME IMPLEMENTATION OF SMART BRACELET USING MEMS ACCELEROMETER FOR MONITORING PHYSIOLOGICAL ACTIVITY OF STAY-ALONE ELDERLY PERSONS

2015-03-01T00:00:00Z

Title: A COST EFFECTIVE REAL TIME IMPLEMENTATION OF SMART BRACELET USING MEMS ACCELEROMETER FOR MONITORING PHYSIOLOGICAL ACTIVITY OF STAY-ALONE ELDERLY PERSONS Authors: Chattopadhyay, Madhurima Abstract: This paper deals with a development of cost effective portable system for determination of basic physiological movements using wearable MEMS tri-axial accelerometer in elderly impaired patents. In this application model, we have derived a simple algorithm without the help of any trained classifier for identifying three most vital physiological states of human being like resting, walking and running. Once the data is fetched from the accelerometer, the maximum frequency component is extracted by performing 27 -point Fast Fourier Transform (FFT). In order to recognize the state, a microcontroller based application is loaded inside the wearable system which compares the fed data with three distinct range of frequencies to classify the current physiological state of the person wearing it. The algorithm is defined in such a way that it can easily calculate the pedometer information provided the subject is in unrest condition. The wearable device applies six-point based sensor data calibration to eliminate discrepancies in senor output due to zero-G and installation errors. Thus, accelerometer based activity detection not only reduces the hardware complexity but also proves cost effective as it has minimized power consumption (<13.5mW) by associated circuitry covering small size (3.9mm*4.0mm*4.1mm) that enables mobility.

A Novel Technique of Black Tea Quality Prediction Using Electronic Tongue Signals

2014-10-01T00:00:00Z

Title: A Novel Technique of Black Tea Quality Prediction Using Electronic Tongue Signals Authors: Saha, Pradip; Ghorai, Santanu; Tudu, Bipan; Bandyopadhyay, Rajib; Bhattacharyya, Nabarun Abstract: Electronic tongue (ET) system is under extensive development for automatic analysis and prediction of quality of different industrial end products. Each sensor in an ET system generates a specific electronic response in presence of different organic or inorganic compounds in the sample. The vital part of the ET system is the discrimination of the complex pattern generated by the sensor array. In this paper, a novel technique of black tea quality estimation is using the ET signals. A moving window is used to extract discrete wavelet transform coefficients from the transient response of ET. The energy in different frequency bands are used as the features of the ET signal for different positions of the window. The prediction of a new sample is performed by the highest score obtained by a particular class by testing all the patterns generated by windowing ET signal. The performance of the proposed technique is verified to estimate black tea quality using two kernel classifiers, namely support vector machine and recently proposed vector valued regularized kernel function approximation method. High prediction accuracy of both the classifiers confirms the effectiveness of the proposed technique of tea quality estimation using ET signals.

Real Time Design and Implementation of Brushless DC Motor Drive based Continuous Positive Airway Pressure (CPAP) based Respirator System for Patients with Chronic Obstructive Pulmonary Diseases (COPD)

2015-01-01T00:00:00Z

Title: Real Time Design and Implementation of Brushless DC Motor Drive based Continuous Positive Airway Pressure (CPAP) based Respirator System for Patients with Chronic Obstructive Pulmonary Diseases (COPD) Authors: Mitra, Arunava; Chowdhury, Debjyoti; Chattopadhyay, Madhurima Abstract: This paper aims at designing a cost-effective, portable and easy-to-use brushless DC (BLDC) motor driven continuous positive airway pressure (CPAP) based respirator for patients with acute breathing trouble. The proposed system is intended to facilitate continuous monitoring of patient's condition with positive airway support provided by a brushless DC (BLDC) motor driven respirator blower fan by measuring Respiration Rate (RR). To measure the respiration rate, a pair of capacitive type respiration rate sensors are mounted below Right Nostril (RN) and Left Nostril (LN), in such a way that the nasal airflow during inspiration and expiration impinge on the sensor diaphragms directly. Due to irregularities in nasal airflow in some respiratory diseases, the respiration rate (RR) varies from the normal rate (12-20). Thus, a supporting airflow regulatory system has been designed to reduce abnormalities in respiration rate (RR). In this case a low cost sensorless commutated BLDC drive is implemented with a three phase inverter and microcontroller by using feedback of rotor rpm. A suitable cost effective algorithm has also been developed to generate an appropriate six transistor switching sequence to commute the BLDC motor according to the RR of the subject. The characteristics of the implemented drive give satisfactory outputs over a wide range of controlled speed variation from 200 to 2440 rpm which requires a match with the patient’s breathing demand. The effectiveness of the designed system is populated by the real time experimental results.

Design of Self-Tuning Fuzzy PI controller in LABVIEW for Control of a Real Time Process

2013-01-01T00:00:00Z

Title: Design of Self-Tuning Fuzzy PI controller in LABVIEW for Control of a Real Time Process Authors: Pal, A.K.; Naskar, I Abstract: Pressure control systems constitute the heart of many process plants. Linguistic modeling and decisionmaking processes like fuzzy and neural controller are very much useful to control the complicated processes. An intelligent control strategy has been proposed and successfully applied to a real time water pressure control system. For the variation of set point change and load disturbance, an intelligent control scheme has been developed by integrating self-tuning scheme with fuzzy PI controller. Satisfactory industrial application results show that such a control scheme has enhanced adaptability and robustness to the complex processes. To demonstrate the performance of the self-tuning fuzzy PI controller (STFPIC), results are compared with a fuzzy PI controller (FPIC). It is observed that the proposed controller structure is able to quickly track the parameter variation and perform better in load disturbances and also for set point changes.