Photoplethysmography and its application in clinical physiological measurement

A survey on ECG analysis

In this paper, we use cross wavelet transform (XWT) for the analysis and classification of electrocardiogram (ECG) signals. The cross-correlation between two time-domain signals gives a measure of similarity between two waveforms. The application of the continuous wavelet transform to two time series and the cross examination of the two decompositions reveal localized similarities in time and frequency. Application of the XWT to a pair of data yields wavelet cross spectrum (WCS) and wavelet coherence (WCOH). The proposed algorithm analyzes ECG data utilizing XWT and explores the resulting spectral differences. A pathologically varying pattern from the normal pattern in the QT zone of the inferior leads shows the presence of inferior myocardial infarction. A normal beat ensemble is selected as the absolute normal ECG pattern template, and the coherence between various other normal and abnormal subjects is computed. The WCS and WCOH of various ECG patterns show distinguishing characteristics over two specific regions R1 and R2, where R1 is the QRS complex area and R2 is the T-wave region. The Physikalisch-Technische Bundesanstalt diagnostic ECG database is used for evaluation of the methods. A heuristically determined mathematical formula extracts the parameter(s) from the WCS and WCOH. Empirical tests establish that the parameter(s) are relevant for classification of normal and abnormal cardiac patterns. The overall accuracy, sensitivity, and specificity after combining the three leads are obtained as 97.6%, 97.3%, and 98.8%, respectively.

Application of Cross Wavelet Transform for ECG Pattern Analysis and Classification

In a world where the industry of mobile applications is continuously expanding and new health care apps and devices are created every day, it is important to take special care of the collection and treatment of users' personal health information. However, the appropriate methods to do this are not usually taken into account by apps designers and insecure applications are released. This paper presents a study of security and privacy in mHealth, focusing on three parts: a study of the existing laws regulating these aspects in the European Union and the United States, a review of the academic literature related to this topic, and a proposal of some recommendations for designers in order to create mobile health applications that satisfy the current security and privacy legislation. This paper will complement other standards and certifications about security and privacy and will suppose a quick guide for apps designers, developers and researchers.

Privacy and Security in Mobile Health Apps: A Review and Recommendations

Wearable health monitoring is an emerging technology for continuous monitoring of vital signs including the electrocardiogram (ECG). This signal is widely adopted to diagnose and assess major health risks and chronic cardiac diseases. This paper focuses on reviewing wearable ECG monitoring systems in the form of wireless, mobile and remote technologies related to older adults. Furthermore, the efficiency, user acceptability, strategies and recommendations on improving current ECG monitoring systems with an overview of the design and modelling are presented. In this paper, over 120 ECG monitoring systems were reviewed and classified into smart wearable, wireless, mobile ECG monitoring systems with related signal processing algorithms. The results of the review suggest that most research in wearable ECG monitoring systems focus on the older adults and this technology has been adopted in aged care facilitates. Moreover, it is shown that how mobile telemedicine systems have evolved and how advances in wearable wireless textile-based systems could ensure better quality of healthcare delivery. The main drawbacks of deployed ECG monitoring systems including imposed limitations on patients, short battery life, lack of user acceptability and medical professional's feedback, and lack of security and privacy of essential data have been also discussed.

A comprehensive survey of wearable and wireless ECG monitoring systems for older adults

In this paper, an Arduino-based real time wireless temperature measurement and logger system is presented Wireless transmission of the temperature data occurs via a Bluetooth link An experimental setup to achieve reliable output was prepared using LM35 temperature sensor The real time temperature information obtained was observed at MATLAB® Graphical User Interface and at mobile phones via a basic hybrid mobile application (Android, Windows, ios) designed by us Experimental result and percentage error curve endorse the reliability and feasibility of the proposed system Moreover, a Global System of Mobile (GSM) module is also used for sending alert messages to a pre-assigned mobile number when an alarm condition is achieved

Arduino based real-time wireless temperature measurement system with GSM based annunciation

A bi-phase enabled serial acquisition system for remote processing of digitized ECG

Electrocardiogram (ECG) compression for patient monitoring is a pre-requisite for efficient utilization of the communication link. Few recent works using delta encoding adopted fixed length symbols were analyzed, and we found that their bits per sample efficiency (BPS) is low, specially in low slope regions of ECG wave. For real-time tele-monitoring, this may lower the link throughput. This paper describes a real-time, lossy ECG compression algorithm based on delta encoding using variable length symbols. For this, the zonal complexity and inter-sample slope was estimated in a fixed length block of 52 samples. Each block was attributed as ‘complex’, ‘semi-complex’ and ‘plain’ by comparing the local measures with global ones, which were continuously updated. The encoder performs a dynamic bit allocation (DBA) algorithm for each block of ECG samples to optimize the BPS efficiency. The algorithms were tested on simulation platform with single lead ECG record from MIT BIH compression test data (cdb) and MIT BIH arrhythmia database (mitdb) at 10 bit quantization level, yielding an average BPS of 1.92 with cdb and 1.91 with mitbdb, and low PRD (1.87 and 2.42 respectively with cdb and mitdb).

Real-time compression of electrocardiogram using dynamic bit allocation strategy

Biomedical sensor networks find wide applications in human health monitoring. In such applications, routing strategies in the sensor nodes play a key role towards energy efficiency of the overall system. In this work, we present a new data routing scheme, which is based on residual energy in a node and equalization (named EEQ) among the neighbours to achieve enhanced average node lifetime under short range monitoring scenario. The scheme was hardware implemented using 12 number of indigenous ATmega328 based static biomedical sensor nodes (BSN) arranged in a grid matrix spread over a floor area of 564 sqm. The objective was to collect short duration electrocardiogram and photoplethysmogram signals from human subjects in a local supervisory computer placed outside the grid. Under simulation platform using 100 BSNs with first order radio model, it was found that the average node lifetime was enhanced by 17% against without EEQ evaluated over 10,000 consecutive data collection sessions. The proposed scheme can be useful for providing low cost solution in healthcare settings in developing nations like India.

An efficient data routing scheme for multi-patient monitoring in a biomedical sensor network through energy equalization strategy

This paper illustrates a low cost novel method for ECG signal acquisition, display and storage using a Graphical User Interface (GUI), which provides a user-friendly front end by using MATLAB-based toolsets. At first, analog ECG has been converted to its digital equivalent with the help of an ADC. Microcontrollers converted this data to a serial (RS232) format and transmit to the PC for serial acquisition. The developed GUI performs the acquisition for its future processing.

Rajarshi Gupta

Papers

Arduino based real-time wireless temperature measurement system with GSM based annunciation

A bi-phase enabled serial acquisition system for remote processing of digitized ECG

Real-time compression of electrocardiogram using dynamic bit allocation strategy

An efficient data routing scheme for multi-patient monitoring in a biomedical sensor network through energy equalization strategy

Development of a State-of-the-Art ECG DAS for Storing, Processing and Analysis Using MATLAB-Based GUI and Microprocessor