Smartphone transmission of electrocardiography images to reduce time of cardiac catheterization laboratory activation

Background

This retrospective study evaluated the use of a smartphone application to facilitate communication between the emergency physician (EP) and the interventional cardiologist in order to minimize the time to cardiac catheterization laboratory (CCL) activation and time to percutaneous coronary intervention (PCI).

Variable Threshold Method for ECG R-peak Detection

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.     

Cooperative wireless network control based health and activity monitoring system

A real-time cooperative communication based wireless network is presented for monitoring health and activity of an end-user in their environment. The cooperative communication offers better energy consumption and also an opportunity to aware the current location of a user non-intrusively. The link between mobile sensor node and relay node is dynamically established by using Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI) based on adaptive relay selection scheme. The study proposes a Linear Acceleration based Transmission Power Decision Control (LA-TPDC) algorithm to further enhance the energy efficiency of cooperative communication. Further, the occurrences of false alarms are carefully prevented by introducing three stages of sequential warning system. The real-time experiments are carried-out by using the nodes, namely mobile sensor node, relay nodes and a destination node which are indigenously developed by using a CC430 microcontroller integrated with an in-built transceiver at 868 MHz. The wireless node performance characteristics, such as energy consumption, Signal-Noise ratio (SNR), Bit Error Rate (BER), Packet Delivery Ratio (PDR) and transmission offset are evaluated for all the participated nodes. The experimental results observed that the proposed linear acceleration based transmission power decision control algorithm almost doubles the battery life time than energy efficient conventional cooperative communication.     

An Integrated Approach Using Chaotic Map & Sample Value Difference Method for Electrocardiogram Steganography and OFDM Based Secured Patient Information Transmission

This paper presents a patient’s confidential data hiding scheme in electrocardiogram (ECG) signal and its subsequent wireless transmission. Patient’s confidential data is embedded in ECG (called stego-ECG) using chaotic map and the sample value difference approach. The sample value difference approach effectually hides the patient’s confidential data in ECG sample pairs at the predefined locations. The chaotic map generates these predefined locations through the use of selective control parameters. Subsequently, the wireless transmission of the stego-ECG is analyzed using the Orthogonal Frequency Division Multiplexing (OFDM) system in a Rayleigh fading scenario for telemedicine applications. Evaluation of proposed method on all 48 records of MIT-BIH arrhythmia ECG database demonstrates that the embedding does not alter the diagnostic features of cover ECG. The secret data imperceptibility in stego-ECG is evident through the statistical and clinical performance measures. Statistical measures comprise of Percentage Root-mean-square Difference (PRD), Peak Signal to Noise Ratio (PSNR), and Kulback-Leibler Divergence (KL-Div), etc. while clinical metrics includes wavelet Energy Based Diagnostic Distortion (WEDD) and Wavelet based Weighted PRD (WWPRD). The various channel Signal-to-Noise Ratio scenarios are simulated for wireless communication of stego-ECG in OFDM system. The proposed method over all the 48 records of MIT-BIH arrhythmia database resulted in average, PRD = 0.26, PSNR = 55.49, KL-Div = 3.34 × 10^?6, WEDD = 0.02, and WWPRD = 0.10 with secret data size of 21Kb. Further, a comparative analysis of proposed method and recent existing works was also performed. The results clearly, demonstrated the superiority of proposed method.     

Towards Improved Healthcare Performance: Examining Technological Possibilities and Patient Satisfaction with Wireless Body Area Networks

This paper investigates the benefits of using less intrusive wireless technologies for heart monitoring. By replacing well established heart monitoring devices (i.e. Holter) with wireless ECG based Body Area Networks (BAN), improved healthcare performance can be achieved, reflected in (1) high quality ECG recordings during physical activities and (2) increased patient satisfaction. A small scale clinical trial was conducted to compare both technologies and the results illustrate that the wireless ECG monitor was able to detect ECG signals intended for arrhythmia diagnostics. Furthermore, from a patient’s perspective, both technologies were evaluated using three dimensions, namely; hygienic aspects, physical activity, and skin reactions. Results demonstrate that the wireless ECG BAN showed better performance, especially regarding the hygienic aspects. It was also favourable for use during physical activities, and the signal quality of the wireless sensor system demonstrated good performance regarding signal noise and artefact disturbances. This paper concludes that wireless cardiac monitoring systems have significant benefits from a patient’s perspective, and further clinical trials should be conducted to further evaluate the new ECG based BAN system, to identify the possibility of widespread adoption and utilisation of wireless technology for arrhythmia diagnostics.     

Wireless Electrocardiogram Transmission in ISM Band: An Approach Towards Telecardiology

Remote monitoring of biomedical signals provides an opportunity to extend health care service to a distant patient. In this paper, a short range wireless telecardiology system is described with the objective to transmit electrocardiogram signal for remote end acquisition. The acquired signal was compressed using a combination of modified delta encoding and run length encoding technique and transmitted using a wireless transceiver operating in 2.4 GHz industrial, scientific and medical band to a distance of 400 ft. In the receiving end, error check principle was used to find any data loss before the data is reconstructed for feature extraction. With Physionet data using 8-bit quantization an average compression ratio (CR) of 12.23, percentage root mean squared difference (PRD) of 4.342 and PRD normalized (PRDN) of 9.271 were obtained. With ECG data collected from healthy volunteers, these figures came out to be 14.64, 12.92 and 13.46 respectively. An improvement of performance was observed with 10 bit quantization of ECG data. Computational simplicity of the proposed algorithm provides an opportunity to use a low end microcontroller to implement the compression in standalone hardware.     

A Pulse Rate Estimation Algorithm Using PPG and Smartphone Camera

The ubiquitous use and advancement in built-in smartphone sensors and the development in big data processing have been beneficial in several fields including healthcare. Among the basic vitals monitoring, pulse rate monitoring is the most important healthcare necessity. A multimedia video stream data acquired by built-in smartphone camera can be used to estimate it. In this paper, an algorithm that uses only smartphone camera as a sensor to estimate pulse rate using PhotoPlethysmograph (PPG) signals is proposed. The results obtained by the proposed algorithm are compared with the actual pulse rate and the maximum error found is 3 beats per minute. The standard deviation in percentage error and percentage accuracy is found to be 0.68 % whereas the average percentage error and percentage accuracy is found to be 1.98 % and 98.02 % respectively.     

DOCSS: doctors on-call smartphone study

Introduction

Smartphones have revolutionised our demands for constant access to information. The usage of smartphones in the clinical setting is becoming widespread. The aim of our study was to assess smartphone ownership and usage across a cohort of interns.

Methods

A voluntary novel questionnaire was distributed to interns in two university hospitals. Details regarding smartphone ownership and usage were assessed. Likert scales were utilised for analysis.

Results

Sixty-one (74.4 %) interns responded to the survey. Sixty (98.4 %) owned a smartphone with iPhone^® being the most popular (76.7 %). Fifty-five (91.6 %) interns have downloaded medical applications (‘apps’), while 29 (52.3 %) reported paying for them. Regarding smartphone use on-call, 30 (50 %) interns agreed it aids diagnoses, 26 (43 %) agree it helped in interpreting laboratory values, 31 (51.7 %) agreed it helped in dosing of medication and 33 (55 %) agreed it was of assistance in medical emergency protocols. Forty-two (70 %), 42 (70 %) and 46 (76.7 %) interns agreed or strongly agreed smartphones have a positive influence on them in terms of levels of stress, confidence and level of knowledge, respectively.

Conclusion

Smartphone usage is widespread among our intern cohort. The introduction of hospital applications with local guidelines would be welcomed; however, this may require informed patient consent regarding their use.     

Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis

The non-stationary and multi-frequency nature of biomedical signal activities makes the use of time-frequency distributions (TFDs) for analysis inevitable. Time-frequency analysis provides simultaneous interpretations in both time and frequency domain enabling comprehensive explanation, presentation and interpretation of electrocardiogram (ECG) signals. The diversity of TFDs and specific properties for each type show the need to determine the best TFD for ECG analysis. In this study, a performance evaluation of five TFDs in term of ECG abnormality detection is presented. The detection criteria based on extracted features from most important ECG signal components (QRS) to detect normal and abnormal cases. This is achieved by estimating its energy concentration magnitude using the TFDs. The TFDs analyse ECG signals in one-minute interval instead of conventional time domain approach that analyses based on beat or frame containing several beats. The MIT-BIH normal sinus rhythm ECG database total records of 18 long-term ECG sampled at 128 Hz have been analysed. The tested TFDs include Dual-Tree Wavelet Transform, Spectrogram, Pseudo Wigner-Ville, Choi-Williams, and Born-Jordan. Each record is divided into one-minute slots, which is not considered previously, and analysed. The sample periods (slots) are randomly selected ten minutes interval for each record. This result with 99.44% detection accuracy for 15,735 ECG beats shows that Choi-Williams distribution is most reliable to be used for heart problem detection especially in automated systems that provide continuous monitoring for long time duration.     

网络化多参数体征监测仪的设计

目的：设计一种基于无线传感网络的多参数体征监测仪,取代传统有线式数据传输,提高便携式心电监测仪的适应能力。方法系统采用Zigbee无线传感技术,对人体心电、血氧饱和度、无创血压等生命体征参数进行动态监测,并通过小波变换对心电监测算法进行改进,提高心电监测的分辨率和精准度。结果实现了各种医疗监测模块的即插即用功能,以及特征监测数据的网络化传输。结论网络化心电检测仪结构简单、精度高、系统功耗低。     

Wireless Body Sensor Network Using Medical Implant Band

A wireless body sensor network hardware has been designed and implemented based on MICS (Medical Implant Communication Service) band. The MICS band offers the advantage of miniaturized electronic devices that can either be used as an implanted node or as an external node. In this work, the prototype system uses temperature and pulse rate sensors on nodes. The sensor node can transmit data over the air to a remote central control unit (CCU) for further processing, monitoring and storage. The developed system offers medical staff to obtain patient’s physiological data on demand basis via the Internet. Some preliminary performance data is presented in the paper.     

Tubular stomach or whole stomach for esophagectomy through cervico-thoraco-abdominal approach: a comparative clinical study on anastomotic leakage

Background

Esophagectomy through cervico-thoraco-abdominal approach is a useful surgical technique in treating patients with esophageal cancer. However, the cervical reconstruction is also known to have a high rate of anastomotic leakage, as well as anastomotic stricture, intrathoracic stomach syndrome, reflux esophagitis and other complications, thereby influencing postoperative recovery and quality of life.

Aims

The objective of this study was to investigate whether tubular stomach is superior to whole stomach in reducing anastomotic leakage for esophageal reconstruction through the cervico-thoraco-abdominal (3-field) approach.

Methods

A total of 850 patients undergoing the 3-field esophagectomy were retrospectively included in this study and divided into a tubular stomach reconstruction group (Group A, n = 453) and a whole stomach reconstruction group (Group B, n = 397). All patients underwent esophagectomy through right thorax, left cervical part, abdominal triple incisions and done in esophageal reconstruction by hand-sewn two-layer anastomosis.

Results

Results revealed that in comparison with whole stomach, esophageal reconstruction with tubular stomach had a lower incidence of anastomotic leakage (5.5 vs. 9.3 %, P < 0.05), less manifestation of intrathoracic syndrome (3.3 vs. 9.8 %, P < 0.001) and less occurence of reflux esophagitis (5.1 vs. 11.1 %, P < 0.01). However, for the incidence of anastomotic stricture, there was no significant difference between the two groups (9.3 vs. 9.8 %).

Conclusions

This observation study suggests that for esophageal cancer patients undergoing the 3-field esophagectomy tubular stomach is better than whole stomach for esophageal reconstruction as reflected by a reduced postoperative anastomotic leakage, intrathoracic syndrome and reflux esophagitis.     

Quality Aware Compression of Electrocardiogram Using Principal Component Analysis

Electrocardiogram (ECG) compression finds wide application in various patient monitoring purposes. Quality control in ECG compression ensures reconstruction quality and its clinical acceptance for diagnostic decision making. In this paper, a quality aware compression method of single lead ECG is described using principal component analysis (PCA). After pre-processing, beat extraction and PCA decomposition, two independent quality criteria, namely, bit rate control (BRC) or error control (EC) criteria were set to select optimal principal components, eigenvectors and their quantization level to achieve desired bit rate or error measure. The selected principal components and eigenvectors were finally compressed using a modified delta and Huffman encoder. The algorithms were validated with 32 sets of MIT Arrhythmia data and 60 normal and 30 sets of diagnostic ECG data from PTB Diagnostic ECG data ptbdb, all at 1 kHz sampling. For BRC with a CR threshold of 40, an average Compression Ratio (CR), percentage root mean squared difference normalized (PRDN) and maximum absolute error (MAE) of 50.74, 16.22 and 0.243 mV respectively were obtained. For EC with an upper limit of 5 % PRDN and 0.1 mV MAE, the average CR, PRDN and MAE of 9.48, 4.13 and 0.049 mV respectively were obtained. For mitdb data 117, the reconstruction quality could be preserved up to CR of 68.96 by extending the BRC threshold. The proposed method yields better results than recently published works on quality controlled ECG compression.     

Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier

In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in diagnosis of heart arrhythmia. Discrete wavelet transform (DWT) is used to decompose ECG signals into different successive frequency bands. A set of different statistical features were extracted from the obtained frequency bands to denote the distribution of wavelet coefficients. This study shows that RF classifier achieves superior performances compared to other decision tree methods using 10-fold cross-validation for the ECG datasets and the obtained results suggest that further significant improvements in terms of classification accuracy can be accomplished by the proposed classification system. Accurate ECG signal classification is the major requirement for detection of all arrhythmia types. Performances of the proposed system have been evaluated on two different databases, namely MIT-BIH database and St. -Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database. For MIT-BIH database, RF classifier yielded an overall accuracy 99.33 % against 98.44 and 98.67 % for the C4.5 and CART classifiers, respectively. For St. -Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database, RF classifier yielded an overall accuracy 99.95 % against 99.80 % for both C4.5 and CART classifiers, respectively. The combined model with multiscale principal component analysis (MSPCA) de-noising, discrete wavelet transform (DWT) and RF classifier also achieves better performance with the area under the receiver operating characteristic (ROC) curve (AUC) and F-measure equal to 0.999 and 0.993 for MIT-BIH database and 1 and 0.999 for and St. -Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database, respectively. Obtained results demonstrate that the proposed system has capacity for reliable classification of ECG signals, and to assist the clinicians for making an accurate diagnosis of cardiovascular disorders (CVDs).     

无线传感器网络在医疗领域的应用

讨论了无线传感器网络的节点组成、网络体系和协议栈模型，给出了一个远程医疗监护网络体系结构，并对无线传感器网络在医疗应用的主要方面、前景和面临的挑战进行了阐述。     

Monitoring of Physiological Parameters from Multiple Patients Using Wireless Sensor Network

This paper presents a wireless sensor network system that has the capability to monitor physiological parameters from multiple patient bodies. The system uses the Medical Implant Communication Service band between the sensor nodes and a remote central control unit (CCU) that behaves as a base station. The CCU communicates with another network standard (the internet or a mobile network) for a long distance data transfer. The proposed system offers mobility to patients and flexibility to medical staff to obtain patient’s physiological data on demand basis via Internet. A prototype sensor network including hardware, firmware and software designs has been implemented and tested. The developed system has been optimized for power consumption by having the nodes sleep when there is no communication via a bidirectional communication.     

Deep circumflex iliac artery flap with osseointegrated implants for reconstruction of mandibular benign lesions: clinical experience of 33 cases

Background

A variety of free flaps have been successfully used for mandible reconstruction. The iliac crest has similar dimensions and form to the lateral mandible. The success rate and complication rate of deep circumflex iliac artery flap transplants had no significant difference to those of other microvascular bone transplants.

Aims

The purpose of this study was to evaluate our experience with the use of the vascularized free iliac flap for the reconstruction of mandibular defects following surgical resection.

Methods

Data from 33 patients who underwent operations, including segmental mandibulectomy, immediate mandibular reconstruction and second-stage surgery, were retrospectively analysed. The size of segmental mandible defects ranged from 6 to 13 cm. Surgicase for cranio-maxillofacial reconstruction software was used for patients with mandible defects greater than 10 cm.

Results

One flap loss occurred related to vascular thrombosis. The survival rate was 96.97 %, and the mean follow-up was 26 months. A total of 81 osseointegrated dental implants were placed in 25 patients with adequate outcomes; 21 patients (63.64 %) showed complete recovery, and in 18 out of these 21 patients, occlusion rehabilitation with fixed dentures benefitted from an appropriate distance between upper teeth and new alveolar bone. Donor-site morbidity was moderate, and most of the patients were satisfied with their functional and aesthetic results.

Conclusions

Our results show that deep circumflex iliac artery is a reliable method for reconstructing hemimandibular body defects with an acceptably low rate of morbidity. The iliac crest is a safe foundation for the placement of osseointegrated implants, which enable good reconstruction and further improve life quality of patients.     

BRAINsens: Body-Worn Reconfigurable Architecture of Integrated Network Sensors

Body sensor network (BSN) is a promising human–centric technology to monitor neurophysiological data. We propose a fully-reconfigurable architecture that addresses the major challenges of a heterogenous BSN, such as scalabiliy, modularity and flexibility in deployment. Existing BSNs especially with Electroencephalogarm (EEG) have these limitations mainly due to the use of driven-right-leg (DRL) circuit. We address these limitations by custom-designing DRL-less EEG smart sensing nodes (SSN) for modular and spatially distributed systems. Each single-channel EEG SSN with a input-referred noise of 0.82 μV_rms and CMRR of 70 dB (at 60 Hz), samples brain signals at 512 sps. SSNs in the network can be configured at the time of deployment and can process information locally to significantly reduce data payload of the network. A Control Command Node (CCN) initializes, synchronizes, periodically scans for the available SSNs in the network, aggregates their data and sends it wirelessly to a paired device at a baud rate of 115.2 kbps. At the given settings of the I²C bus speed of 100 kbps, CCN can configure up to 39 EEG SSNs in a lego-like platform. The temporal and frequency-domain performance of the designed “DRL-less” EEG SSNs is evaluated against a research-grade Neuroscan and consumer-grade Emotiv EPOC EEG. The results show that the proposed network system with wearable EEG can be deployed in situ for continuous brain signal recording in real-life scenarios. The proposed system can also seamlessly incorporate other physiological SSNs for ECG, HRV, temperature etc. along with EEG within the same topology.     

移动医疗对心电信息系统的优化

随着移动医疗的成熟,在信息化飞速发展的同时,移动医疗能为信息化带来很好的优化。使用平板电脑及无线网络在床边心电及远程心电的移动心电检查系统优化了心电检查流程,提高了检查效率,同时居家心电诊疗方便居民获得优质、高效、便捷的医疗卫生服务。     

基于无线的心电采集与传送系统设计

利用nRF401无线收发芯片设计一个心电信号的前端采集与传送系统。该系统可以嵌入心电监护系统中，实现信号采集系统与信号处理系统分离，增强设备应用的灵活性。