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Efficient QRS complex detection algorithm based on Fast Fourier Transform

Ashish KUMAR ; Ramana RANGANATHAM ; Rama KOMARAGIRI ; Manjeet KUMAR

Biomedical Engineering Letters.2019;9(1):145-151. doi:10.1007/s13534-018-0087-y

An ECG signal, generally filled with noise, when de-noised, enables a physician to effectively determine and predict the condition and health of the heart. This paper aims to address the issue of denoising a noisy ECG signal using the Fast Fourier Transform based bandpass filter. Multi-stage adaptive peak detection is then applied to identify the R-peak in the QRS complex of the ECG signal. The result of test simulations using the MIT/BIH Arrhythmia database shows high sensitivity and positive predictivity (PP) of 99.98 and 99.96% respectively, confirming the accuracy and reliability of proposed algorithm for detecting R-peaks in the ECG signal.
Arrhythmias, Cardiac ; Electrocardiography ; Fourier Analysis ; Heart ; Noise

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Adaptive smith predictor controller for total intravenous anesthesia automation

Bhavina PATEL ; Hiren PATEL ; Pragna VACHHRAJANI ; Divyang SHAH ; Alpesh SARVAIA

Biomedical Engineering Letters.2019;9(1):127-144. doi:10.1007/s13534-018-0090-3

Anesthetic agent propofol needs to be administered at an appropriate rate to prevent hypotension and postoperative adverse reactions. To comprehend more suitable anesthetic drug rate during surgery is a crucial aspect. The main objective of this proposal is to design robust automated control system that work effi ciently in most of the patients with smooth BIS and minimum variations of propofol during surgery to avoid adverse post reactions and instability of anesthetic parameters. And also, to design advanced computer control system that improves the health of patient with short recovery time and less clinical expenditures. Unlike existing research work, this system administrates propofol as a hypnotic drug to regulate BIS, with fast bolus infusion in induction phase and slow continuous infusion in maintenance phase of anesthesia. The novelty of the paper lies in possibility to simplify the drug sensitivity-based adaption with infusion delay approach to achieve closedloop control of hypnosis during surgery. Proposed work uses a brain concentration as a feedback signal in place of the BIS signal. Regression model based estimated sensitivity parameters are used for adaption to avoid BIS signal based frequent adaption procedure and large off set error. Adaptive smith predictor with lead–lag fi lter approach is applied on 22 diff erent patients' model identifi ed by actual clinical data. The actual BIS and propofol infusion signals recorded during clinical trials were used to estimate patient's sensitivity parameters EC50 and λ. Simulation results indicate that patient's drug sensitivity parameters based adaptive strategy facilitates optimal controller performance in most of the patients. Results are obtained with proposed scheme having less settling time, BIS oscillations and small off set error leads to adequate depth of anesthesia. A comparison with manual control mode and previously reported system shows that proposed system achieves reduction in the total variations of the propofol dose. Proposed adaptive scheme provides better performance with less oscillation in spite of computation delay, surgical stimulations and patient variability. Proposed scheme also provides improvement in robustness and may be suitable for clinical practices.
Anesthesia ; Anesthesia, Intravenous ; Automation ; Brain ; Health Expenditures ; Humans ; Hypnosis ; Hypotension ; Propofol

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A universal ultrasound diagnostic system developed to support urology and coloproctological applications

Jeong Seok KIM ; Jong Gun LEE ; Jae Hyeok CHOI ; Bong Hyo HAN ; Se Leang YOON ; Ho JUNG ; Tai Kyong SONG ; Jae Young LEE

Biomedical Engineering Letters.2019;9(1):119-125. doi:10.1007/s13534-018-0088-x

In this study, we sought to describe a novel imaging apparatus that is lightweight, inexpensive, and highly eff ective for use in colorectal diagnostic and treatment settings. Typical probes for use in colorectal ultrasonic imaging applications are developed for surgeons to diagnose and stage rectal tumors and image the rectum and anus. Here we outline a new technique and use it for colorectal imaging in an animal. This technique involves use of an ultrasound array module positioned along the axis of rotation such that improved rotation is possible. This module is in the shape of a linear rod with a rotary linear component that allows for emission of focused ultrasonic echo signals from a linear section of the probe. The usability of the transducer and rectal image quality are satisfactory in a porcine model with the technique proposed here, axial/lateral resolution as 0.96/2.24 mm with 6 dB applied through the contour map using the point spread function. When compared to currently available methods, this technique provides superior diagnostic 3D volumetric image quality with reduced acquisition time. Given this, the ultrasound device proposed here may prove a viable and preferable method to those currently available for urology and colorectal imaging applications.
Anal Canal ; Animals ; Methods ; Rectal Neoplasms ; Rectum ; Surgeons ; Transducers ; Ultrasonics ; Ultrasonography ; Urology

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Segmentation of lung fields from chest radiographs-a radiomic feature-based approach

Rahul HOODA ; Ajay MITTAL ; Sanjeev SOFAT

Biomedical Engineering Letters.2019;9(1):109-117. doi:10.1007/s13534-018-0086-z

Precisely segmented lung fields restrict the region-of-interest from which radiological patterns are searched, and is thus an indispensable prerequisite step in any chest radiographic CADx system. Recently, a number of deep learning-based approaches have been proposed to implement this step. However, deep learning has its own limitations and cannot be used in resource-constrained settings. Medical systems generally have limited RAM, computational power, storage, and no GPUs. They are thus not always suited for running deep learning-based models. Shallow learning-based models with appropriately selected features give comparable performance but with modest resources. The present paper thus proposes a shallow learning-based method that makes use of 40 radiomic features to segment lung fields from chest radiographs. A distance regularized level set evolution (DRLSE) method along with other post-processing steps are used to refine its output. The proposed method is trained and tested using publicly available JSRT dataset. The testing results indicate that the performance of the proposed method is comparable to the state-of-the-art deep learning-based lung field segmentation (LFS) methods and better than other LFS methods.
Dataset ; Learning ; Lung ; Methods ; Radiography, Thoracic ; Running ; Thorax

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Additive manufacturing to veterinary practice: recovery of bony defects after the osteosarcoma resection in canines

Vladimir V POPOV ; Gary MULLER-KAMSKII ; Alexander KATZ-DEMYANETZ ; Aleksey KOVALEVSKY ; Stas USOV ; Dmitrii TROFIMCOW ; Georgy DZHENZHERA ; Andrey KOPTYUG

Biomedical Engineering Letters.2019;9(1):97-108. doi:10.1007/s13534-018-00092-7

The paper outlines the achievements and challenges in the additive manufacturing (AM) application to veterinary practice. The state-of-the-art in AM application to the veterinary surgery is presented, with the focus of AM for patient-specifi c implants manufacturing. It also provides critical discussion on some of the potential issues design and technology should overcome for wider and more eff ective implementation of additively manufactured parts in veterinary practices. Most of the discussions in present paper are related to the metallic implants, manufactured in this case using so-called powder bed additive manufacturing (PB-AM) in titanium alloy Ti–6AL–4V, and to the corresponding process of their design, manufacturing and implementation in veterinary surgery. Procedures of the implant design and individualization for veterinary surgery are illustrated basing on the four performed surgery cases with dog patients. Results of the replacement surgery in dogs indicate that individualized additively manufactured metallic implants signifi cantly increase chances for successful recovery process, and AM techniques present a viable alternative to amputation in a large number of veterinary cases. The same time overcoming challenges of implant individualization in veterinary practice signifi cantly contributes to the knowledge directly relevant to the modern medical practice. An experience from veterinary cases where organ-preserving surgery with 3D-printed patient-specifi c implants is performed provides a unique opportunity for future development of better human implants.
Alloys ; Amputation ; Animals ; Dogs ; Humans ; Osteosarcoma ; Surgery, Veterinary ; Titanium

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Practicality and importance of selected endothelial dysfunction measurement techniques: review

Michael D WHITT ; Mark J JACKSON

Biomedical Engineering Letters.2019;9(1):87-95. doi:10.1007/s13534-018-0089-9

The measurement of endothelial dysfunction (ED) has importance in that it indicates the presence of coronary artery disease (Kuvin et al. in J Am Coll Cardiol 38(7):1843–1849, 2001) in addition to acting as a predictor of future adverse events (Halcox et al. in Circulation 106:653–658, 2002). Various tools, methods, and metrics exist that can provide an indicator of endothelial dysfunction. Given the signifi cance of ED, it is of utmost importance to fi nd a measurement technique that is reliable, while defi ning a metric providing a framework for an overall system that is practical, accurate, and repeatable. Success would provide a tool for the early detection of cardiovascular disease not only moving patients that are currently classifi ed as asymptomatic to symptomatic, but also providing a method to monitor the effi cacy of treatments.
Cardiovascular Diseases ; Coronary Artery Disease ; Humans ; Methods

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Smart technologies toward sleep monitoring at home

Kwang Suk PARK ; Sang Ho CHOI

Biomedical Engineering Letters.2019;9(1):73-85. doi:10.1007/s13534-018-0091-2

With progress in sensors and communication technologies, the range of sleep monitoring is extending from professional clinics into our usual home environments. Information from conventional overnight polysomnographic recordings can be derived from much simpler devices and methods. The gold standard of sleep monitoring is laboratory polysomnography, which classifi es brain states based mainly on EEGs. Single-channel EEGs have been used for sleep stage scoring with accuracies of 84.9%. Actigraphy can estimate sleep effi ciency with an accuracy of 86.0%. Sleep scoring based on respiratory dynamics provides accuracies of 89.2% and 70.9% for identifying sleep stages and sleep effi ciency, respectively, and a correlation coeffi cient of 0.94 for apnea–hypopnea detection. Modulation of autonomic balance during the sleep stages are well recognized and widely used for simpler sleep scoring and sleep parameter estimation. This modulation can be recorded by several types of cardiovascular measurements, including ECG, PPG, BCG, and PAT, and the results showed accuracies up to 96.5% and 92.5% for sleep effi ciency and OSA severity detection, respectively. Instead of using recordings for the entire night, less than 5 min ECG recordings have used for sleep effi ciency and AHI estimation and resulted in high correlations of 0.94 and 0.99, respectively. These methods are based on their own models that relate sleep dynamics with a limited number of biological signals. Parameters representing sleep quality and disturbed breathing are estimated with high accuracies that are close to the results obtained by polysomnography. These unconstrained technologies, making sleep monitoring easier and simpler, will enhance qualities of life by expanding the range of ubiquitous healthcare.
Actigraphy ; Brain ; Delivery of Health Care ; Electrocardiography ; Electroencephalography ; Mycobacterium bovis ; Polysomnography ; Respiration ; Sleep Stages

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Wearable EEG and beyond

Alexander J CASSON

Biomedical Engineering Letters.2019;9(1):53-71. doi:10.1007/s13534-018-00093-6

The electroencephalogram (EEG) is a widely used non-invasive method for monitoring the brain. It is based upon placing conductive electrodes on the scalp which measure the small electrical potentials that arise outside of the head due to neuronal action within the brain. Historically this has been a large and bulky technology, restricted to the monitoring of subjects in a lab or clinic while they are stationary. Over the last decade much research eff ort has been put into the creation of “wearable EEG” which overcomes these limitations and allows the long term non-invasive recording of brain signals while people are out of the lab and moving about. This paper reviews the recent progress in this fi eld, with particular emphasis on the electrodes used to make connections to the head and the physical EEG hardware. The emergence of conformal “tattoo” type EEG electrodes is highlighted as a key next step for giving very small and socially discrete units. In addition, new recommendations for the performance validation of novel electrode technologies are given, with standards in this area seen as the current main bottleneck to the wider take up of wearable EEG. The paper concludes by considering the next steps in the creation of next generation wearable EEG units, showing that a wide range of research avenues are present.
Brain ; Electrodes ; Electroencephalography ; Head ; Methods ; Neurons ; Scalp

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Pulse transit time technique for cuffl ess unobtrusive blood pressure measurement: from theory to algorithm

Xiaorong DING ; Yuan Ting ZHANG

Biomedical Engineering Letters.2019;9(1):37-52. doi:10.1007/s13534-019-00096-x

Cuffless technique holds great promise to measure blood pressure (BP) in an unobtrusive way, improving diagnostics and monitoring of hypertension and its related cardiovascular diseases, and maximizing the independence and participation of individual. Pulse transit time (PTT) has been the most commonly employed techniques for cuffl ess BP estimation. Many studies have been conducted to explore its feasibility and validate its performance in the clinical settings. However, there is still issues and challenges ahead before its wide application. This review will investigate the understanding and development of the PTT technique in depth, with a focus on the physiological regulation of arterial BP, the relationship between PTT and BP, and the summaries of the PTT-based models for BP estimation.
Blood Pressure ; Cardiovascular Diseases ; Hypertension ; Pulse Wave Analysis

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Current progress of photoplethysmography and SPO 2 for health monitoring

Toshiyo TAMURA

Biomedical Engineering Letters.2019;9(1):21-36. doi:10.1007/s13534-019-00097-w

A photoplethysmograph (PPG) is a simple medical device for monitoring blood fl ow and transportation of substances in the blood. It consists of a light source and a photodetector for measuring transmitted and refl ected light signals. Clinically, PPGs are used to monitor the pulse rate, oxygen saturation, blood pressure, and blood vessel stiff ness. Wearable unobtrusive PPG monitors are commercially available. Here, we review the principle issues and clinical applications of PPG for monitoring oxygen saturation.
Blood Pressure ; Blood Vessels ; Heart Rate ; Oxygen ; Photoplethysmography ; Respiratory Rate ; Transportation

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