International Journal of Medical Engineering and Informatics http://www.inderscience.com/browse/index.php?journalID=268&year=2012&vol=4&issue=1 Inderscience Publishers Ltd en-uk International Journal of Medical Engineering and Informatics 1755-0653 1755-0661 © 2012 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijmei_scoverijmei.jpg http://www.inderscience.com/browse/index.php?journalID=268&year=2012&vol=4&issue=1 http://www.inderscience.com/link.php?id=45300 Minimally invasive surgery (or key-hole surgery) is an alternative to open surgery has been gaining popularity among patients and health delivery systems. In general, to view the surgical site, an endoscope is inserted into the abdominal cavity though natural or artificial incision. Long stem surgical tools are also inserted through supporting incisions. The surgeon can then perform the operation by indirectly viewing the scene and manipulating the surgical tools. While viewing the monitor, the surgeon does not have any automatic access to preoperative images or patient specific data or be able to manipulate superimpose them on the viewing monitor. This paper presents a novel approach based on image processing of the surgical site and neural network framework for classifying and identifying gestures of surgical tools and classification of their motions. Seven feature quantities were selected as an input to a feed-forward neural network. Experimental analysis of the classification was carried-out for single tools and multiple tool gestures in an in-vitro setting. Through a number of trails we were able to demonstrate the feasibility of our gesture recognition approaches. Toward the design of a novel surgeon-computer interface using image processing of surgical tools in minimally invasive surgery
Shahram Payandeh; Jeff Hsu; Peter Doris
International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 1 - 24
Minimally invasive surgery (or key-hole surgery) is an alternative to open surgery has been gaining popularity among patients and health delivery systems. In general, to view the surgical site, an endoscope is inserted into the abdominal cavity though natural or artificial incision. Long stem surgical tools are also inserted through supporting incisions. The surgeon can then perform the operation by indirectly viewing the scene and manipulating the surgical tools. While viewing the monitor, the surgeon does not have any automatic access to preoperative images or patient specific data or be able to manipulate superimpose them on the viewing monitor. This paper presents a novel approach based on image processing of the surgical site and neural network framework for classifying and identifying gestures of surgical tools and classification of their motions. Seven feature quantities were selected as an input to a feed-forward neural network. Experimental analysis of the classification was carried-out for single tools and multiple tool gestures in an in-vitro setting. Through a number of trails we were able to demonstrate the feasibility of our gesture recognition approaches.

]]> 10.1504/IJMEI.2012.045300 International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 1 - 24 Shahram Payandeh; Jeff Hsu; Peter Doris Experimental Robotics and Imaging Laboratory, School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia, V5A 1S6, Canada. ' Experimental Robotics and Imaging Laboratory, School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia, V5A 1S6, Canada. ' Division of Minimally Invasive Surgery, Surrey Memorial Hospital, 13750 96 Avenue, Surrey, British Columbia, V3V 1Z2, Canada surgical tools image processing tool gesture recognition surgeon-computer interface SCI human-computer interface HCI minimally invasive surgery keyhole surgery neural networks classification tool motion. 2012-02-05T23:20:50-05:00 4 1 1 24 2012-02-05T23:20:50-05:00 http://www.inderscience.com/link.php?id=45301 T-cell receptor V beta (TCRV<SUB align="right">β) gene repertoire (Vβ1-Vβ24) was evaluated in the peripheral blood mononuclear cells (PBMCs) from asymptomatic and amicrofilaremic normal individuals (EN), and patients with chronic pathology (CP) harbouring Wuchereria bancrofti. TCRV<SUB align="right">β gene expression in phytohemagglutinin (PHA) stimulated PBMC cultures from EN and CP individuals was in the order EN > CP while in Brugia malayi adult antigen (BmA) or purified protein derivative from mycobacterium tuberculosis (PPD) stimulation or the unstimulated conditions, the order was CP > EN. Thus, the PBMCs of the CP patients showed elevated levels of TCRV<SUB align="right">β gene expression both in the unstimulated and stimulated conditions compared to EN. T-cell receptor variable beta (1-24) gene repertoire in patients with Wuchereria bancrofti infections
M.S. Sudhakar; K.V. Alala Sundaram; R.B. Narayanan
International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 25 - 35
T-cell receptor V beta (TCRV<SUB align="right">β) gene repertoire (Vβ1-Vβ24) was evaluated in the peripheral blood mononuclear cells (PBMCs) from asymptomatic and amicrofilaremic normal individuals (EN), and patients with chronic pathology (CP) harbouring Wuchereria bancrofti. TCRV<SUB align="right">β gene expression in phytohemagglutinin (PHA) stimulated PBMC cultures from EN and CP individuals was in the order EN > CP while in Brugia malayi adult antigen (BmA) or purified protein derivative from mycobacterium tuberculosis (PPD) stimulation or the unstimulated conditions, the order was CP > EN. Thus, the PBMCs of the CP patients showed elevated levels of TCRV<SUB align="right">β gene expression both in the unstimulated and stimulated conditions compared to EN.

]]> 10.1504/IJMEI.2012.045301 International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 25 - 35 M.S. Sudhakar; K.V. Alala Sundaram; R.B. Narayanan Centre for Biotechnology, Anna University, Chennai 600 025, India. ' Department of Plastic Surgery, Royapettah General Hospital, Chennai 600 014, India. ' Centre for Biotechnology, Anna University, Chennai-600 025, India filariasis T-cell receptor V beta TCRV-beta purified protein derivatives PPD Brugia malayi adult antigen BmA Wuchereria bancrofti gene expression phytohemagglutinin PHA peripheral blood cells blood mononuclear cells mycobacterium tuberculosis mycobacterium TB. 2012-02-05T23:20:50-05:00 4 1 25 35 2012-02-05T23:20:50-05:00 http://www.inderscience.com/link.php?id=45302 This paper focuses on an approach for characterising the mammogram masses using various geometric shape and margin features. According to BIRADS system, benign and malignant masses can be differentiated using its shape, size and density features, which is how radiologist visualise the mammograms. According to BIRADS, benign masses are round, oval, lobular in shape and malignant masses are lobular or irregular in shape. Various 17 geometrical shape and margin features are introduced to characterise the morphology of masses, as there is no single measure to differentiate various shapes. Experiments have been conducted on 1553 DDSM database mammograms and classified using CART classifier. Experimental results indicate that CART can classify masses effectively and generates simple rules, which can be easily implemented in any system using if..then..else statements. Experimental results are found to be encouraging. The results demonstrate the effectiveness of CART classifier for classifying masses as benign, malignant and normal. Mammogram mass classification using various geometric shape and margin features for early detection of breast cancer
B. Surendiran; A. Vadivel
International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 36 - 54
This paper focuses on an approach for characterising the mammogram masses using various geometric shape and margin features. According to BIRADS system, benign and malignant masses can be differentiated using its shape, size and density features, which is how radiologist visualise the mammograms. According to BIRADS, benign masses are round, oval, lobular in shape and malignant masses are lobular or irregular in shape. Various 17 geometrical shape and margin features are introduced to characterise the morphology of masses, as there is no single measure to differentiate various shapes. Experiments have been conducted on 1553 DDSM database mammograms and classified using CART classifier. Experimental results indicate that CART can classify masses effectively and generates simple rules, which can be easily implemented in any system using if..then..else statements. Experimental results are found to be encouraging. The results demonstrate the effectiveness of CART classifier for classifying masses as benign, malignant and normal.

]]> 10.1504/IJMEI.2012.045302 International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 36 - 54 B. Surendiran; A. Vadivel Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore – 641049, Tamilnadu, India. ' Department of Computer Applications, National Institute of Technology, Tiruchirappalli, Tamilnadu – 620015, India digital mammograms geometrical shape features margin features benign masses malignant masses normal masses classification regression tree CART breast imaging reporting and data system BI-RADSTM categories computer aided diagnosis radiology early detection breast cancer early diagnosis tumours. 2012-02-05T23:20:50-05:00 4 1 36 54 2012-02-05T23:20:50-05:00 http://www.inderscience.com/link.php?id=45303 The multiscale entropy (MSE), a technique, to analyse heart rate variability at different time-scales, requires priori determination of pattern length (m) to be compared and tolerance threshold value (r) to accept the similarity between the patterns. Conventionally recommended value of r, 0.1 to 0.2 times the standard deviation of original time series, found inappropriate for accurate MSE at higher scales. Finding true maximum MSE (MSE<SUB align="right">max), by evaluating all values of r from 0 to 1 is a better index of coarse-grained time series complexity, but it is very cumbersome. Automatic selection method of r proposed by Lu et al, has been extended to find MSE<SUB align="right">max of RR interval time series for ten healthy subjects with data length N = 900 and m = 2. The burden of finding MSE<SUB align="right">max has been averted by the proposed modified multiscale entropy and lead to a more appropriate representation of the complexity than the conventional method. Modified multiscale entropy in HRV for automatic selection of threshold value r
Butta Singh; Dilbag Singh
International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 55 - 65
The multiscale entropy (MSE), a technique, to analyse heart rate variability at different time-scales, requires priori determination of pattern length (m) to be compared and tolerance threshold value (r) to accept the similarity between the patterns. Conventionally recommended value of r, 0.1 to 0.2 times the standard deviation of original time series, found inappropriate for accurate MSE at higher scales. Finding true maximum MSE (MSE<SUB align="right">max), by evaluating all values of r from 0 to 1 is a better index of coarse-grained time series complexity, but it is very cumbersome. Automatic selection method of r proposed by Lu et al, has been extended to find MSE<SUB align="right">max of RR interval time series for ten healthy subjects with data length N = 900 and m = 2. The burden of finding MSE<SUB align="right">max has been averted by the proposed modified multiscale entropy and lead to a more appropriate representation of the complexity than the conventional method.

]]> 10.1504/IJMEI.2012.045303 International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 55 - 65 Butta Singh; Dilbag Singh Department of Electronics and Communication Engineering, Guru Nanak Dev University, Regional Campus, Jalandhar, Punjab 144 001, India. ' Department of Instrumentation and Control Engineering, National institute of Technology, Jalandhar, Punjab 144 001, India heart rate variability HRV multiscale entropy modified MSE MMSE threshold values threshold value selection. 2012-02-05T23:20:50-05:00 4 1 55 65 2012-02-05T23:20:50-05:00 http://www.inderscience.com/link.php?id=45304 Avoidance of patients' intraoperative awareness and explicit recall of pain during surgery is important. Conventional methods of depth of anesthesia (DoA) monitoring involve physiological monitoring which are influenced by the administered anesthetic drugs. Balanced anesthesia is fusion of its four components analgesia, amnesia, motor blockade and hypnosis. One major component is analgesia which means inability to feel pain during surgery. Pain cannot be estimated any single physio-pathological signal. A proper analgesia index proportional to the degree of pain experienced by the patient is required. Electroencephalogram (EEG) is a reliable means to determine real time DoA. In the present study, EEG of 12 volunteer subjects was recorded during relaxed and during pain. It was found that the Higuchi fractal dimension (HFD) feature of EEG from parietal region of brain reflects the sensation of pain and gives an overall accuracy of 95% in determining the pain experienced by the patient. Higuchi fractal dimension as a measure of analgesia
Sanjeev Kumar; Amod Kumar; Anjan Trikha; Sneh Anand; Prashanth Gantla
International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 66 - 72
Avoidance of patients' intraoperative awareness and explicit recall of pain during surgery is important. Conventional methods of depth of anesthesia (DoA) monitoring involve physiological monitoring which are influenced by the administered anesthetic drugs. Balanced anesthesia is fusion of its four components analgesia, amnesia, motor blockade and hypnosis. One major component is analgesia which means inability to feel pain during surgery. Pain cannot be estimated any single physio-pathological signal. A proper analgesia index proportional to the degree of pain experienced by the patient is required. Electroencephalogram (EEG) is a reliable means to determine real time DoA. In the present study, EEG of 12 volunteer subjects was recorded during relaxed and during pain. It was found that the Higuchi fractal dimension (HFD) feature of EEG from parietal region of brain reflects the sensation of pain and gives an overall accuracy of 95% in determining the pain experienced by the patient.

]]> 10.1504/IJMEI.2012.045304 International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 66 - 72 Sanjeev Kumar; Amod Kumar; Anjan Trikha; Sneh Anand; Prashanth Gantla Central Scientific Instruments Organisation, Sector 30-C, Chandigarh – 160030, India. ' Central Scientific Instruments Organisation, Sector 30-C, Chandigarh – 160030, India. ' Department of Anesthesiology, All Indian Institute for Medical Sciences, Ansari Nagar, New Delhi – 110029, India. ' Centre for Biomedical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi – 110016, India. ' Department of Physics, National Institute of Technology, Warangal – 506052, India EEG Higuchi fractal dimension HFD balanced anaesthesia electroencephalograms depth of anesthesia anesthesia monitoring amnesia motor blockade hypnosis patient pain surgery. 2012-02-05T23:20:50-05:00 4 1 66 72 2012-02-05T23:20:50-05:00 http://www.inderscience.com/link.php?id=45305 Echocardiography is mainly to assess valvular regurgitation and get valuable information on the severity of aortic regurgitation (AR). It has several applications, but this paper focuses only on its use in the quantitative evaluation of AR. Proximal isovelocity surface area (PISA) evaluates the severity of AR. The quantification of the effective regurgitant orifice area (EROA) in AR is presented utilising Doppler echocardiography aided by clustering based image segmentation and PISA techniques. Pre-processing is done subjecting the colour Doppler echocardiography image to Gaussian filtering which improves the signal to noise ratio of the image. Subsequently, the image was enhanced with the aid of an image contrast enhancement method that utilises contrast-limited adaptive histogram equalisation. Then this image is segmented by using fuzzy-k means clustering to enable more precise quantification of the AR. PISA method is employed for calculating the quantitative parameters of AR such as, EROA, regurgitant volume (RV), regurgitant fraction (RF), etc. The proximal flow convergence method is used to quantify valvular regurgitation by analysing the converging flow field proximal to the mild, severe or eccentric AR lesion. Experimental evaluation on the commonly accessible dataset illustrates the enhanced performance of the proposed approach effectively. Quantification of aortic regurgitation using proximal isovelocity surface area: an effective segmentation approach based on fuzzy clustering
P. Abdul Khayum; P.V. Sridevi; M.N. Giriprasad
International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 73 - 87
Echocardiography is mainly to assess valvular regurgitation and get valuable information on the severity of aortic regurgitation (AR). It has several applications, but this paper focuses only on its use in the quantitative evaluation of AR. Proximal isovelocity surface area (PISA) evaluates the severity of AR. The quantification of the effective regurgitant orifice area (EROA) in AR is presented utilising Doppler echocardiography aided by clustering based image segmentation and PISA techniques. Pre-processing is done subjecting the colour Doppler echocardiography image to Gaussian filtering which improves the signal to noise ratio of the image. Subsequently, the image was enhanced with the aid of an image contrast enhancement method that utilises contrast-limited adaptive histogram equalisation. Then this image is segmented by using fuzzy-k means clustering to enable more precise quantification of the AR. PISA method is employed for calculating the quantitative parameters of AR such as, EROA, regurgitant volume (RV), regurgitant fraction (RF), etc. The proximal flow convergence method is used to quantify valvular regurgitation by analysing the converging flow field proximal to the mild, severe or eccentric AR lesion. Experimental evaluation on the commonly accessible dataset illustrates the enhanced performance of the proposed approach effectively.

]]> 10.1504/IJMEI.2012.045305 International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 73 - 87 P. Abdul Khayum; P.V. Sridevi; M.N. Giriprasad Department of ECE, Madina Engineering College, Kadapa, Andhra Pradesh 516003, India. ' Department of ECE, AU College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh 530003, India. ' Department of ECE, JNTU College of Engineering, Pulivendula, Kadapa Dist, Andhra Pradesh 516390, India Doppler echocardiography valvular regurgitation aortic regurgitation regurgitant volume regurgitant fraction effective regurgitant orifice proximal isovelocity surface area Gaussian filtering image enhancement fuzzy clustering fuzzy k means. 2012-02-05T23:20:50-05:00 4 1 73 87 2012-02-05T23:20:50-05:00 http://www.inderscience.com/link.php?id=45306 This paper introduces a web-based healthcare information system (WB-HIS). The developed HIS consists of secure web server that stores the patient's database, internet infrastructure, review station (client PC) and client personal digital assistant (PDA). The proposed system has many attractive features. First, the WB-HIS provides a global communication and thus satisfies the new requirements of modern HIS to shift from hospital-centred HIS to a global one to be accessed from anywhere and at anytime. Second, the WB-HIS helps the physicians to increase their medical outcomes because they can see more number of patients during his day time and access remotely the patient's information which is clinically high demanded especially in case of emergencies. Finally, it facilitates real-time patient assessment and analysis during examination and diagnosis which improves the healthcare service. Development of a web-based healthcare information system
Mashhour M. Bani Amer; Hussam M. Mousa; Banan M. Al-Salem; Amany K. Rashaideh
International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 88 - 96
This paper introduces a web-based healthcare information system (WB-HIS). The developed HIS consists of secure web server that stores the patient's database, internet infrastructure, review station (client PC) and client personal digital assistant (PDA). The proposed system has many attractive features. First, the WB-HIS provides a global communication and thus satisfies the new requirements of modern HIS to shift from hospital-centred HIS to a global one to be accessed from anywhere and at anytime. Second, the WB-HIS helps the physicians to increase their medical outcomes because they can see more number of patients during his day time and access remotely the patient's information which is clinically high demanded especially in case of emergencies. Finally, it facilitates real-time patient assessment and analysis during examination and diagnosis which improves the healthcare service.

]]> 10.1504/IJMEI.2012.045306 International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 88 - 96 Mashhour M. Bani Amer; Hussam M. Mousa; Banan M. Al-Salem; Amany K. Rashaideh Biomedical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan. ' Biomedical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan. ' Biomedical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan. ' Biomedical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan healthcare information systems web-based systems hospital information systems internet patient database personal digital assistants PDAs e-healthcare electronic healthcare healthcare technology real-time assessment patient assessment. 2012-02-05T23:20:50-05:00 4 1 88 96 2012-02-05T23:20:50-05:00 http://www.inderscience.com/link.php?id=45307 This project focused on characterising the quality of life indices and economic resources in the G-8 nations. The research team explored the existing scientific infrastructures already in place in the industrialised nations, even before the completion of the human genome sequencing by March 2003. Their authentic and well-established technological workforce developed new generation of innovative technologies for inexpensive, spontaneous, and precise genomic sequencing. The project team not only discussed the medical, public health and economic benefits derived from genomic research, but also compiled the fledging careers in bioscience and genetics in the G-8 nations. Human genome sequencing technologies, the medical, public health and economic implications in the industrialised G-8 nations
E. William Ebomoyi; Josephine I. Ebomoyi
International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 97 - 108
This project focused on characterising the quality of life indices and economic resources in the G-8 nations. The research team explored the existing scientific infrastructures already in place in the industrialised nations, even before the completion of the human genome sequencing by March 2003. Their authentic and well-established technological workforce developed new generation of innovative technologies for inexpensive, spontaneous, and precise genomic sequencing. The project team not only discussed the medical, public health and economic benefits derived from genomic research, but also compiled the fledging careers in bioscience and genetics in the G-8 nations.

]]> 10.1504/IJMEI.2012.045307 International Journal of Medical Engineering and Informatics, Vol. 4, No. 1 (2012) pp. 97 - 108 E. William Ebomoyi; Josephine I. Ebomoyi Department of Health Studies College of Health Sciences, Chicago State University, Chicago, Illinois 60628-1598 USA. ' Department of Biology College of Arts and Sciences, Saint Xavier University, Chicago, Illinois, 60611, USA. international human genome sequencing consortium IHGSC quality of life indices G8 nations genomic technology DNA vision medical informatics public health economic outcomes ethics legal implications social implications bioinformatics. 2012-02-05T23:20:50-05:00 4 1 97 108 2012-02-05T23:20:50-05:00