Bangladesh Journal of Medical Physics The official journal of the Bangladesh Medical Physics Association (BMPA) (an affiliate of the International Organisation of Medical Physics - IOMP). Full text articles available. en-US (Professor K. Siddique-e Rabbani) (Md Fahmid Uddin Khondoker) Mon, 03 Dec 2018 16:35:44 +0000 OJS 60 Development of Low Cost Miniature USB Based Data Acquisition System for Biomedical Instrumentation <p>In biomedical instrumentation, computer based data acquisition system is required for recording of physiological parameters and bioelectric signals, which allows signal processing, display, analysis and storage in digital media. However, Most of the commercially available PC based Data Acquisition systems are of very high cost and requires specific commercial software, again at a very high cost. Moreover, if the data is not stored in raw binary or known format, it is not possible for the user to use the data in other system or software of their own choice. Therefore, a low cost, simple and open source PC based data acquisition system for biomedical application would be very useful for biomedical instrument developers and researchers in the low resource countries. In this work, we present such development of data acquisition system. The developed system utilizes an 8-bit ordinary low cost microcontroller and some electronic circuit component to develop the data acquisition system and implementation of USB 1.1 (Universal Serial Bus) interface to PC. The onboard 10-bit ADC of the microcontroller was used for analog data sampling. Two sampling and data transfer mode is implemented, (i) Continuous mode with low sampling rate (800 sample/sec) and practically real time plotting and (ii) Batch mode, with high sampling rate (76.9 k sample/sec) but with batch type plotting. To evaluate the system, PC side GUI (Graphical User Interface) software was also developed. The GUI of system shows that a test sinusoidal signal is reproduced very nicely without any amplitude and phase distortion within the frequency band of 1 to 10 KHz. The system is suitable for low frequency bioelectric signals like ECG, EEG etc. and as well as high frequency signal like EMG, NCV etc. The system is low cost, miniature, simple, and efficient and being used in several indigenously developed medical devices like ECG, EMG, NCV and FIM [Rabbani et al, 1999] at the authors’ department with excellent satisfactory results.</p><p>Bangladesh Journal of Medical Physics Vol.10 No.1 2017 1-11</p> Abdullah Al Amin, K Siddique e Rabbani ##submission.copyrightStatement## Mon, 03 Dec 2018 16:35:08 +0000 Myocardial Ischemia Detection from Slope of ECG ST Segment <p>Myocardial ischemia occurs when blood flow to heart is reduced preventing it from receiving enough oxygen. It is a possible indication of partial or complete blockage of coronary arteries. Though ischemia is accompanied by symptoms (fatigue, chest pain, shortness of breath etc.) sometimes it can be silent. If not treated, it can lead to various heart diseases. Most importantly it can progress to myocardial infarction (heart attack), which can be fatal. Thus detecting ischemia at an early stage is important to prevent serious implications. Nowadays personal healthcare monitoring systems are used which provide vital physiological information. In future ECG measurement devices would also be common in homes. So, the proposed work intends to develop an algorithm in detecting myocardial ischemia from ECG, which would be computationally less complex and easy to implement in homecare ECG devices. One way to do it is through continuous or long term monitoring of ECG. The ST segment elevation (or depression) indicates presence of ischemia. The proposed method measures slope of ST segment which must vary in case of ST changes. The algorithm is tested on selected records of the European ST-T database and returns an accuracy of 83.33%.</p><p>Bangladesh Journal of Medical Physics Vol.10 No.1 2017 12-24</p> Md Soumik Farhan, KM Talha Nahiyan ##submission.copyrightStatement## Mon, 03 Dec 2018 16:35:15 +0000 Real-Time Classification of Multi-Channel Forearm EMG to Recognize Hand Movements using Effective Feature Combination and LDA Classifier <p>Electromyography (EMG) signals acquired from surface of arms can be crucial in recognizing nature of hand gestures. The concept is used in current highly demanding fields such as controlling prosthetic limbs, diagnosing neuromuscular disorders, manipulation of robotic arm etc. The purpose of the work was to classify a set of hand motions from corresponding multi-channel surface EMG signals by developing MATLAB tools. The research focused on extracting multiple signal features and finding the appropriate combination of extracted intelligible features to get the best classification accuracy for the specific set of hand gestures. For dynamic and fast classification purpose, linear discriminant analysis (LDA) classifier was employed. Effect of feature dimensionality reduction on classification accuracy was also investigated via Principal Component Analysis (PCA) in this research. Finally, the research analyzed different electrode placements by comparing classification accuracy for each of the set of motions and proposed a simple and compact data acquisition instrumentation having less number of electrodes while maintaining high classification accuracy.</p><p>Bangladesh Journal of Medical Physics Vol.10 No.1 2017 25-39</p> Muhammad Sabbir Alam, ASM Shamsul Arefin ##submission.copyrightStatement## Mon, 03 Dec 2018 16:35:21 +0000 Effect of top cover tilt angle with ground surface on productivity of basin type solar distillation unit <p>Basin type solar stills were made with two types of top cover, transparent PVC sheet and another with glass sheet. A soaked black towel was at the base which was heated through green-house effect and contributed to the water for distillation. Productivity of these two basin type solar stills were studied at different tilt angles of the top transparent cover with ground surface (13<sup>o</sup>, 23<sup>o</sup> and 35<sup>o</sup>). The average amount of distilled water produced increased with the tilt angles for both types of cover materials, that for glass being much higher than that for PVC cover.</p><p>Bangladesh Journal of Medical Physics Vol.10 No.1 2017 40-46</p> Hosney Ara Begum, M Abu Yousuf, K Siddique e Rabbani ##submission.copyrightStatement## Mon, 03 Dec 2018 16:35:27 +0000 A Feasibility Study of Employing EOG Signal in Combination with EEG Based BCI System for Improved Control of a Wheelchair <p>For a fully paralysed person, EEG (Electroencephalogram) based Brain Computer Interface (BCI) has a great promise for controlling electromechanical equipment such as a wheelchair. Again EOG (Electrooculography) based Human Machine Interface system also provides a possibility. Individually, none of these methods is capable of giving a fully error free reliable and safe control, but an appropriate combination may provide a better reliability, which is the aim of the present work. Here we intend to use EEG data to classify two classes, corresponding to left and right hand movement, and EOG data to classify two classes corresponding to left and right sided eyeball movement. We will use these classifications independently first and then combine these with different weightage to find if a better and reliable control is possible. For this purpose offline classification of motor imaginary EEG data of a subject was carried out extracting features using Common Spatial Pattern (CSP) and classifying using Linear Discriminative Analysis. The independent EEG motor imaginary data classification resulted in 89.8% of accuracy in 10 fold one leave out cross validation. The EOG eyeball movement produces distinctive signals of opposite polarities and is classified using a simple discriminant type classification resulting in 100% accuracy. However, using EOG solely is not acceptable as there always will be unintentional eye movement giving false commands. Combining both EEG and EOG with different weightage to the two classifications produced varied degrees of improvement. For 50% weightage to both resulted in 100% accuracy, without any error, and this may be accepted as a practical solution because the chances of unintentional false commands will be very rare. Therefore, a combination of EOG and BCI may lead to a greater reliability in terms of avoidance of undesired control signals.</p><p>Bangladesh Journal of Medical Physics Vol.10 No.1 2017 47-58</p> Abdullah Al Amin ##submission.copyrightStatement## Mon, 03 Dec 2018 16:35:32 +0000