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Abdullah, S., Hafid, A., Folke, M., Lindén, M. & Kristoffersson, A. (2023). A Novel Fiducial Point Extraction Algorithm to Detect C and D Points from the Acceleration Photoplethysmogram (CnD). Electronics, 12(5), Article ID 1174.
Öppna denna publikation i ny flik eller fönster >>A Novel Fiducial Point Extraction Algorithm to Detect C and D Points from the Acceleration Photoplethysmogram (CnD)
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2023 (Engelska)Ingår i: Electronics, E-ISSN 2079-9292, Vol. 12, nr 5, artikel-id 1174Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

The extraction of relevant features from the photoplethysmography signal for estimating certain physiological parameters is a challenging task. Various feature extraction methods have been proposed in the literature. In this study, we present a novel fiducial point extraction algorithm to detect c and d points from the acceleration photoplethysmogram (APG), namely “CnD”. The algorithm allows for the application of various pre-processing techniques, such as filtering, smoothing, and removing baseline drift; the possibility of calculating first, second, and third photoplethysmography derivatives; and the implementation of algorithms for detecting and highlighting APG fiducial points. An evaluation of the CnD indicated a high level of accuracy in the algorithm’s ability to identify fiducial points. Out of 438 APG fiducial c and d points, the algorithm accurately identified 434 points, resulting in an accuracy rate of 99%. This level of accuracy was consistent across all the test cases, with low error rates. These findings indicate that the algorithm has a high potential for use in practical applications as a reliable method for detecting fiducial points. Thereby, it provides a valuable new resource for researchers and healthcare professionals working in the analysis of photoplethysmography signals.

Nationell ämneskategori
Medicinteknik
Identifikatorer
urn:nbn:se:mdh:diva-62004 (URN)10.3390/electronics12051174 (DOI)000947098400001 ()2-s2.0-85149747017 (Scopus ID)
Tillgänglig från: 2023-03-03 Skapad: 2023-03-03 Senast uppdaterad: 2023-04-12Bibliografiskt granskad
Kanwal, K., Asif, M., Khalid, S. G., Wasi, S., Zafar, F., Kiran, I. & Abdullah, S. (2023). Comparative Analysis of Photoplethysmography Signal Quality from Right and Left Index Fingers. Traitement du signal, 40(5), 2214-2199
Öppna denna publikation i ny flik eller fönster >>Comparative Analysis of Photoplethysmography Signal Quality from Right and Left Index Fingers
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2023 (Engelska)Ingår i: Traitement du signal, ISSN 0765-0019, E-ISSN 1958-5608, Vol. 40, nr 5, s. 2214-2199Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Photoplethysmography (PPG) has emerged as an increasingly attractive signal for non-invasive physiological measurements, owing to its simplicity, cost-effectiveness, and broad applicability spanning cardiovascular to respiratory systems. The burgeoning interest in PPG signal processing has facilitated its extensive incorporation in wearable devices, thus stimulating active research in this field. The present study undertakes a comprehensive evaluation to discern the optimal index finger (right or left) for PPG data acquisition and subsequent filtration, appraised through the lens of the signal-to-noise ratio (SNR) of the filtered signal. An analysis conducted on signals contaminated with white Gaussian noise unveiled that the Savitzky-Golay filter (a polynomial filter) with a window size of three outperformed other window lengths, rendering the highest SNR. Among the Infinite Impulse Response (IIR) filters compared; the Chebyshev I filter emerged as superior. Interestingly, the right index finger consistently demonstrated a higher mean SNR across filters: 0.49% for the Savitzky-Golay filters, 4.32% for the Butterworth (order 6), 7.71% for the Chebyshev I (order 10), and 4.02% for the Chebyshev II (order 4), relative to the left index finger for PPG signals perturbed by white Gaussian noise. These findings provide an insightful perspective for future research and development in wearable devices, suggesting potential superiority of the right index finger for PPG signal acquisition and filtration.

Nationell ämneskategori
Signalbehandling
Identifikatorer
urn:nbn:se:mdh:diva-64862 (URN)10.18280/ts.400537 (DOI)001094288100037 ()2-s2.0-85177818395 (Scopus ID)
Tillgänglig från: 2023-11-29 Skapad: 2023-11-29 Senast uppdaterad: 2023-12-07Bibliografiskt granskad
Abdullah, S., Hafid, A. & Shahid, H. (2023). Comparing the Effectiveness of EMG and Electrical Impedance myography Measurements for Controlling Prosthetics. In: IEEE Int. Multidiscip. Conf. Eng. Technol., IMCET: . Paper presented at 2023 IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023, Beirut, Lebanon, 12-14 December, 2023 (pp. 189-193). Institute of Electrical and Electronics Engineers Inc.
Öppna denna publikation i ny flik eller fönster >>Comparing the Effectiveness of EMG and Electrical Impedance myography Measurements for Controlling Prosthetics
2023 (Engelska)Ingår i: IEEE Int. Multidiscip. Conf. Eng. Technol., IMCET, Institute of Electrical and Electronics Engineers Inc. , 2023, s. 189-193Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In recent years, the field of prosthetics has made significant progress towards creating prosthetic devices that are more functional, comfortable, and user-friendly. However, achieving intuitive control over prosthetic hand movements remains a significant challenge, especially for individuals with limb loss who rely on prosthetics for independent daily activities. To address this challenge, researchers have explored the potential of non-invasive techniques as electromyography (EMG) for prosthetic control. This paper aims to investigate the potential of using EMG and the electrical impedance myography (EIMG) techniques jointly for the measurement of hand movements. The study involved recording and comparing EMG and EIMG signals from a cohort of healthy individuals. These signals were captured during four distinct hand gestures: opening and closing the hand, as well as extending and flexing it, under varying time conditions, allowing for categorization into low and high-intensity movements. Data collection employed the Open BCI and ZRPI devices. The analysis of these signal waveforms revealed compelling results. Brachioradialis activity in EMG 2 exhibited an increase during open hand (0.015mV) and extension hand (0.009mV in low and 0.013mV in high intensity) gestures, accompanied by increased EIMG activity (56mV and 52mV respectively). Additionally, close hand (0.0018mV in low and 0.05mV in high intensity) and flexion hand (0.0075 in low intensity and 0.002 in high intensity) gestures exhibited heightened flexor carpi ulnaris activity with raised EIMG activity (57mV and 45mV respectively). These results proved to be consistent, acceptable, and aligned with existing literature. The findings of this paper indicate that both EMG and EIMG techniques could be used together to control custom-made hand prosthetics, demonstrating a significant development that could lead to more intuitive and easier-to-control prosthetics. Also, the results obtained could be valuable to researchers and engineers working in the prosthetics field, as it provides insights into the potential of non-invasive techniques for prosthetic control.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers Inc., 2023
Nyckelord
Biomedical application, Electrical Impedance Myography, Electromyography, Prosthetic, Electric impedance, Electric impedance measurement, Prosthetics, Signal analysis, Biomedical applications, Electrical impedance, Hands movement, High intensity, Low-intensity, Noninvasive technique, Prosthetic controls, Prosthetic devices, User friendly, Medical applications
Nationell ämneskategori
Medicinska material och protesteknik
Identifikatorer
urn:nbn:se:mdh:diva-65803 (URN)10.1109/IMCET59736.2023.10368219 (DOI)2-s2.0-85182921540 (Scopus ID)9798350313826 (ISBN)
Konferens
2023 IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023, Beirut, Lebanon, 12-14 December, 2023
Tillgänglig från: 2024-01-31 Skapad: 2024-01-31 Senast uppdaterad: 2024-01-31Bibliografiskt granskad
Khan, B., Abdullah, S. & Khan, S. (2023). Current Progress in Conductive Hydrogels and Their Applications in Wearable Bioelectronics and Therapeutics. Micromachines, 14(5), Article ID 1005.
Öppna denna publikation i ny flik eller fönster >>Current Progress in Conductive Hydrogels and Their Applications in Wearable Bioelectronics and Therapeutics
2023 (Engelska)Ingår i: Micromachines, E-ISSN 2072-666X, Vol. 14, nr 5, artikel-id 1005Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Wearable bioelectronics and therapeutics are a rapidly evolving area of research, with researchers exploring new materials that offer greater flexibility and sophistication. Conductive hydrogels have emerged as a promising material due to their tunable electrical properties, flexible mechanical properties, high elasticity, stretchability, excellent biocompatibility, and responsiveness to stimuli. This review presents an overview of recent breakthroughs in conductive hydrogels, including their materials, classification, and applications. By providing a comprehensive review of current research, this paper aims to equip researchers with a deeper understanding of conductive hydrogels and inspire new design approaches for various healthcare applications.

Ort, förlag, år, upplaga, sidor
MDPI, 2023
Nyckelord
bioelectronics, biomaterials, biotherapeutics, conductive materials, drug delivery, sensing, smart hydrogels, wearable electronics, Biocompatibility, Wearable technology, 'current, Bioelectronic, Design approaches, Health care application, Material application, Material classification, Tunables, Hydrogels
Nationell ämneskategori
Medicinteknik
Identifikatorer
urn:nbn:se:mdh:diva-63199 (URN)10.3390/mi14051005 (DOI)000997802800001 ()2-s2.0-85160604739 (Scopus ID)
Tillgänglig från: 2023-06-14 Skapad: 2023-06-14 Senast uppdaterad: 2024-01-17Bibliografiskt granskad
Khan, B., Fatima, H., Qureshi, A., Kumar, S., Hanan, A., Hussain, J. & Abdullah, S. (2023). Drawbacks of Artificial Intelligence and Their Potential Solutions in the Healthcare Sector. Biomedical Materials & Devices
Öppna denna publikation i ny flik eller fönster >>Drawbacks of Artificial Intelligence and Their Potential Solutions in the Healthcare Sector
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2023 (Engelska)Ingår i: Biomedical Materials & Devices, ISSN 2731-4812Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Artificial intelligence (AI) has the potential to make substantial progress toward the goal of making healthcare more personalized, predictive, preventative, and interactive. We believe AI will continue its present path and ultimately become a mature and effective tool for the healthcare sector. Besides this AI-based systems raise concerns regarding data security and privacy. Because health records are important and vulnerable, hackers often target them during data breaches. The absence of standard guidelines for the moral use of AI and ML in healthcare has only served to worsen the situation. There is debate about how far artificial intelligence (AI) may be utilized ethically in healthcare settings since there are no universal guidelines for its use. Therefore, maintaining the confidentiality of medical records is crucial. This study enlightens the possible drawbacks of AI in the implementation of healthcare sector and their solutions to overcome these situations.

Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:mdh:diva-64859 (URN)10.1007/s44174-023-00063-2 (DOI)
Tillgänglig från: 2023-11-29 Skapad: 2023-11-29 Senast uppdaterad: 2023-11-29Bibliografiskt granskad
Abdelakram, H., Kristoffersson, A. & Abdullah, S. (2023). Edu-Mphy: A Low-Cost Multi-Physiological Recording System for Education and Research in Healthcare and Engineering. In: Abstracts: Medicinteknikdagarna 2023. Paper presented at Medicinteknikdagarna 2023, Stockholm, Sweden, 9-11 oktober, 2023 (pp. 117-117).
Öppna denna publikation i ny flik eller fönster >>Edu-Mphy: A Low-Cost Multi-Physiological Recording System for Education and Research in Healthcare and Engineering
2023 (Engelska)Ingår i: Abstracts: Medicinteknikdagarna 2023, 2023, s. 117-117Konferensbidrag, Muntlig presentation med publicerat abstract (Övrigt vetenskapligt)
Nationell ämneskategori
Datorsystem Medicinteknik
Identifikatorer
urn:nbn:se:mdh:diva-64768 (URN)
Konferens
Medicinteknikdagarna 2023, Stockholm, Sweden, 9-11 oktober, 2023
Tillgänglig från: 2023-11-17 Skapad: 2023-11-17 Senast uppdaterad: 2023-11-29Bibliografiskt granskad
Abdelakram, H. & Abdullah, S. (2023). Estimating Physiological Parameters in Various Age Groups: Windkessel 4 Element Model and PPG Waveform Analysis Approach. In: IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023: . Paper presented at 2023 IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023, Beirut, Lebanon, 12-14 December, 2023 (pp. 194-197). IEEE
Öppna denna publikation i ny flik eller fönster >>Estimating Physiological Parameters in Various Age Groups: Windkessel 4 Element Model and PPG Waveform Analysis Approach
2023 (Engelska)Ingår i: IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023, IEEE, 2023, s. 194-197Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Non-invasive monitoring of cardiovascular health through photoplethysmography (PPG) waveforms has emerged as a crucial area of research. The Windkessel 4-Element (WK4) model is a mathematical approach used to estimate key physiological parameters related to cardiovascular health, including arterial compliance, peripheral resistance, inertance, and total arterial resistance. This study aimed to evaluate key physiological parameters associated with cardiovascular health using the WK4 model, leveraging real-life PPG waveform data obtained from volunteers across three distinct age groups. To achieve this, an algorithm was developed to automatically determine optimal parameter values for each volunteer. The results revealed a mean correlation coefficient of 0.96 between the automatically generated waveforms by the algorithm and the actual real-life PPG waveforms, indicating robust agreement. Notably, only the total arterial resistance parameter exhibited significant differences among the age groups, suggesting that the algorithm holds promise for detecting agerelated changes in cardiovascular health. These findings emphasize the potential for the development of a non-invasive tool to assess cardiovascular health status and enhance healthcare outcomes. Furthermore, they underscore the capability of the developed algorithm as a non-invasive means to evaluate various aspects of cardiovascular physiology. Additionally, the versatility of this algorithm opens doors for its application in educational settings, promoting knowledge advancement, empowering research endeavors, and facilitating advancements in the field.

Ort, förlag, år, upplaga, sidor
IEEE, 2023
Nyckelord
Arterial properties, Cardiovascular health, Hemodynamic parameters, Photoplethysmography, Windkessel 4 Element model, Parameter estimation, Physiological models, Waveform analysis, Age groups, Arterial property, Element models, Physiological parameters, Property, Waveforms, Windkessel
Nationell ämneskategori
Kardiologi
Identifikatorer
urn:nbn:se:mdh:diva-65796 (URN)10.1109/IMCET59736.2023.10368236 (DOI)2-s2.0-85182926822 (Scopus ID)9798350313826 (ISBN)
Konferens
2023 IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023, Beirut, Lebanon, 12-14 December, 2023
Tillgänglig från: 2024-01-31 Skapad: 2024-01-31 Senast uppdaterad: 2024-01-31Bibliografiskt granskad
Abdelakram, H., Abdullah, S., Lindén, M., Kristoffersson, A. & Folke, M. (2023). Impact of Activities in Daily Living on Electrical Bioimpedance Measurements for Bladder Monitoring. In: : . Paper presented at 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), 22-24 June 2023, L'Aquila, Italy.
Öppna denna publikation i ny flik eller fönster >>Impact of Activities in Daily Living on Electrical Bioimpedance Measurements for Bladder Monitoring
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2023 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Accurate bladder monitoring is critical in the management of conditions such as urinary incontinence, voiding dysfunction, and spinal cord injuries. Electrical bioimpedance (EBI) has emerged as a cost-effective and non-invasive approach to monitoring bladder activity in daily life, with particular relevance to patient groups who require measurement of bladder urine volume (BUV) to prevent urinary leakage. However, the impact of activities in daily living (ADLs) on EBI measurements remains incompletely characterized. In this study, we investigated the impact of normal ADLs such as sitting, standing, and walking on EBI measurements using the MAX30009evkit system with four electrodes placed on the lower abdominal area. We developed an algorithm to identify artifacts caused by the different activities from the EBI signals. Our findings demonstrate that various physical activities clearly affected the EBI measurements, indicating the necessity of considering them during bladder monitoring with EBI technology performed during physical activity (or normal ADLs). We also observed that several specific activities could be distinguished based on their impedance values and waveform shapes. Thus, our results provide a better understanding of the impact of physical activity on EBI measurements and highlight the importance of considering such physical activities during EBI measurements in order to enhance the reliability and effectiveness of EBI technology for bladder monitoring.

Nationell ämneskategori
Medicinteknik
Identifikatorer
urn:nbn:se:mdh:diva-64033 (URN)10.1109/CBMS58004.2023.00316 (DOI)001037777900135 ()2-s2.0-85166470920 (Scopus ID)979-8-3503-1224-9 (ISBN)
Konferens
2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), 22-24 June 2023, L'Aquila, Italy
Tillgänglig från: 2023-08-16 Skapad: 2023-08-16 Senast uppdaterad: 2024-03-06Bibliografiskt granskad
Abdullah, S., Kanwal, K., Hafid, A. & Difallah, S. (2023). Low-cost BLE based intravenous monitoring and control infusion system. In: Int. Conf. Adv. Electron., Control Commun. Syst., ICAECCS: . Paper presented at 2023 International Conference on Advances in Electronics, Control and Communication Systems, ICAECCS 2023. Institute of Electrical and Electronics Engineers Inc.
Öppna denna publikation i ny flik eller fönster >>Low-cost BLE based intravenous monitoring and control infusion system
2023 (Engelska)Ingår i: Int. Conf. Adv. Electron., Control Commun. Syst., ICAECCS, Institute of Electrical and Electronics Engineers Inc. , 2023Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Administering the medications and fluids intravenously is a frequent practice in modern medical procedures, which plays a vital role in the treatment of certain acute conditions which require immediate action by drugs or fluids. This paper covers the design of a low-cost, wireless drip monitoring system for use in the hospital environment. The device is equipped with the Bluetooth low energy based battery-operated microcontroller, an infrared based drops counting system and a digital servo motor to control the drip flow rate, and it is attached to an existing intravenous stand. A LabView graphical user interface has also been developed to provide sets of input to the system to calculate the desired drip rate and the amount of pressure that digital servo motor must apply to achieve it. The system shows an average accuracy of 96% when compared with the measured and calculated values. This allows accurate computation of the level of the drip.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers Inc., 2023
Nyckelord
Biomedical, embedded system, intravenous infusion, IoT, remote monitoring, Controlled drug delivery, Costs, Embedded systems, Internet of things, Embedded-system, Infusion systems, Low-costs, Medical procedures, Monitoring and control, Servo-motor, Graphical user interfaces
Nationell ämneskategori
Reglerteknik
Identifikatorer
urn:nbn:se:mdh:diva-62594 (URN)10.1109/ICAECCS56710.2023.10104683 (DOI)2-s2.0-85158942132 (Scopus ID)9781665463102 (ISBN)
Konferens
2023 International Conference on Advances in Electronics, Control and Communication Systems, ICAECCS 2023
Tillgänglig från: 2023-05-29 Skapad: 2023-05-29 Senast uppdaterad: 2023-05-29Bibliografiskt granskad
Riaz, Z., Khan, B., Abdullah, S., Khan, S. & Islam, M. S. (2023). Lung Tumor Image Segmentation from Computer Tomography Images Using MobileNetV2 and Transfer Learning. Bioengineering, 10(8), Article ID 981.
Öppna denna publikation i ny flik eller fönster >>Lung Tumor Image Segmentation from Computer Tomography Images Using MobileNetV2 and Transfer Learning
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2023 (Engelska)Ingår i: Bioengineering, E-ISSN 2306-5354, Vol. 10, nr 8, artikel-id 981Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Background: Lung cancer is one of the most fatal cancers worldwide, and malignant tumors are characterized by the growth of abnormal cells in the tissues of lungs. Usually, symptoms of lung cancer do not appear until it is already at an advanced stage. The proper segmentation of cancerous lesions in CT images is the primary method of detection towards achieving a completely automated diagnostic system. Method: In this work, we developed an improved hybrid neural network via the fusion of two architectures, MobileNetV2 and UNET, for the semantic segmentation of malignant lung tumors from CT images. The transfer learning technique was employed and the pre-trained MobileNetV2 was utilized as an encoder of a conventional UNET model for feature extraction. The proposed network is an efficient segmentation approach that performs lightweight filtering to reduce computation and pointwise convolution for building more features. Skip connections were established with the Relu activation function for improving model convergence to connect the encoder layers of MobileNetv2 to decoder layers in UNET that allow the concatenation of feature maps with different resolutions from the encoder to decoder. Furthermore, the model was trained and fine-tuned on the training dataset acquired from the Medical Segmentation Decathlon (MSD) 2018 Challenge. Results: The proposed network was tested and evaluated on 25% of the dataset obtained from the MSD, and it achieved a dice score of 0.8793, recall of 0.8602 and precision of 0.93. It is pertinent to mention that our technique outperforms the current available networks, which have several phases of training and testing.

Ort, förlag, år, upplaga, sidor
Multidisciplinary Digital Publishing Institute (MDPI), 2023
Nyckelord
CT, deep learning, lung cancer, medical imaging, MobileNetV2, pulmonary nodule, UNET
Nationell ämneskategori
Medicinsk bildbehandling
Identifikatorer
urn:nbn:se:mdh:diva-64171 (URN)10.3390/bioengineering10080981 (DOI)001057600300001 ()2-s2.0-85169124977 (Scopus ID)
Tillgänglig från: 2023-09-06 Skapad: 2023-09-06 Senast uppdaterad: 2023-12-04Bibliografiskt granskad
Organisationer
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0003-4841-2488

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