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Abdelakram, Hafid
Alternative names
Publications (9 of 9) Show all publications
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.
Open this publication in new window or tab >>Comparing the Effectiveness of EMG and Electrical Impedance myography Measurements for Controlling Prosthetics
2023 (English)In: IEEE Int. Multidiscip. Conf. Eng. Technol., IMCET, Institute of Electrical and Electronics Engineers Inc. , 2023, p. 189-193Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
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
National Category
Medical Materials
Identifiers
urn:nbn:se:mdh:diva-65803 (URN)10.1109/IMCET59736.2023.10368219 (DOI)2-s2.0-85182921540 (Scopus ID)9798350313826 (ISBN)
Conference
2023 IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023, Beirut, Lebanon, 12-14 December, 2023
Available from: 2024-01-31 Created: 2024-01-31 Last updated: 2024-01-31Bibliographically approved
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).
Open this publication in new window or tab >>Edu-Mphy: A Low-Cost Multi-Physiological Recording System for Education and Research in Healthcare and Engineering
2023 (English)In: Abstracts: Medicinteknikdagarna 2023, 2023, p. 117-117Conference paper, Oral presentation with published abstract (Other academic)
National Category
Computer Systems Medical Engineering
Identifiers
urn:nbn:se:mdh:diva-64768 (URN)
Conference
Medicinteknikdagarna 2023, Stockholm, Sweden, 9-11 oktober, 2023
Available from: 2023-11-17 Created: 2023-11-17 Last updated: 2023-11-29Bibliographically approved
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
Open this publication in new window or tab >>Estimating Physiological Parameters in Various Age Groups: Windkessel 4 Element Model and PPG Waveform Analysis Approach
2023 (English)In: IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023, IEEE, 2023, p. 194-197Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
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
National Category
Cardiac and Cardiovascular Systems
Identifiers
urn:nbn:se:mdh:diva-65796 (URN)10.1109/IMCET59736.2023.10368236 (DOI)2-s2.0-85182926822 (Scopus ID)9798350313826 (ISBN)
Conference
2023 IEEE 4th International Multidisciplinary Conference on Engineering Technology, IMCET 2023, Beirut, Lebanon, 12-14 December, 2023
Available from: 2024-01-31 Created: 2024-01-31 Last updated: 2024-01-31Bibliographically approved
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.
Open this publication in new window or tab >>Impact of Activities in Daily Living on Electrical Bioimpedance Measurements for Bladder Monitoring
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2023 (English)Conference paper, Published paper (Refereed)
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.

National Category
Medical Engineering
Identifiers
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)
Conference
2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS), 22-24 June 2023, L'Aquila, Italy
Available from: 2023-08-16 Created: 2023-08-16 Last updated: 2023-10-25Bibliographically approved
Abdullah, S., Abdelakram, H., Lindén, M., Folke, M. & Kristoffersson, A. (2023). Machine Learning-Based Classification of Hypertension using CnD Features from Acceleration Photoplethysmography and Clinical Parameters. In: Proceedings - IEEE Symposium on Computer-Based Medical Systems: . Paper presented at 36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023, Aquila, 22 June 2023 through 24 June 2023 (pp. 923-924). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Machine Learning-Based Classification of Hypertension using CnD Features from Acceleration Photoplethysmography and Clinical Parameters
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2023 (English)In: Proceedings - IEEE Symposium on Computer-Based Medical Systems, Institute of Electrical and Electronics Engineers Inc. , 2023, p. 923-924Conference paper, Published paper (Refereed)
Abstract [en]

Cardiovascular diseases (CVDs) are a leading cause of death worldwide, and hypertension is a major risk factor for acquiring CVDs. Early detection and treatment of hypertension can significantly reduce the risk of developing CVDs and related complications. In this study, a linear SVM machine learning model was used to classify subjects as normal or at different stages of hypertension. The features combined statistical parameters derived from the acceleration plethysmography waveforms and clinical parameters extracted from a publicly available dataset. The model achieved an overall accuracy of 87.50% on the validation dataset and 95.35% on the test dataset. The model's true positive rate and positive predictivity was high in all classes, indicating a high accuracy, and precision. This study represents the first attempt to classify cardiovascular conditions using a combination of acceleration photoplethysmogram (APG) features and clinical parameters The study demonstrates the potential of APG analysis as a valuable tool for early detection of hypertension.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
acceleration photoplethysmography, cardiovascular, fiducial points, hypertension, PPG, Acceleration, Classification (of information), Learning systems, Statistical tests, Support vector machines, Cardiovascular disease, Causes of death, Clinical parameters, Machine-learning, Photoplethysmogram, Photoplethysmography
National Category
Cardiac and Cardiovascular Systems Medical Engineering
Identifiers
urn:nbn:se:mdh:diva-63964 (URN)10.1109/CBMS58004.2023.00344 (DOI)001037777900162 ()2-s2.0-85166469701 (Scopus ID)9798350312249 (ISBN)
Conference
36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023, Aquila, 22 June 2023 through 24 June 2023
Available from: 2023-08-16 Created: 2023-08-16 Last updated: 2023-10-25Bibliographically approved
Abdullah, S., Hafid, A., Folke, M., Lindén, M. & Kristoffersson, A. (2023). PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points. Frontiers in Bioengineering and Biotechnology, 11, Article ID 1199604.
Open this publication in new window or tab >>PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points
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2023 (English)In: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 11, article id 1199604Article in journal (Refereed) Published
Abstract [en]

Photoplethysmography is a non-invasive technique used for measuring several vital signs and for the identification of individuals with an increased disease risk. Its principle of work is based on detecting changes in blood volume in the microvasculature of the skin through the absorption of light. The extraction of relevant features from the photoplethysmography signal for estimating certain physiological parameters is a challenging task, where various feature extraction methods have been proposed in the literature. In this work, we present PPGFeat, a novel MATLAB toolbox supporting the analysis of raw photoplethysmography waveform data. PPGFeat allows for the application of various preprocessing techniques, such as filtering, smoothing, and removal of baseline drift; the calculation of photoplethysmography derivatives; and the implementation of algorithms for detecting and highlighting photoplethysmography fiducial points. PPGFeat includes a graphical user interface allowing users to perform various operations on photoplethysmography signals and to identify, and if required also adjust, the fiducial points. Evaluating the PPGFeat’s performance in identifying the fiducial points present in the publicly available PPG-BP dataset, resulted in an overall accuracy of 99% and 3038/3066 fiducial points were correctly identified. PPGFeat significantly reduces the risk of errors in identifying inaccurate fiducial points. Thereby, it is providing a valuable new resource for researchers for the analysis of photoplethysmography signals.

Keywords
photoplethysmography, PPG features, fiducial points, MATLAB, toolbox, signal processing, acceleration photoplethysmography, velocity photoplethysmography
National Category
Medical Engineering
Identifiers
urn:nbn:se:mdh:diva-63035 (URN)10.3389/fbioe.2023.1199604 (DOI)001020124900001 ()2-s2.0-85163601193 (Scopus ID)
Available from: 2023-06-09 Created: 2023-06-09 Last updated: 2023-07-26Bibliographically approved
Abdullah, S., Abdelakram, H., Kristoffersson, A., Bilal Saeed, M. & Saad, S. (2023). Real-Time Portable Raspberry Pi-Based System for Sickle Cell Anemia Detection. In: Abstracts: Medicinteknikdagarna 2023. Paper presented at Medicinteknikdagarna 2023, Stockholm, Sweden, 9-11 oktober, 2023 (pp. 118-118).
Open this publication in new window or tab >>Real-Time Portable Raspberry Pi-Based System for Sickle Cell Anemia Detection
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2023 (English)In: Abstracts: Medicinteknikdagarna 2023, 2023, p. 118-118Conference paper, Oral presentation with published abstract (Other academic)
National Category
Computer Systems Medical Engineering
Identifiers
urn:nbn:se:mdh:diva-64765 (URN)
Conference
Medicinteknikdagarna 2023, Stockholm, Sweden, 9-11 oktober, 2023
Available from: 2023-11-17 Created: 2023-11-17 Last updated: 2023-11-29Bibliographically approved
Abdelakram, H., Gunnarsson, E., Ramos, A., Rödby, K., Abtahi, F., Bamidis, P. D., . . . Seoane, F. (2023). Sensorized T-Shirt with Intarsia-Knitted Conductive Textile Integrated Interconnections: Performance Assessment of Cardiac Measurements during Daily Living Activities. Sensors, 23(22), 9208-9208
Open this publication in new window or tab >>Sensorized T-Shirt with Intarsia-Knitted Conductive Textile Integrated Interconnections: Performance Assessment of Cardiac Measurements during Daily Living Activities
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2023 (English)In: Sensors, E-ISSN 1424-8220, Vol. 23, no 22, p. 9208-9208Article in journal (Refereed) Published
Abstract [en]

The development of smart wearable solutions for monitoring daily life health status is increasingly popular, with chest straps and wristbands being predominant. This study introduces a novel sensorized T-shirt design with textile electrodes connected via a knitting technique to a Movesense device. We aimed to investigate the impact of stationary and movement actions on electrocardiography (ECG) and heart rate (HR) measurements using our sensorized T-shirt. Various activities of daily living (ADLs), including sitting, standing, walking, and mopping, were evaluated by comparing our T-shirt with a commercial chest strap. Our findings demonstrate measurement equivalence across ADLs, regardless of the sensing approach. By comparing ECG and HR measurements, we gained valuable insights into the influence of physical activity on sensorized T-shirt development for monitoring. Notably, the ECG signals exhibited remarkable similarity between our sensorized T-shirt and the chest strap, with closely aligned HR distributions during both stationary and movement actions. The average mean absolute percentage error was below 3%, affirming the agreement between the two solutions. These findings underscore the robustness and accuracy of our sensorized T-shirt in monitoring ECG and HR during diverse ADLs, emphasizing the significance of considering physical activity in cardiovascular monitoring research and the development of personal health applications.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-65003 (URN)10.3390/s23229208 (DOI)001119563200001 ()38005593 (PubMedID)2-s2.0-85177759577 (Scopus ID)
Available from: 2023-12-12 Created: 2023-12-12 Last updated: 2024-01-23Bibliographically approved
Abdelakram, H., Difallah, S., Alves, C., Abdullah, S., Folke, M., Lindén, M. & Kristoffersson, A. (2023). State of the Art of Non-Invasive Technologies for Bladder Monitoring: A Scoping Review. Sensors, 23(5), Article ID 2758.
Open this publication in new window or tab >>State of the Art of Non-Invasive Technologies for Bladder Monitoring: A Scoping Review
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2023 (English)In: Sensors, E-ISSN 1424-8220, Vol. 23, no 5, article id 2758Article, review/survey (Refereed) Published
Abstract [en]

Bladder monitoring, including urinary incontinence management and bladder urinary volume monitoring, is a vital part of urological care. Urinary incontinence is a common medical condition affecting the quality of life of more than 420 million people worldwide, and bladder urinary volume is an important indicator to evaluate the function and health of the bladder. Previous studies on non-invasive techniques for urinary incontinence management technology, bladder activity and bladder urine volume monitoring have been conducted. This scoping review outlines the prevalence of bladder monitoring with a focus on recent developments in smart incontinence care wearable devices and the latest technologies for non-invasive bladder urine volume monitoring using ultrasound, optical and electrical bioimpedance techniques. The results found are promising and their application will improve the well-being of the population suffering from neurogenic dysfunction of the bladder and the management of urinary incontinence. The latest research advances in bladder urinary volume monitoring and urinary incontinence management have significantly improved existing market products and solutions and will enable the development of more effective future solutions.

National Category
Medical Engineering
Identifiers
urn:nbn:se:mdh:diva-62006 (URN)10.3390/s23052758 (DOI)000947664800001 ()36904965 (PubMedID)2-s2.0-85149769899 (Scopus ID)
Available from: 2023-03-03 Created: 2023-03-03 Last updated: 2023-05-10Bibliographically approved
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