Ibrahim received the BSc degree in biomedical engineering from the Biomedical Engineering Dept, Helwan University, Egypt, in 2010, and the Joint master’s degree in computer vision and robotics in 2014. He received a Ph.D. degree from the University of Montpellier, France, in 2018.
Multi-Modal Depression Monitoring System Merna Youssef, Omar Abdelazeez, Kareem Hassan, Merna Bibars, Lamees N. Mahmoud, et al. 2025 International Telecommunications Conference Itc Egypt 2025, 2025
Lessons Learned From the Integration of Ambient Assisted Living Technologies in Older Adults' Care: Longitudinal Mixed Methods Study Oteng Ntsweng, Martin Kodyš, Zhi Quan Ong, Fang Zhou, Antoine de Marassé-Enouf, et al. Jmir Rehabilitation and Assistive Technologies, 2025 Background COVID-19 has given impetus to an already growing trend around the use of ambient assisted living (AAL) technologies to support frail older adults who live alone. However, the challenge is that systematic research on the long-term use of AAL technologies remains in its nascent stages, leaving gaps in the understanding of the predictors that contribute to the routine embedding of AAL technologies in older adults’ care. Objective This paper aims to share key lessons from a longitudinal study on the routine embedding of AAL technologies in older adults’ care within a hitherto under-studied Southeast Asian context. Our objective was to design and deploy an AAL system termed Ubiquitous Service Management and Reasoning Architecture (Ubismart), evaluate its impact on older adults’ quality of life (QOL), and distill lessons to inform the sustainable and culturally sensitive adoption of AAL technologies in similar settings. Methods We conducted an in-depth case study using a mixed methods design. First, we designed and deployed Ubismart to unobtrusively monitor and visualize older adults’ activities of daily living. To assess changes in QOL, we administered a simplified, gamified version of the validated Older People’s Quality of Life Questionnaire. Finally, we conducted semistructured interviews with older adults and their caregivers to triangulate the quantitative findings and explore evolving perceptions of the technology and its integration into daily routines. Results Quantitative analysis revealed significant improvements in (1) psychological and emotional well-being (P=.01) and (2) leisure and social activities (P=.03) following the AAL intervention. Other QOL dimensions showed no statistically significant change. Qualitative findings reinforced the improvement in psychological and emotional well-being, with many participants describing a heightened sense of safety and peace of mind, often likening the technology to “insurance” or a silent companion. However, the impact on social relationships was paradoxical; some older adults felt more cared for, while others perceived a decline in in-person visits. This paradox highlighted the complexities of technology’s role in caregiving, as it might simultaneously enhance feelings of safety while unintentionally diminishing social connection for some older adults. Conclusions AAL technologies such as Ubismart enhance older adults’ psychological and emotional well-being and sense of safety but may inadvertently reduce social interaction. Sustainable integration requires balancing these benefits with efforts to maintain meaningful caregiver connections, supporting both safety and social engagement for older adults. Trial Registration ClinicalTrials.gov NCT06486935; https://clinicaltrials.gov/study/NCT06486935
AI-Based Communication Tool for High-Functioning Autistic Children Farah Ossama, Fatmah Issam, Menna Hesham, Menna Kamel, Yumna Hamdy, et al. 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare Medicine and Biology Ieeeconf 2023, 2023
From raw clinical data to robust prediction: an AI framework for early lymphedema detection I Sadek, SU Rehman, A Gehad, EG Eltasawi, A AbdelKader, ... BMC Medical Research Methodology , 2026 2026
Machine learning–driven stress detection in biomedical engineering applications I Sadek, MA Al-Alim, N Salem, R Mubarak Emerging Technologies in the Healthcare System for Sustainable Development … , 2026 2026
Multi-Modal Depression Monitoring System M Youssef, O Abdelazeez, K Hassan, M Bibars, LN Mahmoud, I Sadek 2025 International Telecommunications Conference (ITC-Egypt), 778-783 , 2025 2025
Emotion Recognition from EEG Signals Using Vision Transformer and CNN M Mansour, LN Mahmoud, I Sadek, NM Salem 2025 International Telecommunications Conference (ITC-Egypt), 259-264 , 2025 2025
Lessons Learned From the Integration of Ambient Assisted Living Technologies in Older Adults’ Care: Longitudinal Mixed Methods Study O Ntsweng, M Kodyš, ZQ Ong, F Zhou, A Marassé-Enouf, I Sadek, ... JMIR Rehabilitation and Assistive Technologies 12, e57989 , 2025 2025 Citations: 6
From Lab to Real-Life: A Three-Stage Validation of Wearable Technology for Stress Monitoring BA Darwish, SU Rehman, I Sadek, NM Salem, G Kareem, LN Mahmoud MethodsX, 103205 , 2025 2025 Citations: 22
Sleep Stages Classification Using ECG Signals and Deep Learning: A Comparative Study H Ahmed, NM Salem, I Sadek, LN Mahmoud 2024 International Conference on Computer and Applications (ICCA), 1-4 , 2024 2024 Citations: 1
Focal Adhesions Segmentation Using Deep Learning IE Mohamed, NM Salem, I Sadek, LN Mahmoud 2024 International Conference on Computer and Applications (ICCA), 01-05 , 2024 2024 Citations: 1
A deep learning approach using wesad data for multi-class classification with wearable sensors M Abd Al Aleem, R Mubarak, NM Salem, I Sadek 2024 6th Novel Intelligent and Leading Emerging Sciences Conference (NILES … , 2024 2024 Citations: 10
Enhanced DeepPhys: Leveraging Deep Learning for Heart Rate Detection from Facial Videos ES Abdelwahab, I Sadek, NM Salem, LN Mahmoud 2024 6th Novel Intelligent and Leading Emerging Sciences Conference (NILES … , 2024 2024 Citations: 2
A machine learning approach for pain detection using physiological signals MH Abdelgawad, AM Abdullah, SM El-Sherif, NE Elbasuony, YA Osman, ... 2024 6th Novel Intelligent and Leading Emerging Sciences Conference (NILES … , 2024 2024 Citations: 2
Multimodal machine learning approach for emotion recognition using physiological signals MA Ramadan, NM Salem, LN Mahmoud, I Sadek Biomedical Signal Processing and Control 96, 106553 , 2024 2024 Citations: 28
A machine-learning approach for stress detection using wearable sensors in free-living environments M Abd Al-Alim, R Mubarak, NM Salem, I Sadek Computers in Biology and Medicine 179, 108918 , 2024 2024 Citations: 108
Evaluating the Potential of Wearable Technology in Early Stress Detection: A Multimodal Approach BA Darwish, NM Salem, G Kareem, LN Mahmoud, I Sadek medRxiv, 2024.07. 19.24310732 , 2024 2024 Citations: 4
AI-based tool for early detection of Alzheimer's disease SU Rehman, N Tarek, C Magdy, M Kamel, M Abdelhalim, A Melek, ... Heliyon 10 (8) , 2024 2024 Citations: 44
Deep neural network based for stress detection M Abd Al-Alim, R Mubarak, NM Salem, I Sadek Procedia Computer Science 246, 3178-3187 , 2024 2024 Citations: 6
Iot-Based Emergency Cardiac Death Risk Rescue Alert System SU Rehman, B Huang, S Manickam, I Sadek Available at SSRN 4811194 , 2024 2024 Citations: 5
AI-based communication tool for high-functioning autistic children F Ossama, F Issam, M Hesham, M Kamel, Y Hamdy, M Bibars, I Sadek 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in … , 2023 2023 Citations: 2
Contactless remote monitoring of sleep: evaluating the feasibility of an under-mattress sensor mat in a real-life deployment I Sadek, B Abdulrazak Health Systems 12 (3), 264-280 , 2023 2023 Citations: 13
Prosthetic arm using EEG control signals based on deep convolutional neural network A Mostafa, F Mostafa, S Ahmed The International Undergraduate Research Conference 6 (6), 1-7 , 2022 2022 Citations: 2
MOST CITED SCHOLAR PUBLICATIONS
Ballistocardiogram signal processing: a review I Sadek, J Biswas, B Abdulrazak Health information science and systems 7 (1), 10 , 2019 2019 Citations: 295
A machine-learning approach for stress detection using wearable sensors in free-living environments M Abd Al-Alim, R Mubarak, NM Salem, I Sadek Computers in Biology and Medicine 179, 108918 , 2024 2024 Citations: 108
Nonintrusive vital signs monitoring for sleep apnea patients: a preliminary study I Sadek, E Seet, J Biswas, B Abdulrazak, M Mokhtari IEEE Access 6, 2506-2514 , 2017 2017 Citations: 102
Discrimination of retinal images containing bright lesions using sparse coded features and SVM D Sidibé, I Sadek, F Mériaudeau Computers in biology and medicine 62, 175-184 , 2015 2015 Citations: 77
Privacy and security of IoT based healthcare systems: concerns, solutions, and recommendations I Sadek, SU Rehman, J Codjo, B Abdulrazak International conference on smart homes and health telematics, 3-17 , 2019 2019 Citations: 67
Nonintrusive heart rate measurement using ballistocardiogram signals: a comparative study I Sadek, J Biswas Signal, Image and Video Processing 13 (3), 475-482 , 2019 2019 Citations: 50
Internet of things for sleep tracking: wearables vs. nonwearables I Sadek, A Demarasse, M Mokhtari Health and technology 10 (1), 333-340 , 2020 2020 Citations: 49
Continuous and unconstrained vital signs monitoring with ballistocardiogram sensors in headrest position I Sadek, J Biswas, B Abdulrazak, Z Haihong, M Mokhtari 2017 IEEE EMBS International Conference on Biomedical & Health Informatics … , 2017 2017 Citations: 49
A new approach for detecting sleep apnea using a contactless bed sensor: Comparison study I Sadek, TTS Heng, E Seet, B Abdulrazak Journal of medical Internet research 22 (9), e18297 , 2020 2020 Citations: 47
Security and privacy in the Internet of Things healthcare systems: Toward a robust solution in real-life deployment I Sadek, J Codjo, SU Rehman, B Abdulrazak Computer Methods and Programs in Biomedicine Update 2, 100071 , 2022 2022 Citations: 46
AI-based tool for early detection of Alzheimer's disease SU Rehman, N Tarek, C Magdy, M Kamel, M Abdelhalim, A Melek, ... Heliyon 10 (8) , 2024 2024 Citations: 44
A comparison of three heart rate detection algorithms over ballistocardiogram signals I Sadek, B Abdulrazak Biomedical Signal Processing and Control 70 (103017) , 2021 2021 Citations: 42
Automatic discrimination of color retinal images using the bag of words approach I Sadek, D Sidibé, F Meriaudeau Medical Imaging 2015: Computer-Aided Diagnosis 9414, 398-405 , 2015 2015 Citations: 42
Nonintrusive remote monitoring of sleep in home-based situation I Sadek, M Mohktari Journal of medical systems 42 (4), 64 , 2018 2018 Citations: 38
Automatic heart rate detection from FBG sensors using sensor fusion and enhanced empirical mode decomposition I Sadek, J Biswas, VFS Fook, M Mokhtari 2015 IEEE International Symposium on Signal Processing and Information … , 2015 2015 Citations: 32
Multimodal machine learning approach for emotion recognition using physiological signals MA Ramadan, NM Salem, LN Mahmoud, I Sadek Biomedical Signal Processing and Control 96, 106553 , 2024 2024 Citations: 28
Automatic classification of bright retinal lesions via deep network features I Sadek, M Elawady, AER Shabayek arXiv preprint arXiv:1707.02022 , 2017 2017 Citations: 25
From Lab to Real-Life: A Three-Stage Validation of Wearable Technology for Stress Monitoring BA Darwish, SU Rehman, I Sadek, NM Salem, G Kareem, LN Mahmoud MethodsX, 103205 , 2025 2025 Citations: 22
Automatic Nonlinear Filtering and Segmentation for Breast Ultrasound Images M Elawady, I Sadek, AER Shabayek, G Pons, S Ganau International Conference Image Analysis and Recognition, 206-213 , 2016 2016 Citations: 21
Novel Unobtrusive Approach for Sleep Monitoring Using Fiber Optics in an Ambient Assisted Living Platform I Sadek, J Bellmunt, M Kodys, B Abdulrazak, M Mokhtari Smart Homes and Health Telematics 10461, 48–60 , 2017 2017 Citations: 18