Artificial Intelligence in Dementia Care: From Diagnostic Tools to Daily Living Assistance
Article Sidebar
Main Article Content
บทคัดย่อ
The goal of the present article is to provide a systematic analysis of all recent developments in Artificial Intelligence-based (AI) systems developed for the diagnosis and treatment of dementia. These AI-based systems are designed to support early detection, continuous assessment, and social support for dementia patients. While much attention has focused on using AI to detect and assess various forms of dementia, few researchers have examined how these AI-based systems can be used as part of a complete care process for people with dementia. Therefore, this study provides a detailed description of using AI as part of a complete care system for people with dementia. The methodological approach employed includes a clear definition of the selection criteria for articles included in the review. The results identify many ongoing challenges, limitations, and research needs related to using AI as part of a complete care system for people with dementia.
Downloads
Article Details
อนุญาตภายใต้เงื่อนไข Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
เอกสารอ้างอิง
Ajra, Z. B.; Xu, G.; Dray, J.; Montmain, J.; Perrey, S. Using Shallow Neural Networks with Functional Connectivity from EEG Signals for Early Diagnosis of Alzheimer’s and Frontotemporal Dementia. Front. Neurol. 2023, 14, 1270405. https://doi.org/10.3389/fneur.2023.1270405
Borchert, R.; Azevedo, T.; Badhwar, A.; Bernal, J.; Betts, M.; Bruffaerts, R.; Rittman, T. Artificial Intelligence for Diagnostic and Prognostic Neuroimaging in Dementia: A Systematic Review. Alzheimer’s Dement. 2023, 19(12), 5885–5904. https://doi.org/10.1002/alz.13412
Desai, C.; Dove, E.; Nanthakumar, J.; Main, E.; Colquhoun, H.; Astell, A.; Mihailidis, A.; Layton, N.; Burhan, A. M.; Chan, B.; Wang, R. H. Assistive Technology to Support Dementia Management: Protocol for a Scoping Review of Reviews. JMIR Res. Protoc. 2024, 13, 1–28. https://doi.org/10.2196/57036
Habbal, S.; Mian, M.; Imam, M.; Tahiri, J.; Amor, A.; Reddy, P. H. Harnessing Artificial Intelligence for Transforming Dementia Care: Innovations in Early Detection and Treatment. Brain Organoid Syst. Neurosci. J. 2025, 3, 122–133. https://doi.org/10.1016/j.bosn.2025.05.001
Ienca, M.; Jotterand, F.; Vică, C.; Elger, B. Social and Assistive Robotics in Dementia Care: Ethical Recommendations for Research and Practice. Int. J. Soc. Robot. 2016, 8, 565–573. https://doi.org/10.1007/s12369-016-0366-7
Khan, A. A.; Das, R. K.; Martin, A.; Dowling, D.; Imtiaz, R. Creating an Intelligent Dementia-Friendly Living Space: A Feasibility Study Integrating Assistive Robotics, Wearable Sensors, and Spatial Technology. In 2024 IEEE International Conference on e-Health and Bioengineering (EHB); 2024. https://doi.org/10.1109/HealthCom60970.2024.10880822
Kiselica, A. M.; Hermann, G. E.; Scullin, M. K.; Benge, J. F.; Kiselica, A. M. Technology That CARES: Enhancing Dementia Care through Assistive Technologies. Alzheimer’s Dement. 2024, 20(12), 8969–8978. https://doi.org/10.1002/alz.14192
Lin, Z.-J.; Chen, Y.-J.; Kuo, P.-C.; Huang, L.; Hu, C.-J.; Chen, C.-Y. Dementia Assessment Using Mandarin Speech with an Attention-Based Speech Recognition Encoder. arXiv 2023.
Steijger, D.; Christie, H.; Aarts, S.; IJsselsteijn, W.; Verbeek, H.; de Vugt, M. Use of Artificial Intelligence to Support Quality of Life of People with Dementia: A Scoping Review. Ageing Res. Rev. 2025, 108, 102741. https://doi.org/10.1016/j.arr.2025.102741
Shi, W.; Zhou, W.; Wang, R.; Shen, H.; Xu, N.; Wang, J. Exploring the Perceptions and Experiences of Caregivers with the Application of Socially Assistive Robots in Dementia Care: A Systematic Review of Qualitative Studies. Int. J. Nurs. Stud. 2025, 167, 105084. https://doi.org/10.1016/j.ijnurstu.2025.105084
Tree, J. J.; Jones, A. L. Exploring Insight into Unfamiliar Face Recognition Ability: The Case from Developmental Prosopagnosia. Cortex 2025, 186, 86–98. https://doi.org/10.1016/j.cortex.2025.03.009
Arco, J. E.; Gallego-Molina, N. J.; Ortiz, A.; Arroyo-Alvis, K.; López-Pérez, P. J. Identifying HRV Patterns in ECG Signals as Early Markers of Dementia. Expert Syst. Appl. 2023, 243, 122934. https://doi.org/10.1016/j.eswa.2023.122934
Chakraborty, M.; Naoal, N.; Momen, S.; Mohammed, N. ANALYZE-AD: A Comparative Analysis of Novel AI Approaches for Early Alzheimer’s Detection. Array 2024, 22, 100352. https://doi.org/10.1016/j.array.2024.100352
Al Amin, M.; Biswas, A. A Comprehensive Review of Explainable AI for Disease Diagnosis. Array 2024, 22, 100345. https://doi.org/10.1016/j.array.2024.100345
Yeasmin, N.; Al Amin, M.; Joti, T. J.; Aung, Z.; Azim, M. A. Advances of AI in Image-Based Computer-Aided Diagnosis: A Review. Array 2024, 23, 100357. https://doi.org/10.1016/j.array.2024.100357
Yadollahikhales, G.; Mandelli, M. L.; Ezzes, Z.; Pillai, J.; Ratnasiri, B.; Baquirin, D. P.; Miller, Z.; de Leon, J.; Tee, B. L.; Seeley, W.; Rosen, H.; Miller, B.; Kramer, J.; Sturm, V.; Gorno-Tempini, M. L.; Montembeault, M. Perceptual and Semantic Deficits in Face Recognition in Semantic Dementia. Neuropsychologia 2024, 205, 109020. https://doi.org/10.1016/j.neuropsychologia.2024.109020
Kim, K.; Jang, J.; Park, H.; Jeong, J.; Shin, D.; Shin, D. Detecting Abnormal Behaviors in Dementia Patients Using Lifelog Data: A Machine Learning Approach. Information 2023, 14(8), 433. https://doi.org/10.3390/info14080433
Alsubai, S.; Alqahtani, A.; Sha, M.; Abbas, S.; Gregus, M.; Furda, R. Automated Cognitive Health Assessment Based on Daily Life Functional Activities. Comput. Intell. Neurosci. 2023, 5684914. https://doi.org/10.1155/2023/5684914
Kantayeva, G.; Lima, J.; Pereira, A. I. Application of Machine Learning in Dementia Diagnosis: A Systematic Literature Review. Heliyon 2023, 9(11), e21626. https://doi.org/10.1016/j.heliyon.2023.e21626
Juneja, S.; Dhiman, G.; Kautish, S.; Viriyasitavat, W.; Yadav, K. A Perspective Roadmap for IoMT-Based Early Detection and Care of the Neural Disorder, Dementia. J. Healthc. Eng. 2021, 6712424. https://doi.org/10.1155/2021/6712424
Oishi, Y.; Imamura, T.; Shimomura, T.; Suzuki, K. Visual Texture Agnosia Influences Object Identification in Dementia with Lewy Bodies and Alzheimer’s Disease. Cortex 2020, 129, 23–32. https://doi.org/10.1016/j.cortex.2020.04.008
Hayhurst, J. How Augmented Reality and Virtual Reality Is Being Used to Support People Living with Dementia—Design Challenges and Future Directions. In Augmented Reality and Virtual Reality; 2018; pp 295–305. https://doi.org/10.1007/978-3-319-64027-3_20
Boumpa, E.; Gkogkidis, A.; Charalampou, I.; Ntaliani, A.; Kakarountas, A.; Kokkinos, V. An Acoustic-Based Smart Home System for People Suffering from Dementia. Technologies 2019, 7(1), 29. https://doi.org/10.3390/technologies7010029
Chandra, S. R.; Patwardhan, K.; Pai, A. R. Problems of Face Recognition in Patients with Behavioral Variant Frontotemporal Dementia. Indian J. Psychol. Med. 2017, 39(5), 653–658. https://doi.org/10.4103/IJPSYM.IJPSYM_90_17
Amiribesheli, M.; Bouchachia, A. Smart Homes Design for People with Dementia. In Proceedings of the 2015 International Conference on Intelligent Environments (IE); 2015; pp 156–159. https://doi.org/10.1109/IE.2015.33
Yu, C.; Sommerlad, A.; Sakure, L.; Livingston, G. Socially Assistive Robots for People with Dementia: Systematic Review and Meta-Analysis of Feasibility, Acceptability, and Effects on Cognition, Neuropsychiatric Symptoms and Quality of Life. Ageing Res. Rev. 2022, 78, 101633. https://doi.org/10.1016/j.arr.2022.101633
Nguyen, H.-D.; Clément, M.; Mansencal, B.; Coupé, P. 3D Transformer Based on Deformable Patch Location for Differential Diagnosis between Alzheimer’s Disease and Frontotemporal Dementia. In Machine Learning in Medical Imaging; 2023; pp 53–63. https://doi.org/10.1007/978-3-031-45676-3_6
Ouyang, X.; Shuai, X.; Li, Y.; Pan, L.; Zhang, X.; Fu, H.; Cheng, S.; Wang, X.; Cao, S.; Xin, J.; Yu, D. S. F.; Yan, Z. ADMarker: A Multi-Modal Federated Learning System for Monitoring Digital Biomarkers of Alzheimer’s Disease. In Proceedings of the 30th Annual International Conference on Mobile Computing and Networking; 2024; pp 404–419. https://doi.org/10.1145/3636534.3649370
Rudroff, T.; Rainio, O.; Klén, R. AI for the Prediction of Early Stages of Alzheimer’s Disease from Neuroimaging Biomarkers—A Narrative Review of a Growing Field. Neurol. Sci. 2024, 45, 5117–5127. https://doi.org/10.1007/s10072-024-07649-8
Hsieh, C. J.; Li, P. S.; Wang, C. H.; Lin, S. L.; Hsu, T. C.; Tsai, C. T. Socially Assistive Robots for People Living with Dementia in Long-Term Care Facilities: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Gerontology 2023, 69(8), 1027–1042. https://doi.org/10.1159/000529849
Wahul, R. M.; Ambadekar, S.; Dhanvijay, D. M.; Dudhedia, M. A.; Gaikwad, V.; Kanawade, B.; Pansare, J. R.; Bodkhe, B.; Gawande, S. H. Multimodal Approaches and AI-Driven Innovations in Dementia Diagnosis: A Systematic Review. Discover Artif. Intell. 2025, 5, 96. https://doi.org/10.1007/s44163-025-00358-x
Wurtz, H. M.; Manchester, M.; Valteau, T.; Hanson, H.; Scipion, C.; Federman, A.; Arias, J. J. Artificial Intelligence as a Tool for Cognitive Impairment Screening: Patient Perspectives about Benefits and Limitations. Alzheimer’s Dement.: Behav. Socioecon. Aging 2025, 1(1), 1–10. https://doi.org/10.1002/bsa3.70005
Yuan, F.; Hasnaeen, N.; Zhang, R.; Bible, B.; Taylor, J. R.; Qi, H.; Yao, F.; Zhao, X. Integrating Reinforcement Learning and AI Agents for Adaptive Robotic Interaction and Assistance in Dementia Care. arXiv 2025.
Mohammed, E. M.; Fakhrudeen, A. M.; Alani, O. Y. Detection of Alzheimer’s Disease Using Deep Learning Models: A Systematic Literature Review. Inform. Med. Unlocked 2024, 50, 101551. https://doi.org/10.1016/j.imu.2024.101551
Yadollahikhales, G.; Mandelli, M. L.; Ezzes, Z.; Pillai, J.; Ratnasiri, B.; Baquirin, D. P.; Miller, Z.; de Leon, J.; Tee, B. L.; Seeley, W.; Rosen, H.; Miller, B.; Kramer, J.; Sturm, V.; Gorno-Tempini, M. L.; Montembeault, M. Perceptual and Semantic Deficits in Face Recognition in Semantic Dementia. Neuropsychologia 2024, 205, 109020. https://doi.org/10.1016/j.neuropsychologia.2024.109020
Yeasmin, N.; Al Amin, M.; Joti, T. J.; Aung, Z.; Azim, M. A. Advances of AI in Image-Based Computer-Aided Diagnosis: A Review. Array 2024, 23, 100357. https://doi.org/10.1016/j.array.2024.100357
Kantayeva, G.; Lima, J.; Pereira, A. I. Application of Machine Learning in Dementia Diagnosis: A Systematic Literature Review. Heliyon 2023, 9(11), e21626. https://doi.org/10.1016/j.heliyon.2023.e21626
Zhang, C.; Tian, Y.; Capezuti, E. Privacy Preserving Automatic Fall Detection for Using RGBD Cameras. In Computers Helping People with Special Needs; 2012; Vol. 7382, pp 625–633. https://doi.org/10.1007/978-3-642-31522-0_95
Miller, M. F.; Rich, J. M.; Sliwinska, J. S. Impairments in the Face-Processing Network in Developmental Prosopagnosia and Semantic Dementia. Cogn. Behav. Neurol. 2015, 28(4), 188–197. https://doi.org/10.1097/WNN.0000000000000077
Thabtah, F.; Peebles, D.; Retzler, J.; Hathurusingha, C. Dementia Medical Screening Using Mobile Applications: A Systematic Review with a New Mapping Model. J. Biomed. Inform. 2020, 111, 103573. https://doi.org/10.1016/j.jbi.2020.103573
Ramirez, J. E. G.; Valerio, M. K. A.; Layug, J. R.; Santiago, C. S., Jr.; Ulanday, M. L. P.; Alabanza, J. E. Application of Expert Systems with Artificial Intelligence in the Medical Field: A Literature Review. Am. J. Sci. Technol. Res. 2025, 28(2). https://doi.org/10.55164/ajstr.v28i2.255684
Reddy, G. P.; Rohan, D.; Prakash, K. P.; Kumar, Y. V. P.; Chakravarthi, M. K. Artificial Intelligence-Based Approach for Chronic Kidney Disease Detection. Am. J. Sci. Technol. Res. 2025, 28(5). https://doi.org/10.55164/ajstr.v28i5.258012
Thepparak, S.; Wonglom, P.; Kaewsuksaeng, S.; Sunpapao, A. AI-Based Detection of Leaf Diseases in Durian (Durio zibethinus) Using Convolutional Neural Networks: Model Development and Performance Evaluation. Am. J. Sci. Technol. Res. 2026, 29(4). https://doi.org/10.55164/ajstr.v29i4.261309
Paculaba, A. M.; Palaoag, T. A Framework for a Geospatial Predictive Decision Support System for Hazard Risk Profiling. Am. J. Sci. Technol. Res. 2026, 29(4). https://doi.org/10.55164/ajstr.v29i4.261475
Tanthanawarakun, K.; Sugunnasil, P. Morphological Profiling of Lung Cancer through Explainable Machine Learning. Am. J. Sci. Technol. Res. 2025, 28(5). https://doi.org/10.55164/ajstr.v28i5.257888
García-Ceja, E.; Chen, C.; Sjöström, J.; Civitarese, S.; Aarts, E.; Iglesias, I.; Chen, N.; Rodríguez, J.; García, M.; Liljegren, L.; Smedberg, M.; Alarcón, A. Design and Implementation of a Smart Home in a Box to Monitor the Wellbeing of Residents with Dementia in Care Homes. Front. Digit. Health 2021, 3, 798889. https://doi.org/10.3389/fdgth.2021.798889
Li, R.; Wang, X.; Lawler, K.; Garg, S.; Bai, Q.; Alty, J. Applications of Artificial Intelligence to Aid Early Detection of Dementia: A Scoping Review on Current Capabilities and Future Directions. J. Biomed. Inform. 2022, 127, 104030. https://doi.org/10.1016/j.jbi.2022.104030
Nichols, E.; et al. Estimation of the Global Prevalence of Dementia in 2019 and Forecasted Prevalence in 2050: An Analysis for the Global Burden of Disease Study 2019. Lancet Public Health 2022, 7(2), 105–125. https://doi.org/10.1002/alz.051496
Chimamiwa, G.; Giaretta, A.; Alirezaie, M.; Pecora, F.; Loutfi, A. Are Smart Homes Adequate for Older Adults with Dementia? Sensors 2022, 22(11), 4254. https://doi.org/10.3390/s22114254
Zheng, C.; Bouazizi, M.; Ohtsuki, T.; Kitazawa, M.; Horigome, T.; Kishimoto, T. Detecting Dementia from Face-Related Features with Automated Computational Methods. Bioengineering 2023, 10(7), 862. https://doi.org/10.3390/bioengineering10070862
