Abstract
The world is facing an aging population, and the number of older people suffering from amnesia is increasing year by year. This group of patients is prone to medication errors in daily life due to cognitive decline, which poses a threat to their health. At the same time, the children of the patients find it difficult to accompany and supervise all the time due to the pressures of life. However, at present, both traditional methods and intelligent hardware are infeasible to directly and effectively monitor the medication taking of the amnesic elderly. To address the above problems, we designed an interactive system that utilizes face, arm motion, and character recognition techniques in computer vision to monitor the taking of medication by older people with amnesia. The system includes an on-site medication-taking detection, an on-site interaction, and a remote interaction unit. Besides, it is equipped with the functions of automatically detecting, reminding, and assisting the elderly in taking medication. In the specific test, we recruited 20 older people over 60 years old who suffer from amnesia to monitor their medication and found that the system can timely and accurately monitor the medication status of the elderly, effectively preventing the health problems caused by the elderly's missing of medication, and provide a certain contribution to the social care of the elderly.
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Qian, S., Yang, Y. (2024). Medication Monitoring Interactive System Based on Human Body Feature Points and Label Recognition. In: Stephanidis, C., Antona, M., Ntoa, S., Salvendy, G. (eds) HCI International 2024 Posters. HCII 2024. Communications in Computer and Information Science, vol 2115. Springer, Cham. https://doi.org/10.1007/978-3-031-61947-2_23
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DOI: https://doi.org/10.1007/978-3-031-61947-2_23
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