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Smart Assistant for Alzheimer's Patients

Description:

The elderly, particularly those over 60 years old, often complain about difficulties with cognitive and routine tasks, particularly those related to memory. While this is often considered a natural part of aging, it can also be an early indication of Alzheimer's disease, which has a range of symptoms that can severely impact memory and cognitive function. Alzheimer's is the most common cause of dementia, accounting for 60-80% of cases. In 2011, approximately 33.9 million people worldwide suffered from Alzheimer's, and according to the World Health Organization, nearly 66 million and 115 million people are predicted to be affected by Alzheimer's by 2030 and 2050, respectively. Alzheimer's presents serious problems, including increasing healthcare costs due to the need for skilled nursing care and healthcare at home. In addition, patients face difficulties during the acute stages of the disease, such as difficulty recognizing familiar faces, objects, and even family members. This can severely impact their communication and quality of life. Finally, patients suffering from Alzheimer's may forget important daily tasks, such as taking medication at the right time, which can lead to further health complications. Our invention addresses these challenges and assists patients with Alzheimer's in taking their medication on time, recognizing familiar faces and objects, and completing daily tasks. It is a smart assistant that communicates with elderly patients and helps to minimize the financial costs and irreversible risks associated with the disease. Solutions: Our invention can be used in medical centers, particularly nursing homes for patients with Alzheimer's. It takes the form of glasses that accompany patients, with camera lenses installed on the center or corner of the frame. These cameras connect via Bluetooth or wireless to smart devices such as a smartwatch, allowing patients to correctly recognize objects through a QR-code reader sensor and to recognize familiar faces and voices through a face detection sensor and voice detection module.

Organisation: 1. Isfahan University of Medical Science, Isfahan, Iran. 2. Omron Electric, Mashhad, Iran.

Innovator(s): Sonia Zehtab, Pouria Rezakhah Khadem

Category: Medicine, Biotechnology and Medical Devices

Country: Iran

Gold Award