In this study, we developed a mobile application that will enable caregivers to continuously monitor the vital health, medication, activity, and location of the patients with MCI with a smart wristband while enabling them caregivers to track the progress of the disease by a machine learning model that predicts MMSE of the patient using speech

3-month vital health data collection has been performed on 30 participants who are over 60 years old via smart fitness wristbands distributed to them. A mobile application has been developed that caregivers can register their patients, wristbands and allow them to monitor their health data along with their location. medication and activities while synchronizing data anonymously to the application database.

The data collection has been performed with relatively cheap, simple Xiaomi MI Band 7 wristbands that track only HR, RHR, sleep, steps and move minutes due to reasonable price and light weight and easy wearability of these devices.

Mobile application synchronizes data from wristband to application servers continuously using Google Fit services that synchronize with device software. This made it possible for the patient's data to still be collected when he or she is not using any of them.

MMSE scores of patients were taken at the beginning and at the end of the 3 month period to correlate scores with the collected aggregated health data and patient information

Inclusion Criteria:

• Older patients who are willing to wear a smart wristband and have an Android smart phone

Exclusion Criteria:

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