A Wearable Platform as a First Step towards Enabling Collective Intelligence in Alzheimer's Disease Management: Feasibility Assessment on Healthy Volunteers

Abstract

The burden of Alzheimer's Disease (AD) extends to both patients and caregivers (CGs), necessitating effective management strategies. Non-pharmacological methods like the Walk and Talk Programs have shown promise in enhancing their quality of life. The interactions between patient and CGs and their psychophysical load may influence the adherence to the program, but they still lack an objective evaluation. The assessment of these aspects, aligning with the principles of Collective Intelligence (CI), can foster their refinement with consequent superior outcomes. Wearable systems may intervene to monitor parameters related to the patient-CGs psychophysical load with a good acceptance among AD patients. We proposed a multiparametric wearable system embedding two inertial measurement unit (IMU) sensors to monitor key elements in CI, such as heart rate (HR), respiratory rate (RR) and activity level (LA). The feasibility of the whole system was assessed in a pilot study on eight volunteers, replicating patient-CG interactions typical of the Walk and Talk Program. Results showed low mean percentage errors for HR and RR estimations, validated against a reference chest strap. Dynamic conditions notably captured group dynamics, consistently detecting LAs of the subjects. In summary, our study laid the foundation for a more comprehensive and efficacious AD management approach.

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