Identifying and Monitoring the Daily Routine of Seniors Living at Home.

Area of Science:

• Gerontology
• Computer Science
• Ubiquitous Computing

Background:

• The aging population in Western countries necessitates innovative remote monitoring solutions for seniors.
• Integrating technology into daily living environments can support independent living and reduce caregiving demands.
• Establishing daily routines is crucial for seniors' well-being, offering benefits like reduced stress and enhanced security.

Purpose of the Study:

• To develop a system for identifying seniors' daily routines from monitored activities of daily living (ADL).
• To infer deviations from established routines that may signal a need for caregiver intervention.
• To enhance the safety, security, and independence of older adults through smart home monitoring.

Main Methods:

• A Markov model-based approach was employed to define and identify daily routines.
• Entropy rate and cosine functions were utilized to assess the similarity between daily activities and inferred routines.
• A distributed monitoring system incorporating Beacons and trilateration techniques was developed for real-time ADL tracking.

Main Results:

• The proposed techniques demonstrated high accuracy in identifying daily routines, with a confidence score of 0.98 for activity duration.
• The system effectively identified the sequence of activities within a narrow interval of [0.0794, 0.0829].
• Deviation identification achieved a best sensitivity of 0.88 and an average precision of 0.95.

Conclusions:

• The developed system reliably identifies seniors' daily routines and detects deviations, offering a valuable tool for remote care.
• This technology has the potential to significantly improve the quality of life for older adults by promoting self-management and timely interventions.
• The findings support the integration of smart monitoring systems in elder care to foster independence and reduce healthcare burdens.