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South American Division

Adventist University in Argentina Develops Sensor System to Improve Elderly Care

The project uses sensors and wearable devices to detect falls and changes in daily routines while protecting user privacy.

March 20, 2026

Argentina

Oscar González, South American Division, and ANN
Industrial engineer Rafael Vargas, a researcher at River Plate Adventist University, is leading the development of a system of sensors and smart devices.

Industrial engineer Rafael Vargas, a researcher at River Plate Adventist University, is leading the development of a system of sensors and smart devices.

Photo: River Plate Adventist University

At River Plate Adventist University (UAP), a research project is exploring how technology can improve care for older adults living alone. The initiative is led by industrial engineer Rafael Vargas, a professor and researcher at the Faculty of Economics and Administration (FACEA).

The project focuses on developing a system of sensors and smart devices designed to detect falls and identify changes in daily routines.

Researchers say the initiative responds to the growing challenge of an aging population and the need for solutions that support older adults without compromising their independence or privacy.

“Many times, older adults live alone or spend several hours a day without company. If a fall or some other incident occurs, it can take a long time before anyone finds out,” she noted.

Sensors track activity patterns

The system uses a combination of sensors installed in the home to monitor movement, transitions between rooms, and levels of physical activity. This data allows researchers to establish patterns of daily behavior.

By analyzing these patterns, the system can detect anomalies such as prolonged inactivity or unusual movement, which may indicate a potential risk.

Privacy-focused technology

A key feature of the project is its emphasis on privacy. Unlike some monitoring systems, the technology does not rely on cameras or audio recording.

"The information is obtained from motion sensors, accelerometers, and other measurements that allow us to identify activity patterns without recording images or conversations," the researcher explained.

The system also integrates data from wearable devices, such as smartwatches, to improve accuracy. By combining multiple data sources, researchers aim to reduce false alerts caused by routine activities like climbing stairs or completing household tasks.

Ongoing development

The research team has developed initial prototypes using low-cost, commercially available sensors that have been adapted for improved performance. Current efforts are focused on refining data analysis to better identify critical events, such as falls or sudden disruptions in routine.

If a potential emergency is detected, the system could send alerts to family members or caregivers, allowing for a faster response.

Researchers say the long-term goal is to provide a practical tool that enhances safety and quality of life for older adults, particularly those living alone.

The original article was published on the South American Division Spanish news site.

Oscar González, South American Division, and ANN

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