EIP on AHA Repository

Automated Audio Data Monitoring for a Social Robot in Ambient Assisted Living Environments

Keywords: Assisted Living, Audio Recognition, Elderly, Home Care, Robotics
FUNITEC – La Salle


Digital solution and service (e.g. application/digital health portal/platform/AI based system/etc.)
Short description
Human life expectancy has steadily grown over the last century, which has driven governments and institutions to increase the efforts on caring about the eldest segment of the population. Although this concern was initially addressed by building larger hospitals and retirement homes, these facilities have been rapidly overfilled and their associated maintenance costs are becoming far prohibitive. Therefore, modern trends attempt to take advantage of latest advances in technology and communications to remotely monitor those people with special needs at their own home, which boosts their life quality and has very few impact on their social lives. Nonetheless, this approach still requires a considerable amount of qualified medical personnel to track every patient at any time. The purpose of this paper is to present a social robot for assisted living that tracks patients status by automatically identifying and analyzing the acoustic events happening in a house. Specifically, we have taken benefit of the amazing capabilities of a Raspberry Pi together with a Nao robot to collect data inside a house and send it in realtime to the medical center. Conducted experiments verify the feasibility of our approach and open new research directions in this domain.
No impact-related evidence is currently available
The idea has been formulated and/or research and experiments are underway to test a “proof of concept”
Geographical scope
Submitted in other database or repository of digital health resources that is publicly available
https://futurium.ec.europa.eu/en/active-and-healthy-living-digital-world/library/eip-aha-repository-innovative-practices, EIPonAHA Repository of innovative practices

Additional information

to clinicians / care practitioners
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
to patients / citizens
Health data analytics (Artificial Intelligence/algorithm development and calibration/machine learning/risk stratification tools/etc.)
Robotics (e.g. companion robots)
Smart homes/independent living support/ambient assisted living technologies
Primary target patient group (age)
Older adults (65+)
Ready to be transferred to
Transferability has not been considered in a systematic way.