A System for Real-time Privacy Preserving Data Collection for Ambient Assisted Living

Ambient Assisted Living (AAL) technologies are being developed which could assist elderly people to live healthy and active lives. These technologies have been used to monitor people's daily exercises, consumption of calories and sleeping patterns, and to provide coaching interventions to foster positive behaviour. Speech and audio processing can be used to complement such AAL technologies to inform interventions for healthy ageing by analyzing acoustic data captured in the user's home. However, collection of data in home settings present a number of challenges. One of the most pressing challenges concerns how to manage privacy and data protection. To address this issue, we have developed a low-cost system which can extract audio features while protecting the actual spoken content upon detection of voice activity, and store audio features for further processing which offer privacy guarantees. These privacy preserving features are being tested in the context of a larger project which includes health and well-being monitoring and coaching.