AudioHive
The aim of this study is to investigate novel approaches using audio signal.
The current state-of-the-art in assisted living relies on a blend of wearable sensing technologies (smart watches, wristbands) and location tracking technologies embedded in the existing environment. Nevertheless, real-world deployments of wearable technologies have had only limited success for the elderly. The aim on this study is to explore a new paradigm where the daily activities of people are monitored passively through sensing technologies that are not embedded within environment, without the need of any form of wearable device or active use intervention.
To achieve this, we intend to run this data collection with 20 healthy participants, and we are going to use the labelled audio data we collected to build a Machine Learning Algorithm. The aim of the algorithm is to detect daily activities in a single occupancy household with the future aim of applying it in the context of elderly individuals to monitor their wellbeing (although this is not the focus of the current study).
To reach that point, we aim to run an initial study involving healthy individuals who are asked to generate acoustic data for their daily activities.
Please download the iOS or Android App and do the data collection