HCCVNov 5, 2013

Motion and audio analysis in mobile devices for remote monitoring of physical activities and user authentication

arXiv:1311.1132v14 citations
Originality Synthesis-oriented
AI Analysis

This addresses remote healthcare monitoring for the elderly and implicit security for mobile users, but it is incremental as it builds on existing accelerometer-based techniques.

The paper tackles remote monitoring of physical activities using smartphone accelerometers, proposing a cost-effective method for healthcare and extending it to implicit security by detecting unexpected movements for automatic phone locking and continuous user authentication.

In this article we propose the use of accelerometer embedded by default in smartphone as a cost-effective, reliable and efficient way to provide remote physical activity monitoring for the elderly and people requiring healthcare service. Mobile phones are regularly carried by users during their day-to-day work routine, physical movement information can be captured by the mobile phone accelerometer, processed and sent to a remote server for monitoring. The acceleration pattern can deliver information related to the pattern of physical activities the user is engaged in. We further show how this technique can be extended to provide implicit real-time security by analysing unexpected movements captured by the phone accelerometer, and automatically locking the phone in such situation to prevent unauthorised access. This technique is also shown to provide implicit continuous user authentication, by capturing regular user movements such as walking, and requesting for re-authentication whenever it detects a non-regular movement.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes