Project

Electrocardiogram collection in noisy ambulatory environments with Android smartphone devices

Groups

The explosion of mHealth in both abundant and resource-constrained countries is both a cause for celebration and for concern. While mHealth clearly has the potential to deliver information and diagnostic decision support to the poorly trained, it is not appropriate to simply translate the technologies which the trained clinician uses into the hands of non-experts. In particular, it is important that the explosion of access does not lead to a flooding of the medical system with low quality data and false negatives. Clearly for mHealth to expand, a paradigm shift in how data is analysed must occur. Data must be vetted at the front end, using automated algorithms, to provide robust filtering of low quality data.

This project addresses the specific problem of vetting the quality of electrocardiograms (ECGs) collected by an untrained user in ambulatory scenarios using smartphone devices.

The explosion of mHealth in both abundant and resource-constrained countries is both a cause for celebration and for concern. While mHealth clearly has the potential to deliver information and diagnostic decision support to the poorly trained, it is not appropriate to simply translate the technologies which the trained clinician uses into the hands of non-experts. In particular, it is important that the explosion of access does not lead to a flooding of the medical system with low quality data and false negatives. Clearly for mHealth to expand, a paradigm shift in how data is analysed must occur. Data must be vetted at the front end, using automated algorithms, to provide robust filtering of low quality data.

This project addresses the specific problem of vetting the quality of electrocardiograms (ECGs) collected by an untrained user in ambulatory scenarios using smartphone devices.