UCSF

Objective

To improve home monitoring of heart failure patients so as to reduce emergency room visits and hospital readmissions. We aim to do this by analyzing the ballistocardiogram (BCG) to evaluate the clinical state of the patient.

Methods

1) High quality BCG signals were collected at home from HF patients after discharge. 2) The BCG recordings were preprocessed to exclude outliers and artifacts. 3) Parameters of the BCG that contain information about the cardiovascular system were extracted. These features were used for the task of classification of the BCG recording based on the status of HF.

Results

The best AUC score for the task of classification obtained was 0.78 using slight variant of the leave one subject out validation method.

Conclusion

This work demonstrates that high quality BCG signals can be collected in a home environment and used to detect the clinical state of HF patients.

Significance

In future work, a clinician/caregiver can be introduced into the system so that appropriate interventions can be performed based on the clinical state monitored at home.