Congestive heart failure (CHF) is a chronic medical condition, and early detection of acute cardiac events caused by CHF can lead to life saving results. In this paper, we present Blue Scale, a measuring device that allows both patients and their physicians to monitor cardiac health at home on a daily basis by providing the necessary feedback for early cardiac event detection. Blue Scale measures electrocardiography (EKG), systolic time intervals through photoplethysmography (PPG), weight, and whole body bioimpedance. Collected datasets are transmitted to a central database using a secure Wi-Fi 802.11b/g protocol for remote data analysis and disease management. Following a test deployment in different populations, we conclude that off-device signal processing is required to ensure the accuracy of derived measurements. Furthermore, our anomaly emulation experiments yield average Z-scores of below 2 for most EKG and PPG related metrics, and the resulting Z-scores also vary significantly across different patients. These observations indicate that a standard 95% confidence interval is not sufficient for attribute-by-attribute anomaly detection, and any cardiac monitoring systems need to be tailored to each individual.