Traditional heart failure markers fail to reliably predict heart-failure related hospitalisations and deaths. Multi- sensor patch data can provide an objective insight into activity and sleep patterns of patients and may therefore improve the performance of current risk-quantification algorithms. This work aimed to establish the feasibility of collecting multi-sensor patch data from heart failure patients and to perform an initial analysis of activity and sleep patterns of heart failure patients in relation to disease severity. 13 heart failure patients from the SUPPORT-HF study were provided with chest-worn multisensor patches and asked to wear the devices continuously for up to seven consecutive days. Using a combination of impedance, heart rate and accelerometer data participants' sleep and wakefulness information were extracted and analyzed in relation to self-reported symptom scores. Patch data for eleven patients were of high enough quality to be included in the analysis, accounting for 63 patient days worth of data. The heart failure patients slept for an average of 8.3 hours a night and experienced 2.8 sleep interruptions. Potential differences in sleep angle, heart rate and wake-time activity were found for patients with different heart failure severity. Larger studies are necessary to create a more coherent picture of the potential of activity and sleep as a markers for heart failure deterioration.