As technology advances, the usage and applications of context-aware systems continue to spread across different areas in patient monitoring and disease management. It provides a platform for healthcare professionals to assess the health status of patients in their care using multiple relevant parameters. Existing technologies for cardiac patient monitoring are generally based on the physiological information, mostly the heart rate or Electrocardiogram(ECG) Signals. Other important factors such as physical activities and time of the day are usually ignored. We propose a context-aware solution for cardiac rehabilitation monitoring using multiple vital signs from the physiological and activity data of the patient. This research considers the activity of the patient alongside the time of the activity to facilitate physicians decision-making process. We provide a personalised physical activity recognition processing by generating a personalised model for each user. A prototype is presented to illustrate our proposed approach.