In automated home care systems (HCSs), sensor technology is employed to monitor patients, thereby aiming to reduce the workload of healthcare professionals and improving the patient s quality of life. A complex event processing (CEP) system can be used to analyze sensor readings and identify interesting events. CommonSens is a CEP system that is specifically designed for automated HCSs, which simplifies the work of the application programmer by adapting to different environment and sensor configuration. It provides fundamental data models for the environment, sensors and events, which enables the user to identify elements in the home environment and to reuse these elements. However, some required features are not fully implemented, such as support for processing multiple queries simultaneously and a solution for notifying the caregiver when an important event has occurred. Esper is considered the leading open source CEP provider and can be applied to a variety of domains. As Esper is designed in a generalized way, it has to be extended in order for it to be usable as an underlying CEP system for an automated HCS. In this thesis we investigate if Esper can be used as a CEP system to build an automated HCS by implementing the three fundamental data models of CommonSens with Esper. The resulting system is called EsperSens. To sim- plify the work for the application programmer, by using the query language of CommonSens, we create a translator that takes a CommonSens query and constructs an Esper query. We implement a web application to serve as a user interface for the system so that it can be accessed by multiple devices, e.g., a smartphone or a laptop. To evaluate if EsperSens correctly detects events we performed simula- tions with synthetic workloads. We measure the time Esper needs to process events during these simulations and compare them with the results of run- ning these simulations with CommonSens. Our results show that EsperSens correctly detect events, but runs on average slower than CommonSens. Com- pared to the time measured when delivering a notification over a network, the difference between CommonSens and EsperSens is insignificant. We con- clude that EsperSens satisfies the most crucial requirement of automated HCS, which is to correctly detect events in near real-time and deliver notifi- cations to a healthcare professional.