COMPASS aims to define and create a Personal Health System (PHS) to monitor the physiological parameters of patients affected by e.g. Chronic Obstructive Pulmonary Disease (COPD) and associated chronic illnesses, and predict the physiological state as a support to the decisions taken by medical doctors. COMPASS will achieve this by combining the usage of the state-of-the art Biovotion multi-parametric sensors, pervasive health, interoperability technology, and machine learning techniques.
COMPASS will deal with several challenges related to the use of multi-sensor solutions developed by Biovotion, namely:
- Standardisation of the communication stack according to the Continua Alliance standards to ensure interoperability
- Signal compression and analysis at the mobile application level to minimise the power requirements of the system
- Machine learning algorithm for prediction and classification and critical conditions and exacerbation of the COPD condition of the patients using the Biovotion sensors to provide actionable information;
- Machine learning algorithms to model the rehabilitation of COPD patients and provide advices for a personalised rehabilitation program
- Representation of the physiological signals of the patient with current medical standards, such as HL7 CDA R2, to interface to existing care management solutions to ensure that standards are adhered to providing interoperability of the devices within a wireless patient monitoring environment.