Our healthcare systems are facing sustainability challenges caused by a demographic shift with ageing, chronicity and disability growing in our society. A novel healthcare paradigm should be founded on 4P medicine: Preventive, Predictive, Personalized, and Participatory medicine needs new methodologies and tools enabled by Information and Communication Technologies (ICTs). One of the key technology enablers for 4P medicine is telemonitoring, i.e. ICTs to monitor the health status of a patient from a distance, which may trigger 4P decision making. A new generation of telemonitoring tools allow prescription and follow-up around the main chronic care strategies, namely, therapeutic adherence and healthy habits promotion. A broader and more ambitious challenge is Quality of Life (QoL) telemonitoring based on the knowledge of context. We are proposing a formal methodology to provide Context-aware QoL assessment, categorizing data inputs, defining outputs, and exploring data fusion techniques. A Telemonitoring and Home Support System (TMHSS) which implements that methodology has been designed, developed and integrated to the BackHome system for a particular Use Case, i.e. severely disabled people using Brain Computer Interfaces (BCI) as an assistive technology (AT) at home. We have applied User Centred Design throughout all development stages of a multi-functional BCI, in order to move BCIs from the lab towards independent home use. The BackHome system has achieved five key innovations: (i) an architecture able to meet the requirements of BCI multifunctionality and remote home support; (ii) a light, autonomous, comfortable and reliable BCI equipment; (iii) an easy-to-use software to control multiple purpose applications; (iv) a TMHSS for BCI independent home use; and (v) a Therapist station to manage and monitor BCI-based remote services. We have evaluated the BackHome system with end-users at home, also taking the therapists' and non-expert caregivers' perspective into account. The results show good acceptance, usability levels, user satisfaction and levels of control, which demonstrate that BCI can already be considered as an alternative AT. We used the TMHSS of BackHome to recognize activities and habits of users based on the analysis of sensors' data, in order to detect for example whether the user is at home or away or whether has received a visit at home or not. Similarly, and consequently from the previous analysis, results show good accuracies in assessing items of QoL such as Mobility, Sleep, or Mood, based on measures and fusion of detected activities from the user. The assessment of the overall wellbeing of an individual with a multidimensional perspective through processing of data gathered from environmental and personal sensors in a broad and non-intrusive way, will become of great interest to healthcare professionals, policy makers and also for citizens which are called to co-produce and lead the new paradigm of care.
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