One of FrailSafe objectives is to generate reliable advanced intervention services and determine the risk of triggering events that would make a person tip from the pre-frail category to the frail one. To do so, the technical partners have designed and developed a detailed definition of a personalized Virtual Patient Model (VPM) composed of older people information. These will be collected by unobtrusively monitoring their everyday life through a variety of embedded and wireless smart indoors and outdoors sensors, social interaction, clinical assessment and self-evaluation tests. In other words, this VPM will be the older person’s virtual alter ego, reflecting their medical condition (see figure).
The model will be personalised, in a sense that the frailty related entities are categorized into data related to the (i) user identification, (ii) summary of the data recorded from the integrated sensors as well as the questionnaire and game analysis, (iii) archived medical data essential to the clinicians such as comorbidities and test results, and finally (iv) a list of parameters that are linked to the recognition of short-term (for example fall detection) and long-term events (change of frailty metric).
The VPM will be coupled with a monitoring system that will (i) facilitate the analysis of the collected data and frailty feature extraction, (ii) support the physician in his/her decision process ranging from general health preservation monitoring to critical situation management, (iii) allow an adaptation of the user interfacing and (iv) provide a personalized feedback to the older person via lifestyle change suggestions, behaviour guidelines and medical intervention strategies.
Thanks to this personalised VPM and monitoring system, the older person will benefit from a system that gives him/her an optimal overview of his/her (pre-) frail state and at the same time, provide them with a tool that enable them to take the right decision concerning frailty prevention.