Use case 4: home-based (high tech scenario)

The user of this UC is an elderly person with MCI (Mild Cognitive Impairment) such as light dementia (due to age) who lives in a single person household (or in a nursing home with other elderly persons). The user suffers from multiple pathologies such as COPD (Chronic Obstructive Pulmonary Disease) and diabetes and therefore needs to carry on daily checks. For instance he she may need to measure his/her blood oxygen and/or blood glucose level daily, as well as other bio signals together with indicators assessing his/her mental state.

The user has bought a specific set-up box* with two additional compatible sensors, for measurement of blood glucose and/or blood oxygen levels. The user also uses a smartphone (or tablet or smartwatch) to run a dedicated App*.

To better support him/her with assistance at home and to support tele-monitoring, he/she had his/her house refurbished and fitted with various sensors as well as with a building automation system which can be used to control lighting systems, shading, climate etc. The building automation system is compliant with the KNX standard (conforms to EN 50090 and ISO/IEC 14543) and therefore can be controlled by the set-up box*. Lastly, the house is also equipped with compatible sensor flooring that can be used to track the location of people and identify when someone has fallen, and to provide activity monitoring.

On daily basis, the user uses the set-up box*’s user-friendly interface and web-based social networking/video-conferencing features to communicate with friends, family members and –most notably- with caretakers for routine checks. During one of these routine checks with the medical helpdesk, based on latest information from blood glucose and/or blood oxygen levels, the doctor prescribes a daily check of both values and adds this schedule to the user’s calendar (which can be used for medical and non-medical events). Periodic checks are assessed and the appropriate actions suggested for taking the appropriate medicine from the cabinet.

Historic information from the checks is stored in encrypted form within a dedicated cloud service* managed by the private care service provider. The cloud features high level of security and whenever each party receives data it is re-encrypted uniquely thus ensuring cryptographic separation of each recipient’s data and allowing audit by both key management and document distribution.

At the due time, the reminder service* recalls the user through “contextualised” reminders which are adapted to the specific context. According to the situation the user is in, the __system__* autonomously takes the appropriate actions to produce alerts using the most appropriate objects (through semantic assessment of connected object descriptions) which are “qualified” to raise his attention: this could be a smartphone ringtone, a buzzer, flashing light in the room (through command sent to the building automation system), a message on TV etc.

Following acknowledgement of such alerts the user is reminded through his App* how (and where) to properly perform the test and, in case of need, he/she is also guided to the place in the house where the medicine is located. In extreme cases, tele-monitoring is activated with his/her doctors / caretakers.

One night, the user wakes up and gets out of his/her bed in a state of partial confusion. The system* recognises his movements thanks to a night vision video camera or sensor flooring. The system automatically turns on soft lights (through a message to the KNX home automation system). Preventively, the system* turns on the lights of the corridor to illuminate the path to the toilet (included) to help him/her reach the restroom. After a couple of minutes, he/she turns off the lights and goes to bed. Longer times standing still in the night may have triggered a warning to a caregiver, as this may indicate a problem.

NOTE: some of the features within the following section may require prior explicit consent by the users

Family members or caretakers may be alarmed whenever reminders are repeatedly ignored while, whenever a threshold violation is detected, the medical team is notified together with an aggregated report of daily and weekly values to evaluate the patient’s condition.

Abnormal patterns and/or extreme values are software detected and dispatched to the helpdesk or attending doctors who have full access to the EHR. The report includes also macroscopic information on physical exercise by the user (e.g. number of kilometres the user has walked per day, average time spent still etc.) based on aggregation of position information related to the user’s mobile phone, which are automatically retrieved by the system* within indoor and outdoor contexts. The most important alerts are also automatically sent to close relatives or to emergency staff either when the user clicks on the “emergency function” on one of specific devices* (e.g. the App* or ad hoc devices) or whenever the system* detects that the user has fallen.

This event could be triggered, as illustrated earlier, in an autonomous and context-aware manner, fitting the equipment available to detect that a fall has indeed occurred (i.e. sensor flooring, image processing on camera feeds, noise patterns recognition, wearable sensors data etc.).

*) “set-up box”, “system”, “app” and “service” all refer to the various components being developed by the EC funded project UNCAP ( www.uncap.eu )



-- GiuseppeConti - 28 May 2015
Topic revision: r1 - 28 May 2015, GiuseppeConti
 

This site is powered by FoswikiThe information you supply is used for OGC purposes only. We will never pass your contact details to any third party without your prior consent.
If you enter content here you are agreeing to the OGC privacy policy.

Copyright © by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Ideas, requests, problems regarding OGC Public Wiki? Send feedback