The CAMI project has completed a study on elderly patients attitudes and needs of patient monitoring and social care technologies in the home.The study showed that a portable computer is the most common mobile device (67%), followed by smart phones (48%) and tablets (30%). 90% of the respondents have Internet access. The respondents were asked about various social care technologies and if thought they could be helpful in their daily lifes. See below for the percentage of the respondents that thought the following devices would be a good idea and helpful
54% “a robot with a touch screen which you can use anywhere around the house for socializing, communication with other people and for providing information”
48% “a robot remind you on tasks and medication”
51% “a robot supervising your house through various sensors and alerting in case of problems”
50% “a robot bring you of water, your medication or any other small object”.
From the study it was also clear that “remembering to take their pills and medication” was one of the biggest problems for the respondents.
59% was very interested in “viewing graphic displays of your various health measurements (blood pressure, heart rate, oxygen levels) and their change in time and 60% thought it was a good idea to share these health measurements with their doctors.
105 persons aged between 55 and 75 years in Denmark, Poland and Romania was part of the study as well as 58 caregivers.
We have now made the LinkWatch Observation Server available through a REST API. eHealth developers can now retrieve streams of observations and display them in different, easy to understand diagrams to both clinicians and to patients. It can be used both for traditional patient and clinician portals, as well as for smart phone app developments. LinkWatch Medical Device Gateways for PC, tablets and smart phones, LinkWatch Health Plugins and the LinkWatch Observation Server forms the LinkWatch Remote Care Platform that can easily be customized for different care scenarios and organisations.
LinkWatch Observation Server is an ehealth software that can receive medical observations from medical devices, process them and store them in database. In addition to the stand-alone SQL Server based solution we are now also offering it as a cloud service through the Microsoft Azure IoT Cloud. This relieves care organisations from having to manage and update such a complex system themselves, new devices and formats are constantly being added to the Remote Patient Monitoring market.
The LinkWatch Observation Server supports Continua, HL7, IEEE11073, IHE-PCD021 formats and can process observations encoded using these standards but also industry formats like openmHealth. The LinkWatch Observation Server also provides an REST-based API for developers that needs to retrieve observation streams (in standard formats) and incorporate them into patient and clinician portals.
The LinkWatch Observation Server can be used as a stand-alone component or cloud service, and it can also be used with the different LinkWatch Gateways for PC, tablet and smart phones and the LinkWatch Plugins to provide a complete Remote Patient Monitoring Platform.
CNet has join the European AIOTI Alliance for IoT Developers and Innovators. The Alliance for Internet of Things Innovation was recently initiated by the European Commission in order to develop and support the dialogue and interaction among the Internet of Things (IoT) various players. The overall goal of the establishment of the AlOTI is the creation of a dynamic European IoT ecosystem to unleash the potentials of the IoT.
The CAMI project had its kick-off meeting in end of June in Bucharest, Romania. The project will develop a fully integrated AAL (Ambient Assisted Living) solution by providing services for health management, home management and wellbeing including socialization. CAMI builds an artificial intelligence ecosystem, which allows seamless integration of any number of ambient and wearable sensors with a mobile robotic platform endowed with multimodal interaction (touch, voice, person detection), including a telepresence robot.