Joint research to support independent living for senior citizens
According to a Japanese Ministry of Health, Labour and Welfare survey, the average Japanese life expectancy in 2014 was 80.50 years for men and 86.83 years for women, both new records. Recently, various efforts are being made not only to just extend longevity but also to extend healthy life expectancy (the age people live independently without daily nursing care). Fujitsu aims to develop systems to support managing health and daily lives with ICT and build solutions for senior citizens and patients using the developed systems.
In July 2013, Fujitsu Laboratories, together with the Irish research institutions CASALA* and Insight@UCD**, embarked on a three-year joint research project aimed at supporting people living full, independent lives safely and with peace of mind. In this joint research, we collect data on the daily lives of senior citizens and patients living in smart houses*** from some 110 sensors embedded in living spaces, as well as sensors worn by patients.
*Built and operates the Great Northern Haven trial smart house equipped with environmental sensing in Dundalk, Ireland.
**Brings together expertise from life and clinical sciences, and biomedical engineering to advance the application of the sensor web to the connected health field.
***A concept for houses proposed in the United States in 1980s in which a wide variety of services are provided according to user needs under optimal control involving the networking of home appliances with the facility’s equipment.
Extracting events matched to individual features to detect hidden abnormalities
In the past, it has not been easy to extract data from vast amounts of sensor data connected to health risks, such as abnormal motor functions. For example, as there are over 50 characteristics that can be extracted from walking data, such as stride length, stagger, and intensity, etc., and because these will vary from person to person, it is difficult to detect risks in everyday living—such as poor mobility that might be caused by various disorders or illness.
As one of the results of this joint research, Fujitsu developed technology to discover hidden abnormalities by quantifying a series of everyday activities, such as “opened door” or “walked” that match an individual’s way of walking from vast amounts of sensing data from smart house residents.
Using environmental sensors, physical activity sensors, and vital-signs sensors, this technology continuously reports everyday activities, such as standing and walking, and quantifies characteristics that will vary with each person and illness. By repeatedly extracting successive events, such as the consecutive two-step process of rising and then walking, it is possible to discover aspects of motor function irregularity that clinical practitioners may overlook. For example, in the case of someone who has trouble walking after getting out of bed, this technology would observe and provide insight to problems such as joint stiffness or changes in blood pressure after rising that a clinical practitioner could identify and start to question.
Improving QOL with a treatment or care plan suitable for individuals
This technology detects risks hidden in everyday activities that will vary from person to person. For example, a patient who walks with a limp may be prone to loss of balance while walking after getting out of bed.
The visualization of risks in everyday activities allows medical institutions and facilities for senior citizens to draw up a treatment or care plan suitable for individuals, which contributes to improving their quality of life (QOL).
Fujitsu Laboratories, Fujitsu Ireland, and Fujitsu are aiming for a practical implementation of this technology in fiscal 2017, and are proceeding with a trial project in Ireland to test other disorders and to apply the technology and test it outside of smart houses. In the future, Fujitsu aims to develop services that can be used in the home or in institutions to identify behaviors that lead to an individual’s risk and to provide operational support to medical practitioners.