NeuroInformatics in Aging
Toshiharu Nakai, PhD
NeuroImaging & Informatics, National Center for Geriatrics & Gerontology
Ohbu, Aichi Japan
Aging makes not only physical but also mental change throughout our life. Extension of lifespan has been medically, socially and economically raising many issues. Since wellness in older adults reflects various factors depending on individual backgrounds and histories, it is difficult to design a global solution applicable to each individual. Therefore, it is quite important to share knowledge, technologies and methods across the research and development fields in wellness of older adults to supply optimized resources and integrate the outcomes.
Any orgNIAsm has its own biological system, which is at the same time NIAnformation system. We propose that the domain to explore this information system in aging research, i.e. Aging NeuroInformatics for Aging (NIA), will be the main power to promote wellness in aging. The following three will characterize NIA.
1. Personal sensing and logging systems:
A personal sensing and logging system will have interactive procedures with a cloud system to orgNIAze a large cohort database. It will continuously collect and update the cohort database, and support daily life of older adults by reporting their physical activities and physiological status to give possible suggestions. In order to more precisely estimate physical activities and characteristics of movements, the handy monitoring systems to be developed will include a set of sensors such as camera-less motion-capture beside conventional life log sensors. A camera-less motion capture will be useful to identify the type of movements and more precisely estimate their amount. Sensing by an electromyogram (EMG) and an electro-encephalography (EEG) will be further implemented to investigate the potential of physiological logging to detect clinical signs by correlating with behavioral episodes.
2. Databasing system to manage large-scale cohort studies:
The physiological and psychological statuses of older adults are much more variable than younger to middle-aged adults depending on their genetic factors, life style and clinical history. Therefore, large number of samples is required as the population of longitudinal cohort studies including more dependent variables of behavioral data, physiological data, image data, and personal attributes. Development of a standard databasing system equipped with automatic multivariable analysis capability to find significant variables correlated with the independent variable of interest out of such large and heterogeneous cohort data sets is indispensable in aging researches.
3. Information and assisting system for older adults:
Application of intelligent system will be quite useful to assist them to pace and maintain their activities for health promotions, since not a few of them live by themselves making them easily isolated in their community and cognitive decline due to aging. It will also inform older adults of instructions and suggestions to optimize physical / cognitive interventions depending on analysis of their various physical and psychological statuses. The medium to present such information may be a wearable device enough small and light for older adults or an agent like small humanoid.
Neuroimaging methods take quite important roles in NIA, since the characteristics of cognitive processing in older adults has several differences from that of younger adults. Neuroimaging will be applied not only 1) to clarify the changes of neural network responses in older adults but also 2) to validate the outcome of physical / cognitive intervention and 3) to evaluate the designs of interfaces of the devices for older adults.
NIA is an emerging field to include neuroscience, cognitive science, information science, robotics, gerontology and neurology. It is not just one application of neuroinformatics, since it more involves implementation of the information and assisting systems which are taking important parts in the wellness in aging.