Unobtrusive Detection of Mild Cognitive Impairment in Older Adults Through Home Monitoring

The early detection of dementias such as Alzheimer's disease can in some cases reverse, stop, or slow cognitive decline and in general greatly reduce the burden of care. This is of increasing significance as demographic studies are warning of an aging population in North America and worldwide. Various smart homes and systems have been developed to detect cognitive decline through continuous monitoring of high risk individuals. However, the majority of these smart homes and systems use a number of predefined heuristics to detect changes in cognition, which has been demonstrated to focus on the idiosyncratic nuances of the individual subjects, and thus, does not generalize. In this paper, we address this problem by building generalized linear models of home activity of older adults monitored using unobtrusive sensing technologies. We use inhomogenous Poisson processes to model the presence of the recruited older adults within different rooms throughout the day. We employ an information theoretic approach to compare the generalized linear models learned, and we observe significant statistical differences between the cognitively intact and impaired older adults. Using a simple thresholding approach, we were able to detect mild cognitive impairment in older adults with an average area under the ROC curve of 0.716 and an average area under the precision-recall curve of 0.706 using activity models estimated over a time window of 12 weeks.

Developing Programs to Meet the Needs of Alzheimer's Families in Rural Maine

In 1992, Maine had only the rudiments of an integrated system of diagnostic and supportive services for people with Alzheimer's disease. Needs assessments confirmed that caregiver attitudes, geography, a lack of awareness of available services, and limited diagnostic and other specialized resources were major barriers to establishing an effective, comprehensive, and coordinated system of services for people with Alzheimer's disease. Responding to this situation, Maine received funds to develop the capacity to respond to the immediate needs of individuals with Alzheimer's disease and their families and to promote service system development. This article outlines the objectives of the project and highlights the successes and challenges experienced in Maine. Several important themes emerge that should be considered when developing programs to meet mental health needs in rural areas.

How Linked Are Physicians to Community Support Services for Their Patients With Dementia?

Physicians increasingly are expected to link patients affected by dementia and theirfamilies with community support services; yet, little is known about physicians' referral patterns or their fa miliarity with such services. This study of 206 physicians found that respondents were more likely to refer dementia patients and families to home health agencies and nursing homes than to respite or adult day care, the local Alzheimer's Association, or the local Area Agency on Aging. Physicians with more than 20 dementia patients in their practices were most likely to refer. Un certainty about available community services was ranked higher than time or reimbursement constraints as a barrier to care for dementia patients. Physicians in practice 1 to 5 years were more uncertain about available services than physicians in practice more than 20 years. Crea tive interventions to link physicians with community support services specializing in dementia care would benefit physicians, patients, and family caregivers.

Clustering Home Activity Distributions for Automatic Detection of Mild Cognitive Impairment in Older Adults

The public health implications of growing numbers of older adults at risk for dementia places pressure on identifying dementia at its earliest stages so as to develop proactive management plans. The prodromal dementia phase commonly identified as mild cognitive impairment is an important target for this early detection of impending dementia amenable to treatment. In this paper, we propose a method for home-based automatic detection of mild cognitive impairment in older adults through continuous monitoring via unobtrusive sensing technologies. Our method is composed of two main stages: a training stage and a test stage. For training, room activity distributions are estimated for each subject using a time frame of ω weeks, and then affinity propagation is employed to cluster the activity distributions and to extract exemplars to represent the different emerging clusters. For testing, room activity distributions belonging to a test subject with unknown cognitive status are compared to the extracted exemplars and get assigned the labels of the exemplars that result in the smallest normalized Kullbak-Leibler divergence. The labels of the activity distributions are then used to determine the cognitive status of the test subject. Using the sensor and clinical data pertaining to 85 homes with single occupants, we were able to automatically detect mild cognitive impairment in older adults with an F_0.5 score of 0.856. Also, we were able to detect the non-amnestic sub-type of mild cognitive impairment in older adults with an F_0.5 score of 0.958.

Identifying the components of clinical vignettes describing Alzheimer's disease or other dementias: a scoping review

Background

Clinical vignettes are often used to elicit information about health conditions in research studies. This review summarizes the components of clinical vignettes describing Alzheimer’s disease (AD) or other dementias. The purpose is to provide recommendations for the development of standardized vignettes that may be used in future studies.

Methods

MEDLINE, EMBASE, PsycINFO, ASSIA, CINAHL were searched from their inception to June 2014. Primary English-language studies employing vignettes to describe AD or similar disorders (including other dementias and Parkinson’s disease) were included in the review. Included studies had to describe the content of the vignettes in the published manuscripts. The characteristics of the included studies and the vignettes were extracted in tabular form and summarized qualitatively.

Results

Forty-two studies were included in the review. Twenty-four of the studies contained at least one AD vignette, 11 had vignettes focusing on non-AD dementias, and seven contained vignettes describing conditions other than dementia. In total, 58 vignettes were obtained from the 42 included studies.

Conclusions

Key aspects to consider when constructing vignettes for AD or other dementias include writing the vignettes from a third-person perspective and presenting hypothetical patients as being at least 65 years of age. Researchers should develop standardized vignettes for use across studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-015-0179-x) contains supplementary material, which is available to authorized users.

Autonomous unobtrusive detection of mild cognitive impairment in older adults

The current diagnosis process of dementia is resulting in a high percentage of cases with delayed detection. To address this problem, in this paper, we explore the feasibility of autonomously detecting mild cognitive impairment (MCI) in the older adult population. We implement a signal processing approach equipped with a machine learning paradigm to process and analyze real-world data acquired using home-based unobtrusive sensing technologies. Using the sensor and clinical data pertaining to 97 subjects, acquired over an average period of three years, a number of measures associated with the subjects' walking speed and general activity in the home were calculated. Different time spans of these measures were used to generate feature vectors to train and test two machine learning algorithms namely support vector machines and random forests. We were able to autonomously detect MCI in older adults with an area under the ROC curve of 0.97 and an area under the precision-recall curve of 0.93 using a time window of 24 weeks. This study is of great significance since it can potentially assist in the early detection of cognitive impairment in older adults.

The Northern California Chronic Care Network for Dementia

The Northern California Chronic Care Network for Dementia brings together Northern California's major providers of managed care, community-based care, consumer education, and advocacy in new partnerships to improve the care of persons with dementia enrolled in managed care plans and their family caregivers. These partnerships are part of a national initiative entitled the Chronic Care Network for Alzheimer's Disease (CCN/AD) sponsored by the National Chronic Care Consortium and the Alzheimer's Association. This initiative selected eight promising provider-consumer partnerships across the country to implement and evaluate a new model of coordinated care for people with dementia and their families. This paper describes the Northern California network's partnerships and its intervention and challenges. The intervention is grounded in the key components of the CCN/AD model: "identification of patients with possible dementia, diagnostic assessment, care management and family caregiver information and support." These components, in turn, are translated into protocols and pathways designed to create timely, comprehensive, appropriate, and effective systems of care services that address the unique needs of dementia patients and their caregivers over the course of the disease.