Temporal decision making using unsupervised learning

With the explosion of ubiquitous continuous sensing, on-line streaming clustering continues to attract attention. The requirements are that the streaming clustering algorithm recognize and adapt clusters as the data evolves, that anomalies are detected, and that new clusters are automatically formed as incoming data dictate. In this dissertation, we develop a streaming clustering algorithm, MU Streaming Clustering (MUSC), that is based on coupling a Gaussian mixture model (GMM) with possibilistic clustering to build an adaptive system for analyzing streaming multi-dimensional activity feature vectors. For this reason, the possibilistic C-Means (PCM) and Automatic Merging Possibilistic Clustering Method (AMPCM) are combined together to cluster the initial data points, detect anomalies and initialize the GMM. MUSC achieves our goals when tested on synthetic and real-life datasets. We also compare MUSC's performance with Sequential k-means (sk-means), Basic Sequential Clustering Algorithm (BSAS), and Modified BSAS (MBSAS) here MUSC shows superiority in the performance and accuracy. The performance of a streaming clustering algorithm needs to be monitored over time to understand the behavior of the streaming data in terms of new emerging clusters and number of outlier data points. Incremental internal Validity Indices (iCVIs) are used to monitor the performance of an on-line clustering algorithm. We study the internal incremental Davies-Bouldin (DB), Xie-Beni (XB), and Dunn internal cluster validity indices in the context of streaming data analysis. We extend the original incremental DB (iDB) to a more general version parameterized by the exponent of membership weights. Then we illustrate how the iDB can be used to analyze and understand the performance of MUSC algorithm. We give examples that illustrate the appearance of a new cluster, the effect of different cluster sizes, handling of outlier data samples, and the effect of the input order on the resultant cluster history. In addition, we investigate the internal incremental Davies-Bouldin (iDB) cluster validity index in the context of big streaming data analysis. We analyze the effect of large numbers of samples on the values of the iCVI (iDB). We also develop online versions of two modified generalized Dunn's indices that can be used for dynamic evaluation of evolving (cluster) structure in streaming data. We argue that this method is a good way to monitor the ongoing performance of online clustering algorithms and we illustrate several types of inferences that can be drawn from such indices. We compare the two new indices to the incremental Xie-Beni and Davies-Bouldin indices, which to our knowledge offer the only comparable approach, with numerical examples on a variety of synthetic and real data sets. We also study the performance of MUSC and iCVIs with big streaming data applications. We show the advantage of iCVIs in monitoring large streaming datasets and in providing useful information about the data stream in terms of emergence of a new structure, amount of outlier data, size of the clusters, and order of data samples in each cluster. We also propose a way to project streaming data into a lower space for cases where the distance measure does not perform as expected in the high dimensional space. Another example of streaming is the data acivity data coming from TigerPlace and other elderly residents' apartments in and around Columbia. MO. TigerPlace is an eldercare facility that promotes aging-in-place in Columbia Missouri. Eldercare monitoring using non-wearable sensors is a candidate solution for improving care and reducing costs. Abnormal sensor patterns produced by certain resident behaviors could be linked to early signs of illness. We propose an unsupervised method for detecting abnormal behavior patterns based on a new context preserving representation of daily activities. A preliminary analysis of the method was conducted on data collected in TigerPlace. Sensor firings of each day are converted into sequences of daily activities. Then, building a histogram from the daily sequences of a resident, we generate a single data vector representing that day. Using the proposed method, a day with hundreds of sequences is converted into a single data point representing that day and preserving the context of the daily routine at the same time. We obtained an average Area Under the Curve (AUC) of 0.9 in detecting days where elder adults need to be assessed. Our approach outperforms other approaches on the same datset. Using the context preserving representation, we develoed a multi-dimensional alert system to improve the existing single-dimensional alert system in TigerPlace. Also, this represenation is used to develop a framework that utilizes sensor sequence similarity and medical concepts extracted from the EHR to automatically inform the nursing staff when health problems are detected. Our context preserving representation of daily activities is used to measure the similarity between the sensor sequences of different days. The medical concepts are extracted from the nursing notes using MetamapLite, an NLP tool included in the Unified Medical Language System (UMLS). The proposed idea is validated on two pilot datasets from twelve Tiger Place residents, with a total of 5810 sensor days out of which 1966 had nursing notes

CPA elderCare/primePlus services : a practitioner\u27s resource guide;

CD-ROM files converted to PDF and included after main texthttps://egrove.olemiss.edu/aicpa_guides/1105/thumbnail.jp

Explainable pattern modelling and summarization in sensor equipped smart homes of elderly

In the next several decades, the proportion of the elderly population is expected to increase significantly. This has led to various efforts to help live them independently for longer periods of time. Smart homes equipped with sensors provide a potential solution by capturing various behavioral and physiological patterns of the residents. In this work, we develop techniques to model and detect changes in these patterns. The focus is on methods that are explainable in nature and allow for generating natural language descriptions. We propose a comprehensive change description framework that can detect unusual changes in the sensor parameters and describe the data leading to those changes in natural language. An approach that models and detects variations in physiological and behavioral routines of the elderly forms one part of the change description framework. The second part comes from a natural language generation system in which we identify important health-relevant features from the sensor parameters. Throughout this dissertation, we validate the developed techniques using both synthetic and real data obtained from the homes of the elderly living in sensor-equipped facilities. Using multiple real data retrospective case studies, we show that our methods are able to detect variations in the sensor data that are correlated with important health events in the elderly as recorded in their Electronic Health Records.Includes bibliographical reference

Family proximity and relocations in older adulthood

The family remains one of the most important sources of support for older adults. Geographic proximity between family members has important implications for the growing demand for formal and informal care. As people age, their own and their family members’ residential (im)mobility may be a strategy to facilitate the exchange of care. Drawing on the full population register data from Norway and Sweden, this research addresses the following question: How are needs-related life circumstances of older people associated with their own and their relatives’ migration and immobility (including older adults’ moves into institutionalized care facilities)? The roles of a range of needs-related life circumstances of older adults in their own and their family members’ locational choice are documented: needs for formal care, severe health problems, the absence of core family members, or losing a partner recently. The overall answer to the research question is that older adults’ needs-related life circumstances deter intergenerational geographic divergence, and inspire moves toward adult children, siblings, and into institutionalized residential care. The results emphasize the importance of non-resident family members in migration and immobility both as a deterrent to moving into institutionalized care and elsewhere when family members live nearby and as an attraction to migrate toward clusters of relatives. The findings broadly suggest that even in Norway and Sweden where formal care services are available, the welfare state is far from “crowding out” the family from the sphere of care and the family plays an important role in the locational choices of older adults

The Notebook: An Accidental Alzheimer\u27s Awareness Campaign

My paper examines and critiques the portrayal of Alzheimer¹s disease in the popular film, The Notebook. Based off of a Nicholas Sparks novel, The Notebook uses Alzheimer¹s disease as a vehicle to relay a love story, but in doing so, presents a distorted picture of Alzheimer¹s disease to its audience. My paper compares the responsibilities of family caregivers of Alzheimer¹s patients in today¹s world with the unrealistic family caregiver, Noah, depicted on screen. My paper also explores and exposes inconsistencies between the attractive nursing home experience presented on screen and the less than ideal treatment patients experience in long term care facilities in America today. In addition, my paper uses several other films to examine and compare the emotional distress Alzheimer¹s disease patients and their families face when confronted with the condition: further underlining the idealized familial encounter with the disease depicted in The Notebook. My paper also examines the glamorized representation of Alzheimer¹s disease symptoms in the film. The misrepresentation and glamorization of Alzheimer¹s disease in The Notebook elicit serious implications in today¹s society. My paper describes how Alzheimer¹s awareness groups and other organizations utilize The Notebook as an educational tool to raise awareness for the condition, despite its imperfections. For better or worse, in today¹s society, people absorb a myriad of information from film and pop culture, leaving filmmakers with the difficult task of balancing entertainment and medicine in their films. Ultimately, my paper highlights this imbalance in The Notebook and describes its resulting accidental Alzheimer¹s awareness campaign

Evidence review : Essential capabilities for managing an aged care workforce

Effective management and leadership in aged care are essential for effective aged care worker performance, which, in turn, enables high-quality care. This research report commissioned by the Australian Association of Gerontology highlights the critical need to understand better the nature and challenges of aged care management and leadership against a backdrop of growing demand for care and predicted shortfalls in the supply of workers to the sector

Perspectives and Theories of Social Innovation for Ageing Population

In recent years we may observe increasing interest in the development of social innovation both regarding theory as well as the practice of responding to social problems and challenges. One of the crucial challenges at the beginning of the 21st century is population ageing. Various new and innovative initiatives, programs, schemes, and projects to respond to negative consequences of this demographic process are emerging around the world. However, social theories related to ageing are still insufficiently combined with these new practices, social movements, organisational models, and institutions. Many scholars are still using notions and tools from classical theories of social gerontology or the sociology of ageing such as disengagement theory, activity theory, and successful and productive ageing. Such theories do not sufficiently explain ageing in the context of, for example, a broad use of the information and communications technologies (ICTs) including robotics and automation, new healthcare and long-term care models, advancements in the development and governance of age-friendly environments, and public engagement of older adults into co-production of services delivered by public, private, non-governmental as well as non-formal entities