Detecting Human Movement Patterns Through Data Provided by Accelerometers. A Case Study Regarding Alzheimer’s Disease

2016 ◽  
pp. 56-66 ◽  
Author(s):  
Rafael Duque ◽  
Alicia Nieto-Reyes ◽  
Carlos Martínez ◽  
José Luis Montaña
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Movement Patterns ◽  
Human Movement

scholarly journals A Convolutional Neural Network-Based Method for Human Movement Patterns Classification in Alzheimer’s Disease

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 72 ◽  
Author(s):  
Santos Bringas ◽  
Sergio Salomón ◽  
Rafael Duque ◽  
José Luis Montaña ◽  
Carmen Lage
Keyword(s):  
Neural Network ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Convolutional Neural Network ◽  
Human Movement ◽  
Accelerometer Data ◽  
Mobility Patterns ◽  
Mobility Data ◽  
Neurodegenerative Pathology

Alzheimer’s disease (AD) constitutes a neurodegenerative pathology that presents mobility disorders as one of its earliest symptoms. Current smartphones integrate accelerometers that can be used to collect mobility data of Alzheimer’s patients. This paper describes a method that processes these accelerometer data and a convolutional neural network (CNN) that classifies the stage of the disease according to the mobility patterns of the patient. The method is applied in a case study with 35 Alzheimer’s patients, in which a classification success rate of 91% was obtained.

scholarly journals Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Karen McCulloch ◽  
Nick Golding ◽  
Jodie McVernon ◽  
Sarah Goodwin ◽  
Martin Tomko
Keyword(s):  
Spatial Scales ◽  
Predictive Ability ◽  
Movement Patterns ◽  
Human Movement ◽  
Continental Scale ◽  
Movement Characteristics ◽  
Human Movements ◽  
Movement Models ◽  
Epidemiology Data

AbstractUnderstanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movement patterns across broad regions. Movement characteristics, however, strongly depend on the scale and type of movement captured for a given study. The models that have so far been proposed for human movement are best suited to specific spatial scales and types of movement. Selecting both the scale of data collection, and the appropriate model for the data remains a key challenge in predicting human movements. We used two different data sources on human movement in Australia, at different spatial scales, to train a range of statistical movement models and evaluate their ability to predict movement patterns for each data type and scale. Whilst the five commonly-used movement models we evaluated varied markedly between datasets in their predictive ability, we show that an ensemble modelling approach that combines the predictions of these models consistently outperformed all individual models against hold-out data.

scholarly journals Opieka pielęgniarska nad pacjentką w przebiegu choroby Alzheimera z wykorzystaniem ICNP®

2020 ◽  
Vol 5 (3) ◽  
pp. 97-115
Author(s):  
Karolina Krajewska ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Holistic Approach ◽  
Female Gender ◽  
Control Field ◽  
Her Family ◽  
Everyday Activities ◽  
Nurse Caring ◽  
It Risk

Introduction. Alzheimer's disease (AD – Alzheimer Disease) is an incurable neurodegenerative disease. The main source of memory discomfort is destruc-tion. With age, irresistibly falling ill with it. Risk factors for the development of Alzheimer's disease are primarily: diabetes, female gender, hypertension and the lack of a control field. It is estimated that in Poland Alzheimer's disease affects about 200,000 people. According to statistics, 60% of all forms of de-mentia are AD. Aim of the study. The aim of the study is to present the activities that should be performed by a nurse caring for a patient with diagnosed Alzheimer's dis-ease. Case study. A 75-year-old patient admitted to the internal medicine ward, she has communication, content swallowing and spatial orientation disorders. It requires constant assistance in the performance of everyday activities. He complains of urinary and faecal incontinence. Conclusion. Thanks to the holistic approach to the patient, it is possible to ensure her correctness and the approach of the patient and her family.

scholarly journals Using U.S. Medicare records to evaluate the indirect health effects on spouses: a case study in Alzheimer’s disease patients

2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Daniel M Gilden ◽  
Joanna M Kubisiak ◽  
Kristin Kahle-Wrobleski ◽  
Daniel E Ball ◽  
Lee Bowman
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Health Effects

Parallels Between Neurodevelopment and Neurodegeneration: A Case Study of Alzheimer's Disease

2008 ◽  
pp. 147-155 ◽  
Author(s):  
X. Zhu ◽  
G. Casadesus ◽  
K. M. Webber ◽  
C. S. Atwood ◽  
R. L. Bowen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease

scholarly journals Selecting Remote Measurement Technologies to Optimize Assessment of Function in Early Alzheimer's Disease: A Case Study

2020 ◽  
Vol 11 ◽  
Author(s):  
Andrew P. Owens ◽  
Chris Hinds ◽  
Nikolay V. Manyakov ◽  
Thanos G. Stavropoulos ◽  
Grace Lavelle ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Remote Measurement ◽  
Early Alzheimer’S Disease

Mining Twitter to Inform the Design of Online Interventions for Hispanic Alzheimer’s Disease and Related Dementias Caregivers

2019 ◽  
Vol 18 (3) ◽  
pp. 138-143 ◽  
Author(s):  
Sunmoo Yoon ◽  
Robert Lucero ◽  
Mary S. Mittelman ◽  
José A. Luchsinger ◽  
Suzanne Bakken
Keyword(s):  
Social Support ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Structural Changes ◽  
Topic Models ◽  
Network Size ◽  
Self Management ◽  
Content Mining ◽  
Using Data

Background/Objective: Hispanics are about 1.5 times as likely as non-Hispanic Whites to experience Alzheimer’s disease and related dementias (AD/ADRD). Eight percent of AD/ADRD caregivers are Hispanics. The purpose of this article is to provide a methodological case study of using data mining methods and the Twitter platform to inform online self-management and social support intervention design and evaluation for Hispanic AD/ADRD caregivers. It will enable other researchers to replicate the methods for their phenomena of interest. Method: We extracted an analytic corpus of 317,658 English and Spanish tweets, applied content mining (topic models) and network structure analysis (macro-, meso-, and micro-levels) methods, and created visualizations of results. Results: The topic models showed differences in content between English and Spanish tweet corpora and between years analyzed. Our methods detected significant structural changes between years including increases in network size and subgroups, decrease in proportion of isolates, and increase in proportion of triads of the balanced communication type. Discussion/Conclusion: Each analysis revealed key lessons that informed the design and/or evaluation of online self-management and social support interventions for Hispanic AD/ADRD caregivers. These lessons are relevant to others wishing to use Twitter to characterize a particular phenomenon or as an intervention platform.

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