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Sketch-based navigation for mobile robots using qualitative landmark states
(University of Missouri--Columbia, 2007)
In this work, a system for navigating a mobile robot along a sketched route is proposed. The sketch is drawn on a PDA screen by a human operator and contains approximate landmarks and a path, similar to a sketch provided ...
Personalized functional health and fall risk prediction using electronic health records and in-home sensor data
(University of Missouri--Columbia, 2021)
Research has shown the importance of Electronic Health Records (EHR) and in-home sensor data for continuous health tracking and health risk predictions. With the increased computational capabilities and advances in machine ...
Investigation of the relative amplitude method in detecting early illness
(University of Missouri--Columbia, 2013)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] In this study, we examine the relative amplitude - a circadian rhythm measure, as a potential feature for early illness detection. We used data collected ...
3D scene description and construction using spatial referencing language
(University of Missouri--Columbia, 2010)
It has long been a dream of science fiction to have a robot that can understand and communicate using the rich dialog of natural language. Having such capabilities would allow a human collaborator to interact naturally and ...
PIR sensing array for fall detection
(University of Missouri--Columbia, 2011)
The purpose of the Fuzzy PIR Fall Detection Array is to keep the elderly safe by providing a means for an immediate response to falls while still allowing them to enjoy the same independence they felt before fall detection ...
Data-driven methods for analyzing ballistocardiograms in longitudinal cardiovascular monitoring
(University of Missouri--Columbia, 2019)
Cardiovascular disease (CVD) is the leading cause of death in the US; about 48% of American adults have one or more types of CVD. The importance of continuous monitoring of the older population, for early detection of ...
Investigation of the effects of body type on accelerometer based fall detection
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI--COLUMBIA AT REQUEST OF AUTHOR.] Precision or personalized medicine follows the idea that analyzing a patient's genome can help stratify patients into treatment groups [1] ...
Investigation of the effects of body type on accelerometer based fall detection
(University of Missouri--Columbia, 2019)
Precision or personalized medicine follows the idea that analyzing a patient's genome can help stratify patients into treatment groups. Patients with cancer, for example, are split into groups based on the genetic make-up, ...
Activity segmentation with special emphasis on sit-to-stand analysis
(University of Missouri--Columbia, 2010)
In this study, we present algorithms to segment the activities of sitting and standing, and identify the regions of sit-to-stand transitions in a given image sequence. As a means of fall risk assessment, we propose methods ...
Type-1 and type-2 fuzzy systems for detecting visitors in an uncertain environment
(University of Missouri--Columbia, 2009)
In this work, I have developed an algorithm to detect the presence of visitors in a noninvasive manner. This algorithm is designed as part of an in home monitoring system. The data from the algorithm will be used as a way ...
RF sensing and processing methods for noninvasive health monitoring
(University of Missouri--Columbia, 2021)
Vulnerable populations include groups of people with a higher risk of poor health as a result of the limitations due to illness or disability. The health issues of vulnerable populations include three categories: physical, ...
Body-worn accelerometer-based health assessment algorithms for independent living older adults
(University of Missouri--Columbia, 2020)
The mainstream smart wearable products used for activity trackers have experienced significant growth recently. Among the older population, collecting long periods of activity data in a real-life setting is challenging ...