scholarly journals Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms

PLoS Genetics ◽  
2020 ◽  
Vol 16 (10) ◽  
pp. e1009089
Author(s):  
Xinyue Li ◽  
Hongyu Zhao
Keyword(s):  
Feature Extraction ◽  
Circadian Rhythms ◽  
Wearable Device ◽  
Automated Feature Extraction

scholarly journals Automated Feature Extraction from Population Wearable Device Data Identified Novel Loci Associated with Sleep and Circadian Rhythms

2020 ◽  
Author(s):  
Xinyue Li ◽  
Hongyu Zhao
Keyword(s):  
Feature Extraction ◽  
Circadian Rhythms ◽  
Large Scale ◽  
Population Studies ◽  
Wearable Devices ◽  
Wearable Device ◽  
Genome Wide Association Studies ◽  
Physical Activity Monitoring ◽  
Scale Population ◽  
Shared Genetic

AbstractWearable devices have been increasingly used in research to provide continuous physical activity monitoring, but how to effectively extract features remains challenging for researchers. To analyze the generated actigraphy data in large-scale population studies, we developed computationally efficient methods to derive sleep and activity features through a Hidden Markov Model-based sleep/wake identification algorithm, and circadian rhythm features through a Penalized Multi-band Learning approach adapted from machine learning. Unsupervised feature extraction is useful when labeled data are unavailable, especially in large-scale population studies. We applied these two methods to the UK Biobank wearable device data and used the derived sleep and circadian features as phenotypes in genome-wide association studies. We identified 53 genetic loci with p<5×10-8 including genes known to be associated with sleep disorders and circadian rhythms as well as novel loci associated with Body Mass Index, mental diseases and neurological disorders, which suggest shared genetic factors of sleep and circadian rhythms with physical and mental health. Further cross-tissue enrichment analysis highlights the important role of the central nervous system and the shared genetic architecture with metabolism-related traits and the metabolic system. Our study demonstrates the effectiveness of our unsupervised methods for wearable device data when additional training data cannot be easily acquired, and our study further expands the application of wearable devices in population studies and genetic studies to provide novel biological insights.

scholarly journals Quantitative analysis ofex vivocolorectal epithelium using an automated feature extraction algorithm for microendoscopy image data

2016 ◽  
Vol 3 (2) ◽  
pp. 024502 ◽  
Author(s):  
Sandra P. Prieto ◽  
Keith K. Lai ◽  
Jonathan A. Laryea ◽  
Jason S. Mizell ◽  
Timothy J. Muldoon
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Image Data ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Automated Feature Extraction

Automated feature extraction for the classification of humanin vivo13C NMR spectra using statistical pattern recognition and wavelets

1996 ◽  
Vol 35 (6) ◽  
pp. 834-840 ◽  
Author(s):  
A. Rosemary Tate ◽  
Des Watson ◽  
Stephen Eglen ◽  
Theodores N. Arvanitis ◽  
E. Louise Thomas ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Nmr Spectra ◽  
Statistical Pattern Recognition ◽  
Statistical Pattern ◽  
Automated Feature Extraction

Investigation of automated feature extraction using multiple data sources

2003 ◽  
Author(s):  
Neal R. Harvey ◽  
Simon J. Perkins ◽  
Paul A. Pope ◽  
James P. Theiler ◽  
Nancy A. David ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Data Sources ◽  
Multiple Data Sources ◽  
Multiple Data ◽  
Automated Feature Extraction

scholarly journals Geoinformation approach to the urban geographic system research (case studies of Kharkiv region)

2018 ◽  
Keyword(s):  
Feature Extraction ◽  
Case Studies ◽  
Urban Areas ◽  
City Planning ◽  
Emergent Properties ◽  
Lidar Data ◽  
Research Approach ◽  
System Research ◽  
Automated Feature Extraction

Research problem introduction. The main research goal of this paper is to provide the urban geosystem research concept with both the theoretical basics presentation of GIS involvement in urban studies, and with examples of its practical applications. An urbogeosystem (UGS) has been presented not as a simple aggregate of cities, but as the emergent entity that produced complicated interconnections and interdependencies among its constituents. By the urbogeosystem concept the authors attempt to introduce a reliable research approach that has been deliberately developed to identify the nature and spatial peculiarities of the urbanization process in a given area. The exigency of this concept elaboration is listed by the number of needs and illustrated with ordinary 2D digital city cadaster limitations. The methodological background has been proposed, and its derivative applied solutions meet the number of necessities for more efficient urban mapping, city understanding, and municipal mana-gement. The geoinformation concept of the urban geographic system research. External and internal urbogeosystems. The authors explain why an UGS can be formalized as three major components: an aggregate of point features, a set of lines, an aggregate of areal features. The external UGS represents a set of cities, the internal one – a set of delineated areas within one urban territory. Algorithmic sequence of the urbogeosystem study with a GIS. The authors introduce algorithmic sequence of research provision with GIS, in which the LiDAR data processing block has been examined in the details with the procedure of the automated feature extraction explanation. Relevant software user interface sample of the visualization of the urban modeled feature attributes is provided. A case study of the external urbogeosystem. The regional case study of the external urbogeosystem modeling is introduced with GIS MapInfo Professional. The authors present the spatial econometric analysis for commuting study directed to a regional workforce market. The results of the external UGS research mainly correspond to some published social economic regularities in the area, but nonetheless it also demonstrates significant deviations that may be explained by this system’s emergent properties. Case studies of the internal urbogeosystem of Kharkiv-City. Two case studies of the internal urbogeosystem of Kharkiv City have been demonstrated, too. In the first one, automated feature extraction provided by the authors’ original software from LiDAR data has been applied for modeling this UGS content throughout a densely built-up urban parcel. In another case the GIS-analysis of the urbogeosystem functional impact on the catering services spatial distribution has been provided with the ArcGIS software. Results and conclusion. Summarizing all primary and derivative data processed with this technique as well as generalizing key ideas discussed in the text, the authors underline this whole methodological approach as such that can be considered as a general outlining showing how to use geoinformation software for the analysis of urban areas. Concluding their research, the authors emphasize that the urbogeosystem concept may be quite useful for visualization and different analysis applied for urban areas, including city planning, facility and other municipal management methods. The short list of the obtained results has been provided at the end of the text.

scholarly journals GPU Accelerated Automated Feature Extraction From Satellite Images

2013 ◽  
Vol 4 (2) ◽  
pp. 1-15 ◽  
Author(s):  
K. Phani Tejaswi ◽  
D. Shanmukha Rao ◽  
Thara Nair ◽  
Prasad A.V.V
Keyword(s):  
Feature Extraction ◽  
Satellite Images ◽  
Automated Feature Extraction
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