Paper Info
Title
Building a framework for recognition of activities of daily living from depth images using fuzzy logic
Abstract
Complex activities such as instrumental activities of daily living (IADLs) can be identified by creating a hierarchical model of fuzzy rules. In this work, we present a framework to model a specific IADL - "making the bed". For this activity recognition, the need for a three level Fuzzy Inference System (FIS) model is shown. Simple features such as bounding box parameters were extracted from the foreground images and combined with 3D features extracted from the Kinect depth data. This was then fed as input to the three layered FIS for further analysis. Data collected from several participants were tested and evaluated. Such a framework can be used to model several other IADLS as well as basic activities of daily living (ADLs). Analysis of ADLs can be used to compare daily patterns in older adults to measure changes in behavior. This can then be used to predict health changes to assist older adults in leading independent lifestyles for longer time periods.
Year
DOI
Venue
2014
10.1109/FUZZ-IEEE.2014.6891647
Fuzzy Systems
Keywords
DocType
ISSN
feature extraction,fuzzy logic,fuzzy reasoning,learning (artificial intelligence),3D feature extraction,IADL,IADLS,Kinect depth data,behavior change measurement,bounding box parameters,data collection,depth images,foreground images,fuzzy logic,health change prediction,hierarchical fuzzy rule model,instrumental activities-of-daily living recognition,older adults,three-layered FIS model,three-level fuzzy inference system model,activities of daily living,depth image,fuzzy rules,machine learning
Conference
1544-5615
Citations 
PageRank 
References 
0
0.34
10
Authors
3
Name
Order
Citations
PageRank
Tanvi Banerjee18316.41
James M. Keller23201436.69
Marjorie Skubic31045105.36