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Using Decision Trees to Predict Intent to Use Passive Occupational Exoskeletons in Manufacturing Tasks

McNamara, Nathan Patrick
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605720844135027

Abstract Details

2020, Master of Science (MS), Ohio University, Industrial and Systems Engineering (Engineering and Technology).
A nontraditional decision tree approach was used to predict worker intent to use passive occupational exoskeletons in various manufacturing tasks. A dataset adapted from a previous study containing 33 records of participant, exoskeleton, and task combinations was used to create multiple decision tree models. Worker intent to use the exoskeleton was used as the target variable for all decision tree models. Data were collected during two separate sessions with fifteen participants at five manufacturing facilities in Ohio. Participants wore exoskeletons for under 30 minutes in each session and answered questions pertaining to personal characteristics, task characteristics, and personal preferences. Response data were used to create practitioner and research decision tree models. The practitioner models classified worker intent to use exoskeletons using only task characteristics and personal characteristics. Research models used personal characteristics, task characteristics, and personal preferences features to predict intent to use with all collected data. Both practitioner and research models may be useful for practitioners and exoskeleton developers for better understanding factors related to intent to use exoskeletons. All models created in the study yielded findings consistent with previous exoskeleton literature. This study demonstrated the ability of classification trees to identify nonlinear relationships in datasets relating to intent to use assistive technologies.
Diana Schwerha, Ph.D (Advisor)
Gary Weckman, Ph.D (Committee Member)
Dean Bruckner, Ph.D (Committee Member)
Timothy Ryan, Ph.D (Committee Member)
72 p.
Industrial Engineering
Decision; tree; trees; assistive; device; devices; exoskeleton; ergonomic intervention; ergonomics; machine learning; human factors; predictive algorithm; intent to use; safety

Recommended Citations

Citations

  • McNamara, N. P. (2020). Using Decision Trees to Predict Intent to Use Passive Occupational Exoskeletons in Manufacturing Tasks [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605720844135027

    APA Style (7th edition)

  • McNamara, Nathan. Using Decision Trees to Predict Intent to Use Passive Occupational Exoskeletons in Manufacturing Tasks. 2020. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605720844135027.

    MLA Style (8th edition)

  • McNamara, Nathan. "Using Decision Trees to Predict Intent to Use Passive Occupational Exoskeletons in Manufacturing Tasks." Master's thesis, Ohio University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605720844135027

    Chicago Manual of Style (17th edition)

ohiou1605720844135027
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© 2020, all rights reserved.
This open access ETD is published by Ohio University and OhioLINK.