Browsing by Author "Ojelade, Aanuoluwapo"

Now showing 1 - 11 of 11
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    A data-driven approach to understand factors contributing to exoskeleton use-intention in construction
    Kim, Sunwook; Moore, Albert; Ojelade, Aanuoluwapo; Gutierrez, Nancy; Harris-Adamson, Carisa; Barr, Alan; Srinivasan, Divya; Nussbaum, Maury A. (SAGE, 2023-10-25)
    Work-related musculoskeletal disorders (WMSDs) remain an important heath concern for construction workers. Occupational exoskeletons (EXOs) are a new ergonomic intervention to control WMSD risk, yet their adoption has been low in construction. We explored contributing factors to EXO use-intention, by building a decision tree to predict the intention to try an exoskeleton using responses to an online survey. Variable selection and hyperparameter tuning were used respectively to reduce the number of potential predictors, and for a better prediction performance. Performance was assessed using four common metrics. The importance of variables in the final tree was calculated to understand which variable had a greater influence. The final tree had moderate prediction performance. Important variables identified were associated with opinions on EXO use, demographics, job demands, and perceived potential risks. The key influential variables were EXOs becoming standard equipment and fatigue reduction with EXO use. Practical implications of the findings are discussed.
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    Effects of Arm-Support Exoskeletons on Kinematics and Subjective Assessments During a Static Task
    Ojelade, Aanuoluwapo; Kelson, Denean D.; Srinivasan, Divya D.; Kim, Sunwook S.; Smets, Marty; Nussbaum, Maury A. (Human Factors and Ergonomics Society, 2021-09)
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    Effects of Back-support Exoskeletons on Task Performance and Perceived Exertion During Construction-related Tasks: Differences related to Experience
    Ojelade, Aanuoluwapo; Kim, Sunwook; Morris, Wallace; Harris-Adamson, Carisa; Barr, Alan; Nussbaum, Maury A. (SAGE, 2023-10-24)
    The effects of three Back-support Exoskeletons (BSEs) on task performance (completion time) and perceived exertion were examined during simulated construction tasks. Forty participants (20 novices) completed the tasks using no BSE and three BSEs, each with two support settings (On and Off). There were significant main and interaction effects of Experience level on both outcome measures. Using BSEs negatively affected task performance for some tasks, though these effects were smaller among experienced participants. Interestingly, using BSEs inconsistently affected perceived physical effort, possibly due to the characteristics of the tasks, BSE designs, and experience levels. These results indicate that the effects of BSE on task performance and perceived physical effort are specific to experience level, BSE designs, and task demands. Further study is needed to better understand how to generalize these results to the actual work population.
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    Effects of Back-support Exoskeletons on Task Performance and Usability During Simulated Construction-relevant Tasks
    Ojelade, Aanuoluwapo; Morris, Wallace; Kim, Sunwook; Harris-Adamson, Carisa; Barr, Alan; Nussbaum, Maury A. (SAGE, 2022-10-11)
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    Perceived benefits, barriers, perceptions, and readiness to use exoskeletons in the construction industry: Differences by demographic characteristics
    Gutierrez, Nancy; Ojelade, Aanuoluwapo; Kim, Sunwook; Barr, Alan; Akanmu, Abiola; Nussbaum, Maury A.; Harris-Adamson, Carisa (Elsevier, 2023-12-21)
    Exoskeletons (EXOs) are a promising wearable intervention to reduce work-related musculoskeletal disorder risks among construction workers. However, the adoption of EXOs may differ with demographic characteristics. Survey data (n = 361) were collected from construction industry stakeholders and a summation score method was used to summarize respondent's benefits and barriers to EXO use, along with perceptions and readiness to use. Responses were stratified by race (White vs. non-White), sex (male vs. female), and age (<47 years vs. ≥47 years). Both a higher Benefits score and a higher Perceptions score were significantly and positively associated with a higher Readiness to Use score. There were also significant differences in perceived barriers to EXO use by race and sex. These results demonstrate substantial interest in EXO use but also emphasize the need to ensure proportionate access to the potential benefits of EXO technology.
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    Predicting External Hand Forces During Overhead Work: An Approach Using EMG and Random Forest Regression
    Behjati Ashtiani, Mohamad; Freidouny, Mohammadreza; Ojelade, Aanuoluwapo; Kim, Sunwook; Nussbaum, Maury A. (Sage, 2024-08-29)
    We developed a predictive model to estimate dynamic external hand forces during overhead tasks while wearing arm-support exoskeletons (ASEs). Despite the reported potential of ASEs to reduce muscle activation during overhead work, challenges in EMG sensor placement hinder comprehensive muscle monitoring. ASE effectiveness can be assessed by estimating shoulder forces through inverse dynamics, which requires external forces and body kinematics. Direct measurement of external forces can be quite challenging in practice. However, a predictive model could support estimating these forces without load cells. Participants completed task simulations using ASEs, while muscle activity and external forces were measured. Employing a random forest algorithm, EMG signals were mapped to force time series, accounting for participant characteristics and task parameters. Mean load cell values were 7.6 (SD 30.5) N, while predicted values were 7.6 (SD 22.7) N, affirming the potential of using EMG signals to estimate external hand forces while using ASEs.
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    A preliminary decision tree modeling of factors that determine readiness to use exoskeletons in construction
    Moore, Albert; Kim, Sunwook; Srinivasan, Divya; Nussbaum, Maury A.; Ojelade, Aanuoluwapo; Harris-Adamson, Carisa; Gutierrez Contreras, Nancy; Barr, Alan; Rempel, David (SAGE, 2021-09)
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    Subjective Assessments of Arm-Support Exoskeletons During Simulated Static and Dynamic Overhead Tasks
    Morris, Wallace; Kim, Sunwook; Ojelade, Aanuoluwapo; Srinivasan, Divya; Smets, Marty; Nussbaum, Maury A. (SAGE, 2022-10-11)
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    TEC and ROTI Measurements from a New GPS Receiver at BOWEN University, Nigeria
    Bolaji, Olawale S.; Kaka, Rafiat O.; Scales, Wayne A.; Fashae, Joshua B.; Peng, Yuxiang; Rabiu, A. Babatunde; Fadiji, Joshua O.; Ojelade, Aanuoluwapo (MDPI, 2023-03-28)
    Scintillation and total electron content (TEC) are the two major examples of the top-side ionospheric parameters that are recorded differently by most Global Positioning System (GPS) receivers. The new GPS sensor created by the Atmospheric and Space Technology Research Associates (ASTRA), Cornell University, and the University of Texas, Austin have capability to record scintillation and TEC fluctuations simultaneously. Hence, the Connected Autonomous Space Environment Sensor (CASES) from ASTRA is a software-defined GPS receiver with the dual frequency of L1 C/A and L2C codes for space-weather monitoring and can be remotely programmed via an internet source. The receiver employs numerous novel techniques that make it suitable for space-weather studies compared to other nearby GPS receivers, such as different methods for eliminating local clock effects, an advanced triggering mechanism for determining scintillation onset, data buffering to permit observation of the prelude to scintillation, and data-bit prediction and wipe-off for robust tracking. Moreover, the CASES hardware is made up of a custom-built dual frequency, a digital signal processor board, and a “single board computer” with an ARM microcontroller. We have used the CASES GPS receiver newly installed at Bowen University, Iwo, Nigeria, to investigate the TEC and the rate of the TEC index (ROTI) around the equatorial region. Measurements of the TEC and ROTI showed similar variation trends in monthly, seasonal, and annual periods when compared to TEC and ROTI measurements from a nearby station, BJCO at Cotonou, Benin Republic. The newly installed GPS receiver looks promising for scientific use as it is the only one operational in Nigeria at the moment.
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    Three Passive Arm-Support Exoskeletons have Inconsistent Effects on Muscle Activity, Posture, and Perceived Exertion During Diverse Simulated Pseudo-Static Overhead Work Tasks
    Ojelade, Aanuoluwapo; Morris, Wallace; Kim, Sunwook; Kelson, Denean; Srinivasan, Divya; Smets, Marty; Nussbaum, Maury A. (Elsevier, 2023-07-01)
    Arm-support exoskeletons (ASEs) are an emerging technology with the potential to reduce physical demands during diverse tasks, especially overhead work. However, limited information is available about the effects of different ASE designs during overhead work with diverse task demands. Eighteen participants (gender-balanced) performed lab-based simulations of a pseudo-static overhead task. This task was performed in six different conditions (3 work heights × 2 hand force directions), with each of three ASEs and in a control condition (i.e., no ASE). Using ASEs generally reduced the median activity of several shoulder muscles (by ∼12–60%), changed working postures, and decreased perceived exertion in several body regions. Such effects, though, were often task-dependent and differed between the ASEs. Our results support earlier evidence of the beneficial effects of ASEs for overhead work but emphasize that: 1) these effects depend on the task demands and ASE design and 2) none of the ASE designs tested was clearly superior across the tasks simulated.
  • Understanding contributing factors to exoskeleton use-intention in construction: A decision tree approach using results from an online survey
    Kim, Sunwook; Ojelade, Aanuoluwapo; Moore, Albert; Gutierrez, Nancy; Harris-Adamson, Carisa; Barr, Alan; Srinivasan, Divya; Rempel, David M.; Nussbaum, Maury A. (Informa, 2023-12-12)
    Work-related musculoskeletal disorders (WMSDs) are a major health concern in the construction industry. Occupational exoskeletons (EXOs) are a promising ergonomic intervention to help reduce WMSD risk. Their adoption, however, has been low in construction. To understand the contributing factors to EXO use-intention and assist in future decision-making, we built decision trees to predict responses to each of three EXO use-intention questions (Try, Voluntary Use, and Behavioral Intention), using online survey responses. Variable selection and hyperparameter tuning were used respectively to reduce the number of potential predictors and improve prediction performance. The importance of variables in each final tree was calculated to understand which variables had a greater influence. The final trees had moderate prediction performance. The root node of each tree included EXOs becoming standard equipment, fatigue reduction, or performance increase. Important variables were found to be quite specific to different decision trees. Practical implications of the findings are discussed.