Scholarly Works, Industrial and Systems Engineering

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Research articles, presentations, and other scholarship

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Evaluating Back-Support Exoskeletons in Simulated Construction-Relevant Tasks: Effects on Task Completion Time and Aspects of Usability
Ojelade, Aanuoluwapo; Kim, Sunwook; Morris, Wallace; Barr, Alan; Harris-Adamson, Carisa; Nussbaum, Maury A. (2025-09)
Back-support exoskeletons (BSEs) are a promising intervention in reducing physical demands during diverse occupational tasks. However, limited information is available about the effectiveness of different BSE designs during construction work and if those effects are consistent between novices and experienced workers. In our study, we aimed to identify the benefits and potential unintended consequences of BSEs during construction work, considering worker experience levels. Forty participants (20 novices and 20 experienced, balanced in both groups by biological sex) completed lab-based simulations of several construction-relevant tasks. These tasks were performed under a control condition (no BSE) and with three BSEs, each of which was tested in two support settings (on and off). Task performance was measured using completion time, and perceptions of diverse aspects of usability were obtained. Generally, BSE use increased task completion time, perceived discomfort, and perceived interference of BSEs during simulated tasks, while its effects on perceived physical effort were mixed. Rigid BSEs particularly increased perceived movement restrictions, while exosuits did not. In a few cases, the effects of BSEs on completion time and BSE usability differed between novice and experienced groups. Nonetheless, we suggest that future work could generalize results from novice participants to experienced participants. Overall, our results suggested that the effects of BSEs on completion time and perceptions of usability were distinct and task-specific, with no single BSE design emerging as being clearly superior across the simulated tasks.
MIND: A Multimodal AI Framework for Detecting and Forecasting Motor RRBs among Children with ASD
Shen, Mengqi; Cantin-Garside, Kristine D.; Kim, Sunwook; Nussbaum, Maury A. (2023-08-01)
Motor restricted and repetitive behaviors (RRBs), including self-injurious behavior (SIB) and stereotypical motor movements (SMM), hinder social interactions and adversely impact the physical and psychological well-being of individuals with autism spectrum disorder (ASD) and their families. Although behavioral interventions can effectively address RRBs, their accurate detection and forecasting were previously considered unattainable due to their impulsive nature and individualized behavior types, triggers, and patterns. Monitoring these behaviors may be possible via wearable sensors, but is challenged by expected inconsistencies in how sensors are worn, especially given the often low compliance observed among children with ASD. In this study, we introduced a novel AI framework for detecting and forecasting motor RRBs – Multimodal, Interpretation, Numeration, and Deep neural decoding (MIND). We observed what we term ”transition behaviors,” in which participants exhibited subtle changes in their behavior patterns or facial expressions immediately preceding the onset of motor RRBs. Identifying these transition behaviors provided evidence that motor RRBs can, in fact, be forecasted. Through a series of assumptions, the multimodal interpretation within MIND connects wearable sensor functionality to existing behavioral and psychological evidence about motor RRBs. Additionally, novel signal processing guidelines categorize modality into motion and biological modalities. These guidelines process the signal based on their generalized functionality, ensuring robustness to inconsistent data and minimizing the impact of sensor specifications (i.e., range and units of measurement, sensor resolution, sensor orientation). Analyses of modalities supported the noted assumptions. The multimodal optimization under MIND framework suggested the effective use of a single wearable device integrating several sensors (or modalities). Crucially, all children in the study were willing to wear the sensor at the optimized location, highlighting its practicality. MIND achieved 100% accuracy in detecting motor RRBs in new subjects with unfamiliar behavior types and 92.2% accuracy in forecasting (2 sec. in advance) motor RRBs. Cross-validation using various sampling methods showcased that MIND has the potential to generalize to a broader sample of children with ASD. MIND provides an advancement in the automated detection and forecasting of motor RRBs.
Algorithms in Art and Code: How Teaching Embodied Artmaking Procedures Can Stimulate Analytical Thinking in Art Crafting and Computer Programming
Bruen, Jacqueline; Jeon, Myounghoon (ACM, 2025-06-23)
People have pointed to a connection between the creative arts and computing. In the present longitudinal pilot study we taught six programmers and six non-programmers how to read and write written crochet patterns with or without the accompanying crochet gestures. Half of programmers (three participants) and nonprogrammers (three participants) were taught with the gestures, while the other halves were not. Over two weeks we individually taught participants crochet during three separate 30 minute sessions. In a fourth session, we tested participants on crochet and elementary programming and algorithms. Test results showed that programmers and non-programmers performed better on average on both tests when they learned with gestures. We interviewed all participants afterwards; programmers provided examples of how crochet demonstrated elementary programming ideas, while nonprogrammers described what they thought about programming. Our empirical study provides evidence of embodied cognition and offers contributions towards developing novel teaching methods in computer science.
AI-Supported Dance Performances Provoke Audiences to Seek Creative Merit and Meaning in AI's Artistic Decisions
Bruen, Jacqueline; Jeon, Myounghoon (ACM, 2025-06-23)
With the development of tools using generative artificial intelligence (GenAI) to create art, stakeholders cannot come to an agreement on the value of these works. In this study we uncovered the mixed opinions surrounding art made by AI. We developed two versions of a dance performance augmented by technology either with or without GenAI. For each version we informed audiences of how the performance was developed either before or after they had taken a survey on their perceptions of the performance. There were thirty-nine participants (13 males, 26 female) recruited and divided between the four performances. After the survey, we conducted focus groups with a subset of audience members. Results demonstrated that individuals were more inclined to attribute artistic merit to works made by GenAI when they were unaware its use. Our work contributes to the understanding of the design and reception of AI-made art.
Investigating the Effects of Simulated Eye Contact in Video Call Interviews
Jelson, Andrew; Tausif, Md Tahsin; Lim, Sol; Khanna, Soumya; Lee, Sang Won (ACM, 2025-04-26)
Some people suggest that deliberately watching the camera during video calls can simulate eye contact and help build trust. In this study, we investigated the effects of simulated eye contact in video calls and job interviews through an experimental study and a survey. Study 1 involved participants in a mock interview as an interviewer, where a confederate interviewee simulated eye contact half the time. The gaze patterns of the participants were tracked to understand the effects. In Study 2, we conducted an online survey to confirm the findings of Study 1 on a larger scale by asking those with experience interviewing to evaluate interviewees based on interview videos, half of which simulated eye contact. The results of both studies indicate that simulated eye contact had little impact on their evaluation compared to common belief. We discuss how the results motivate future work and how computational approaches to correcting eye gaze can be deceptive.
"Look at My Planet!": How Handheld Virtual Reality Shapes Informal Learning Experiences
Moon, Hayoun; Bautista Isaza, Carlos Augusto; Gallagher, Matthew; McDaniel, Clara; Vernier, Atlas; Ican, Leah; Springer, Karina; Cohn, Madelyn; Bennett, Sylvia; Nair, Priyanka; Ricard, Alayna; Pochiraju, Nayha; Enriquez, Daniel; Lee, Sang Won; Ogle, J. Todd; Newbill, Phyllis; Jeon, Myounghoon (ACM, 2025-04-26)
Handheld virtual reality offers a promising tool for fostering engagement in informal learning environments, providing safe, shared, and inclusive experiences. This study investigated the potential of a handheld VR-based educational program, Solar System Explorer, in a science museum setting. Fifty-three participants, aged 5 to 13, engaged in six interactive scenes using handheld tablets, involving room-scale exploration of virtual environments in small groups guided by a docent. Findings showed that dynamic, room-scale content encouraged active physical movement, while visually rich, interactive scenes fostered knowledge sharing and elicited positive emotional responses. Social engagement was strongest during creative activities, such as planet building, which facilitated interactions even among unfamiliar peers. These insights inform design guidelines for developing fun, active, and collaborative VR learning environments, contributing to scalable and inclusive handheld VR applications for informal education.
A child-robot theater afterschool program can promote children’s conceptualization of social robots’ mental capacities and engagement in learning
Dong, Jiayuan; Yu, Shuqi; Choi, Koeun; Jeon, Myounghoon (Frontiers, 2025-03-14)
Research on integrating emerging technologies, such as robots, into K-12 education has been growing because of their benefits in creating engaging learning environments and preparing children for appropriate human-robot interactions in the future. However, most studies have focused on the impact of robots in formal educational settings, leaving their effectiveness in informal settings, such as afterschool programs, unclear. The present study developed a 9-week afterschool program in an elementary school to promote STEAM (STEM + Art) education for elementary school students. The program incorporated four modules (Acting, Dancing, Music & Sounds, and Drawing), each with specific learning objectives and concluding with a theater play at the end. This program facilitated hands-on activities with social robots to create engaging learning experiences for children. A total of 38 students, aged 6–10 years, participated in the afterschool program. Among these students, 21 took part in research activities, which included answering questions about their perceptions of robots compared to other entities (i.e., babies and beetles), learning interest and curiosity, and their opinions about robots. In addition, four teachers and staff participated in interviews, sharing their reflections on children’s learning experiences with robots and their perceptions of the program. Our results showed that 1) children perceived robots as having limited affective and social capabilities but gained a more realistic understanding of their physiological senses and agentic capabilities; 2) children were enthusiastic about interacting with robots and learning about robot-related technologies, and 3) teachers recognized the importance of embodied learning and the benefits of using robots in the afterschool program; however, they also expressed concerns that robots could be potential distractions and negatively impact students’ interpersonal relationships with peers in educational settings. These findings suggest how robots can shape children’s perceptions of robots and their learning experiences in informal education, providing design guidelines for future educational programs that incorporate social robots for young learners.
Happiness improves perceptions and game performance in an escape room, whereas anger motivates compliance with instructions from a robot agent
Dong, Jiayuan; Jeon, Myounghoon (Academic Press - Elsevier, 2025-08)
Emotions have been discovered to have critical impacts on human-robot interaction (HRI), but research has focused more on robots’ emotion expressions than user emotions. The present study investigated the impact of users’ emotions (happiness and anger) on their perceptions and trust toward robots, perceived workload, and task performance in an escape room with a robot agent. Forty-six college students participated in our study. The results suggested that happy participants rated the robot agent as significantly more likable, safer, and more comfortable than angry participants. Angry participants complied significantly more with the robot agent's instructions than happy participants, but fewer succeeded. Among the participants who failed to escape the room, angry participants showed significantly higher cognitive trust in the robot than happy participants. The results underscored the importance of user emotions in shaping user perceptions and trust in robots, providing valuable theoretical and practical implications for emotions in HRI.
Investigating drivers' responses to cyber-attacks while conducting non-driving related tasks in highly automated vehicles
Ban, Gayoung; Jeon, Myounghoon (Academic Press - Elsevier, 2025-08)
As automated vehicles (AVs) advance, understanding human factors in cybersecurity incidents is essential to ensuring driver safety and system resilience. While prior research has explored driver responses to cyber-attacks in partially automated (Level 2–3) vehicles, less is known about how drivers in highly automated vehicles respond. In Level 4 automation, drivers are not required to monitor the roadway continuously but may still need to intervene in unforeseen cyber-attack, making re-engagement dynamics fundamentally different from lower levels of automation. This study examines the impact of non-driving-related task (NDRT) engagement and cyber-attack criticality on situation awareness, visual attention, response time, and workload in Level 4 AVs. To this end, forty-five participants drove in a driving simulator with two types of cyber-attack criticality (non-safety-related, and safety-related as within-subjects) and three non-driving related tasks (NDRTs) engagement levels (no, single and dual as between-subjects). Results indicate that drivers engaged in any level of NDRT (Single or Dual) had significantly reduced situation awareness of road conditions and delayed response time and gaze reallocation to critical information after a cyber-attack, particularly in Dual NDRT conditions. Additionally, safety-related cyber-attacks induced greater cognitive workload, suggesting that drivers exert more mental effort when responding to high-risk threats. These findings highlight the unique re-engagement challenges in Level 4 AVs, where drivers must transition from passive engagement in NDRTs to active situation awareness during cybersecurity incidents. The results emphasize the need for human-centered AV cybersecurity systems that optimize alert delivery, minimize cognitive overload, and facilitate rapid driver response to emerging threats in highly automated driving environments.
Mapping the complex causal mechanisms of drinking and driving behaviors among adolescents and young adults
Hosseinichimeh, Niyousha; MacDonald, Rod; Li, Kaigang; Fell, James C.; Haynie, Denise L.; Simons-Morton, Bruce; Banz, Barbara C.; Camenga, Deepa R.; Iannotti, Ronald J.; Curry, Leslie A.; Dziura, James; Mayes, Linda C.; Andersen, David F.; Vaca, Federico E. (Pergamon-Elsevier, 2022-03)
Background: The proportion of motor vehicle crash fatalities involving alcohol-impaired drivers declined substantially between 1982 and 1997, but progress stopped after 1997. The systemic complexity of alcohol-impaired driving contributes to the persistence of this problem. This study aims to identify and map key feedback mechanisms that affect alcohol-impaired driving among adolescents and young adults in the U.S. Methods: We apply the system dynamics approach to the problem of alcohol-impaired driving and bring a feedback perspective for understanding drivers and inhibitors of the problem. The causal loop diagram (i.e., map of dynamic hypotheses about the structure of the system producing observed behaviors over time) developed in this study is based on the output of two group model building sessions conducted with multidisciplinary subject-matter experts bolstered with extensive literature review. Results: The causal loop diagram depicts diverse influences on youth impaired driving including parents, peers, policies, law enforcement, and the alcohol industry. Embedded in these feedback loops are the physical flow of youth between the categories of abstainers, drinkers who do not drive after drinking, and drinkers who drive after drinking. We identify key inertial factors, discuss how delay and feedback processes affect observed behaviors over time, and suggest strategies to reduce youth impaired driving. Conclusion: This review presents the first causal loop diagram of alcohol-impaired driving among adolescents and it is a vital first step toward quantitative simulation modeling of the problem. Through continued research, this model could provide a powerful tool for understanding the systemic complexity of impaired driving among adolescents, and identifying effective prevention practices and policies to reduce youth impaired driving.
Trajectories and outcomes of adolescents that ride with an impaired driver/drive while impaired
Vaca, Federico E.; Li, Kaigang; Haynie, Denise L.; Gao, Xiang; Camenga, Deepa R.; Dziura, James; Banz, Barbara C.; Curry, Leslie A.; Mayes, Linda; Hosseinichimeh, Niyousha; MacDonald, Rod; Iannotti, Ronald J.; Simons-Morton, Bruce (Elsevier, 2022-03)
Introduction: For young drivers, independent transportation has been noted to offer them opportunities that can be beneficial as they enter early adulthood. However, those that choose to engage in riding with an impaired driver (RWI) and drive while impaired (DWI) over time can face negative consequences reducing such opportunities. This study examined the prospective association of identified longitudinal trajectory classes among adolescents that RWI and DWI with their later health, education, and employment in emerging adulthood. Methods: We analyzed all seven annual assessments (Waves, W1–W7) of the NEXT Generation Health Study, a nationally representative longitudinal study starting with 10th grade (2009–2010 school year). Using all seven waves, trajectory classes were identified by latent class analysis with RWI (last 12 months) and DWI (last 30 days) dichotomized as ≥ once = 1 vs. none = 0. Results: Four RWI trajectories and four DWI trajectories were identified: abstainer, escalator, decliner, and persister. For RWI and DWI trajectories respectively, 45.0% (N = 647) and 76.2% (N = 1657) were abstainers, 15.6% (N = 226) and 14.2% (N = 337) were escalators, 25.0% (N = 352) and 5.4% (N = 99) were decliners, and 14.4% (N = 197) and 3.8% (N = 83) persisters. RWI trajectories were associated with W7 health status (χ² = 13.20, p <.01) and education attainment (χ² = 18.37, p <.01). Adolescent RWI abstainers reported better later health status than RWI escalators, decliners, and persisters; and decliners reported less favorable later education attainment than abstainers, escalators, and persisters. DWI trajectories showed no association with health status, education attainment, or employment. Conclusions: Our findings suggest the importance of later health outcomes of adolescent RWI. The mixed findings point to the need for more detailed understanding of contextual and time-dependent trajectory outcomes among adolescents engaging in RWI and DWI.
What determines the success of states in reducing alcohol related crash fatalities? A longitudinal analysis of alcohol related crashes in the US from 1985 to 2019
Hosseinichimeh, Niyousha; Williams, Ross; MacDonald, Rod; Li, Kaigang; Vaca, Federico E. (Pergamon-Elsevier, 2022-09)
In the United States, nearly 28 people die in alcohol–related motor vehicle crashes every day (1 fatality every 52 min). Over decades, states have enacted multiple laws to reduce such fatalities. From 1982 to 2019, the proportion of drivers in fatal crashes with a blood alcohol concentration (BAC) above 0.01 g/dl declined from 41% to 22%. States vary in terms of their success in reducing alcohol–related crash fatalities. The purpose of this study was to examine factors associated with changes in fatalities related to alcohol–impaired driving at the state level. We created a panel dataset of 50 states from 1985 to 2019 by merging different data sources and used fixed–effect linear regression models to analyze the data. Our two outcome variables were the ratio of drivers in fatal crashes with BAC ≥ 0.01 g/dl to those with BAC = 0.00, and the ratio of those with BAC ≥ 0.08 g/dl to those with BAC < 0.08 g/dl. Our independent variables included four laws (0.08 g/dl BAC per se law, administrative license revocation law, minimum legal drinking age law, and zero tolerance law), number of arrests due to impaired driving, alcohol consumption per capita, unemployment rate, and vehicle miles traveled. We found that the 0.08 g/dl per se law was significantly associated with lower alcohol–related crash fatalities while alcohol consumption per capita was significantly and positively associated with crash–related fatalities. Arrests due to driving under the influence (DUI) and crash fatalities were nonlinearly correlated. In addition, interaction of DUI arrests and two laws (0.08 g/dl BAC per se law, and zero tolerance) were significantly associated with lower crash–related fatalities. Our findings suggest that states which have more restrictive laws and enforce them are more likely to significantly reduce alcohol–related crash fatalities.
From text to map: a system dynamics bot for constructing causal loop diagrams
Hosseinichimeh, Niyousha; Majumdar, Aritra; Williams, Ross; Ghaffarzadegan, Navid (Wiley, 2024-07)
We introduce and test the System Dynamics Bot, a computer program leveraging a large language model to automate the creation of causal loop diagrams from textual data. To evaluate its performance, we ensembled two distinct databases. The first dataset includes 20 causal loop diagrams and associated texts sourced from the system dynamics literature. The second dataset comprises responses from 30 participants to a vignette, along with causal loop diagrams coded by three system dynamics modelers. The bot uses textual data and successfully identifies approximately 60% of the links between variables and feedback loops in both datasets. This article outlines our approach, provides examples, and presents evaluation results. We discuss encountered challenges and implemented solutions in developing the System Dynamics Bot. The bot can facilitate extracting mental models from textual data and improve model-building processes. Moreover, the two datasets can serve as a test-bed for similar programs.
Best-Response Dynamics for Large-Scale Integer Programming Games with Applications to Aquatic Invasive Species Prevention
Lee, Hyunwoo; Hildebrand, Robert; Cai, Wenbo; Büyüktahtakın, İ. Esra (2025-06)
This paper presents a scalable algorithm for computing the best pure Nash equilibrium (PNE) in large-scale integer programming games (IPGs). While recent advances in IPG algorithms are extensive, existing methods are limited to a small number of players, typically 𝑛 = 2, 3. Motivated by a county-level aquatic invasive species (AIS) prevention problem involving 84 players, we develop efficient and scalable algorithms that significantly extend the applicability of IPGs. Specifically, we propose the best-response dynamics incorporated zero-regret (BZR) algorithm, which leverages best-response dynamics (BRD) for rapid PNE identification and integrates BRD as a primal heuristic within the zero-regret (ZR) framework. This approach dramatically improves the scalability of IPG algorithms, allowing us to solve IPGs with up to 30 players in random datasets and the 84-player AIS prevention problem with Minnesota data. To model the AIS prevention problem, we introduce the edge-weighted budgeted maximum coverage (EBMC) game, a newclass of IPG that has not been previously studied. We establish theoretical conditions for the existence of a PNE under both selfish and locally altruistic utility functions. Experimental results in EBMC games and knapsack problem games demonstrate that BZR significantly enhances ZR in both finding a PNE and identifying the best PNE, particularly in games with many players.
Using musculoskeletal models to estimate the effects of exoskeletons on spine loads during dynamic lifting tasks: differences between OpenSim and the AnyBody modelling system
Behjati Ashtiani, Mohamad; Akhavanfar, Mohammadhossein; Li, Lingyu; Kim, Sunwook; Nussbaum, Maury A. (Elsevier, 2025-05-23)
Occupational back-support exoskeletons (BSEs) can reduce physical demands during lifting by providing assistive torques, but their effects on spine loading are poorly understood. In this study, we used two common musculoskeletal models developed in OpenSim and the AnyBody Modeling System to estimate intervertebral joint forces (IJF) during asymmetric and symmetric lifting tasks with and without BSEs. Data from an earlier study were used, involving 18 participants who performed repetitive lowering/lifting in three task conditions and with three different BSEs (along with a control condition using no BSE). We simulated the tasks with both models and estimated axial compression and anteroposterior shear forces at the L4/L5 joint and derived peak values (95th percentile) as outcome measures. OpenSim estimated significantly larger axial compression and anteroposterior shear forces than AMS. Both models estimated reductions in spine loading when using either of the BSEs, though OpenSim estimated greater reductions than AMS. Strong positive, linear relationships (r > 0.95) between the two model estimates were found for axial compression, while much weaker and even negative relationships were observed for shear forces, especially under asymmetric conditions. The differences in model estimates were likely due to variations in model assumptions and passive tissue representations. Future research should explore more detailed human-exoskeleton interaction models, evaluate the impact of modelling assumptions on IJF estimates, and assess the agreement of these findings with in vivo measurements such as electromyography.
Effectiveness and usability of a trunk posture feedback system: An exploratory, longitudinal study for up to 10 days among vehicle assembly operators
Choi, Jiwon; Kim, Sunwook; Lim, Sol; Porto, Ryan; Nussbaum, Maury A. (Elsevier, 2025-10)
Postural feedback systems are a potential ergonomic intervention to reduce postural exposures, and thus musculoskeletal disorder risk, but field-based evidence of their longer-term effectiveness remains limited. We conducted an exploratory investigation of a commercial postural feedback system, which provided auditory and vibrotactile feedback following excessive trunk motion, in vehicle manufacturing. Eight workers used the system during regular shifts for up to 10 workdays. We observed a reduction in “poor” postures on the first day of feedback. However, these benefits diminished over time, possibly due to a novelty effect—with improvements diminishing as participants adapted to the system—and effects varied greatly across participants. Participant responses were mixed; some reported improved postural awareness while others found the feedback irritating and often ignored it. Findings from this exploratory study suggest the importance of enhancing postural feedback system design to sustain behavioral change over time and better support individual needs.
Two Novel Slip Training Methods Improve the Likelihood of Recovering Balance After a Laboratory-Induced Slip
Allin, Leigh J.; Nussbaum, Maury A.; Madigan, Michael L. (Human Kinetics, 2018-08-06)
Task-specific balance training is an approach to fall prevention that has the potential to reduce the number of slip-induced falls. However, a limitation of current task-specific training methods is that they require nontrivial financial and/or equipment resources. This pilot study evaluated the efficacy of 2 low-cost, low-tech methods for slip-recovery training in improving balance recovery ability. The 2 methods were as follows: (1) repeated unexpected slip training (UST), which involved repeated unexpected slips while walking (similar to current methods of task-specific slip-recovery training) and (2) volitional sliprecovery training (VST), which involved practicing a slip recovery response after volitionally stepping to induce a slip-like perturbation. A total of 36 young adults completed 1 training session (UST, VST, or control), followed by 1 unexpected, laboratory-induced slip while walking on the following day. Compared with controls, UST and VST resulted in a higher proportion of successful balance recoveries from the laboratory-induced slips. UST improved both proactive control and the reactive stepping response after slipping, whereas VST improved the ability to arrest the motion of the slipping foot. Based on these preliminary results, UST and VST may provide practical, cost-effective methods for slip-recovery training.
Required friction during overground walking is lower among obese compared to non-obese older men, but does not differ with obesity among women
Arena, Sara L.; Garman, Christina R.; Nussbaum, Maury A.; Madigan, Michael L. (Elsevier, 2017-02-27)
Obesity and aging have been independently associated with altered required friction during walking, but it is unclear how these factors interact to influence the likelihood of slipping. Therefore, the purpose of this study was to determine whether there are differences related to obesity and aging on required friction during overground walking. Fourteen older non-obese, 11 older obese, 20 younger non-obese, and 20 younger obese adults completed walking trials at both a self-selected and hurried speed. When walking at a hurried speed, older obese men walked at a slower gait speed and exhibited lower frictional demands compared both to older non-obese men and to younger obese men. No differences in required friction were found between non-obese and obese younger adults. These results suggest that the increased rate of falls among obese or older adults is not likely due to a higher risk of slip initiation.
Relative Effort while Walking Is Higher among Women Who Are Obese, and Older Women
Koushyar, Hoda; Anderson, Dennis E.; Nussbaum, Maury A.; Madigan, Michael L. (Lippincott Williams & Wilkins, 2019-07-23)
Purpose: Individuals who are obese, and older individuals, exhibit gait alterations that may result, in part, from walking with greater effort relative to their maximum strength capacity. The goal of this study was to investigate obesity-related and age-related differences in relative effort during gait. Methods: Four groups of women completed the study, including 10 younger healthy-weight, 10 younger obese, 10 older healthy-weight, and 9 older obese women. The protocol included strength measurements at the hip, knee, and ankle in both flexion and extension, and gait trials under self-selected and constrained (1.5 m·s-1 gait speed and 0.65-m step length) conditions. Relative effort was calculated as the ratio of joint torques during gait, and strength from a subject-specific model that predicted strength as a function of joint angle. Results: Relative effort during self-selected gait was higher among women who were obese in knee extension (P = 0.028) and ankle plantar flexion (P = 0.013). Although both joint torques and strength were higher among women who were obese, these increases in relative effort were attributed to greater obesity-related increases in joint torques than strength. Relative effort was also higher among older women in hip flexion (P < 0.001) and knee extension (P = 0.008), and attributed to age-related strength loss. Results were generally similar between self-selected and constrained gait, indicating the greater relative effort among women who were obese and older women was not attributed to differences in gait spatiotemporal characteristics. Conclusions: Women who were obese, as well as older women, walk with greater relative effort. These results may help explain the compromised walking ability among these individuals.
Obesity as a Factor Contributing to Falls by Older Adults
Madigan, Michael L.; Rosenblatt, Noah J.; Grabiner, Mark D. (Springer, 2014-05-24)
The growth of the worldwide population of older adults presents significant challenges, many inter-related, that range from the health of individuals to the health of national economies. In the US, more than one-third of older adults may be obese, a condition that may independently increase the risk for mobility impairment, fall-related injury and, possibly, costs of post-injury treatment and care. The effectiveness of conventional exercise-based fall prevention programs is significant but smaller than both the annual rate of falling of older adults and rate of growth of this population, who are at greatest risk for injurious falls. The anthropometric and functional consequences of obesity may impose limitations on the ability to perform compensatory stepping responses following large postural disturbances. The focus of this paper is the potential of task-specific training to improve compensatory stepping responses and reduce falls by obese people given the individual-specific anthropometric and functional consequences of obesity.

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