Human Factors in AI-Driven Digital Solutions for Increasing Physical Activity: Scoping Review.

BACKGROUND: Artificial intelligence (AI) has the potential to enhance physical activity (PA) interventions. However, human factors (HFs) play a pivotal role in the successful integration of AI into mobile health (mHealth) solutions for promoting PA. Understanding and optimizing the interaction between individuals and AI-driven mHealth apps is essential for achieving the desired outcomes. OBJECTIVE: This study aims to review and describe the current evidence on the HFs in AI-driven digital solutions for increasing PA. METHODS: We conducted a scoping review by searching for publications containing terms related to PA, HFs, and AI in the titles and abstracts across 3 databases-PubMed, Embase, and IEEE Xplore-and Google Scholar. Studies were included if they were primary studies describing an AI-based solution aimed at increasing PA, and results from testing the solution were reported. Studies that did not meet these criteria were excluded. Additionally, we searched the references in the included articles for relevant research. The following data were extracted from included studies and incorporated into a qualitative synthesis: bibliographic information, study characteristics, population, intervention, comparison, outcomes, and AI-related information. The certainty of the evidence in the included studies was evaluated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation). RESULTS: A total of 15 studies published between 2015 and 2023 involving 899 participants aged approximately between 19 and 84 years, 60.7% (546/899) of whom were female participants, were included in this review. The interventions lasted between 2 and 26 weeks in the included studies. Recommender systems were the most commonly used AI technology in digital solutions for PA (10/15 studies), followed by conversational agents (4/15 studies). User acceptability and satisfaction were the HFs most frequently evaluated (5/15 studies each), followed by usability (4/15 studies). Regarding automated data collection for personalization and recommendation, most systems involved fitness trackers (5/15 studies). The certainty of the evidence analysis indicates moderate certainty of the effectiveness of AI-driven digital technologies in increasing PA (eg, number of steps, distance walked, or time spent on PA). Furthermore, AI-driven technology, particularly recommender systems, seems to positively influence changes in PA behavior, although with very low certainty evidence. CONCLUSIONS: Current research highlights the potential of AI-driven technologies to enhance PA, though the evidence remains limited. Longer-term studies are necessary to assess the sustained impact of AI-driven technologies on behavior change and habit formation. While AI-driven digital solutions for PA hold significant promise, further exploration into optimizing AI's impact on PA and effectively integrating AI and HFs is crucial for broader benefits. Thus, the implications for innovation management involve conducting long-term studies, prioritizing diversity, ensuring research quality, focusing on user experience, and understanding the evolving role of AI in PA promotion.

Patient selection for nonoperating room anesthesia.

PURPOSE OF REVIEW: Given the rapid growth of nonoperating room anesthesia (NORA) in recent years, it is essential to review its unique challenges as well as strategies for patient selection and care optimization. RECENT FINDINGS: Recent investigations have uncovered an increasing prevalence of older and higher ASA physical status patients in NORA settings. Although closed claim data regarding patient injury demonstrate a lower proportion of NORA cases resulting in a claim than traditional operating room cases, NORA cases have an increased risk of claim for death. Challenges within NORA include site-specific differences, limitations in ergonomic design, and increased stress among anesthesia providers. Several authors have thus proposed strategies focusing on standardizing processes, site-specific protocols, and ergonomic improvements to mitigate risks. SUMMARY: Considering the unique challenges of NORA settings, meticulous patient selection, risk stratification, and preoperative optimization are crucial. Embracing data-driven strategies and leveraging technological innovations (such as artificial intelligence) is imperative to refine quality control methods in targeted areas. Collaborative efforts led by anesthesia providers will ensure personalized, well tolerated, and improved patient outcomes across all phases of NORA care.

How does the consecutive use of intraoral scanners affect musculoskeletal health? A preliminary clinical study.

BACKGROUND: Minimizing muscle strain and reducing the risk of musculoskeletal disorders associated with intraoral scanner (IOS) usage require ergonomic awareness, device selection, and workplace adjustments in dental practice. This preliminary clinical study aimed to simulate intraoral scanning tasks using wired and wireless IOSs and assess muscle activation and fatigue for both types. MATERIALS AND METHODS: Fourteen participants performed intraoral scanning tasks using wired and wireless IOSs (i700; MEDIT), with weights of 280 g and 328 g, respectively. The same computer system and software conditions were maintained for both groups (N = 14 per IOS group). Electrodes were placed on arm, neck, and shoulder muscles, and maximal voluntary contraction (MVC) was measured. Surface electromyography (EMG) was performed during the simulation, and EMG values were normalized using MVC. The root mean square EMG (%MVC) and muscle fatigue (%) values were calculated. Statistical comparisons were performed using the Mann-Whitney U and Friedman tests, with the Bonferroni adjustment for multiple comparisons (α = 0.05). RESULTS: Arm (flexor digitorum superficialis) and neck muscles (left sternocleidomastoid and left splenius capitis) showed significantly higher EMG values with wireless IOS (P < 0.05). The neck (left sternocleidomastoid and right levator scapulae) and shoulder muscles (right trapezius descendens) demonstrated significantly higher muscle fatigue with wireless IOS (P < 0.05). CONCLUSIONS: The consecutive use of heavier wireless IOS may increase the risk of muscle activation and fatigue in certain muscles, which may have clinical implications for dentists in terms of ergonomics and musculoskeletal health.

A Rapid Review on the Effectiveness and Use of Wearable Biofeedback Motion Capture Systems in Ergonomics to Mitigate Adverse Postures and Movements of the Upper Body.

Work-related diseases and disorders remain a significant global health concern, necessitating multifaceted measures for mitigation. One potential measure is work technique training utilizing augmented feedback through wearable motion capture systems. However, there exists a research gap regarding its current effectiveness in both real work environments and controlled settings, as well as its ability to reduce postural exposure and retention effects over short, medium, and long durations. A rapid review was conducted, utilizing two databases and three previous literature reviews to identify relevant studies published within the last twenty years, including recent literature up to the end of 2023. Sixteen studies met the inclusion criteria, of which 14 were of high or moderate quality. These studies were summarized descriptively, and the strength of evidence was assessed. Among the included studies, six were rated as high quality, while eight were considered moderate quality. Notably, the reporting of participation rates, blinding of assessors, and a-priori power calculations were infrequently performed. Four studies were conducted in real work environments, while ten were conducted in controlled settings. Vibration feedback was the most common feedback type utilized (n = 9), followed by auditory (n = 7) and visual feedback (n = 1). All studies employed corrective feedback initiated by the system. In controlled environments, evidence regarding the effectiveness of augmented feedback from wearable motion capture systems to reduce postural exposure ranged from strong evidence to no evidence, depending on the time elapsed after feedback administration. Conversely, for studies conducted in real work environments, the evidence ranged from very limited evidence to no evidence. Future reach needs are identified and discussed.

A Novel IMU-Based System for Work-Related Musculoskeletal Disorders Risk Assessment.

This study introduces a novel wearable Inertial Measurement Unit (IMU)-based system for an objective and comprehensive assessment of Work-Related Musculoskeletal Disorders (WMSDs), thus enhancing workplace safety. The system integrates wearable technology with a user-friendly interface, providing magnetometer-free orientation estimation, joint angle measurements, and WMSDs risk evaluation. Tested in a cable manufacturing facility, the system was evaluated with ten female employees. The evaluation involved work cycle identification, inter-subject comparisons, and benchmarking against standard WMSD risk assessments like RULA, REBA, Strain Index, and Rodgers Muscle Fatigue Analysis. The evaluation demonstrated uniform joint patterns across participants (ICC=0.72±0.23) and revealed a higher occurrence of postures warranting further investigation, which is not easily detected by traditional methods such as RULA. The experimental results showed that the proposed system's risk assessments closely aligned with the established methods and enabled detailed and targeted risk assessments, pinpointing specific bodily areas for immediate ergonomic interventions. This approach not only enhances the detection of ergonomic risks but also supports the development of personalized intervention strategies, addressing common workplace issues such as tendinitis, low back pain, and carpal tunnel syndrome. The outcomes highlight the system's sensitivity and specificity in identifying ergonomic hazards. Future efforts should focus on broader validation and exploring the relative influence of various WMSDs risk factors to refine risk assessment and intervention strategies for improved applicability in occupational health.

Development of a virtual reality system usability questionnaire (VRSUQ).

Virtual reality (VR) has gained significant attention as a technology that provides immersive experiences similar to the real world. In order for a VR system to be accepted, usability needs to be guaranteed. Accordingly, VR-related researchers are continuing their efforts to improve VR systems by conducting usability evaluations. However, existing studies have limitations in that they cannot comprehensively evaluate the detailed properties of VR systems by using questionnaires developed for general product usability evaluation or focusing only on some usability aspects of VR systems. This suggests it may be difficult to fully capture usability issues in a VR system, and that it is necessary to develop a usability evaluation tool that reflects the specific characteristics of the VR system. Therefore, this study develops and proposes the Virtual Reality System Usability Questionnaire (VRSUQ). In the development of the questionnaire, items were structured based on a literature review and discussions with experts. To account for the diverse characteristics of VR systems, the validity of the questionnaire was verified through both exploratory and confirmatory factor analysis, utilizing data obtained from three distinct experimental studies that employed different VR systems. In addition, by comparing the results of VRSUQ with the results from the System Usability Scale, which is widely used for perceived usability evaluation, alternative possibilities for using VRSUQ are presented. Further testing on various VR platforms is needed to ensure the reliability and validity of VRSUQ, and as results from using VRSUQ are accumulated, it is expected to be widely used as a more powerful and robust VR-specific perceived usability evaluation tool.

Comparison of multi-task ergonomic assessment methods for risk of upper extremity and low back musculoskeletal disorders.

Work-related musculoskeletal disorder of upper extremity multi-task assessment methods (Revised Strain Index [RSI], Distal Upper Extremity Tool [DUET]) and manual handling multi-task assessment methods (Revised NIOSH Lifting Equation [RNLE], Lifting Fatigue Failure Tool [LiFFT]) were compared. RSI and DUET showed a strong correlation (rs = 0.933, p < 0.001) where increasing risk factor exposure resulted in increasing outputs for both methods. RSI and DUET demonstrated fair agreement (κ = 0.299) in how the two methods classified outputs into risk categories (high, moderate or low) when assessing the same tasks. The RNLE and LiFFT showed a strong correlation (rs = 0.903, p = 0.001) where increasing risk factor exposure resulted in increasing outputs, and moderate agreement (κ = 0.574) in classifying the outputs into risk categories (high, moderate or low) when assessing the same tasks. The multi-task assessment methods provide consistent output magnitude rankings in terms of increasing exposure, however some differences exist between how different methods classify the outputs into risk categories.

Active workstations: A literature review on workplace sitting.

The purpose of this paper is to further understand current literature on prolonged sitting, sitting posture and active sitting solutions. This paper is divided into three sections: The first section (Part I) is a comprehensive overview of the literature on how a static prolonged seated posture can affect: spinal health, trunk posture, contact pressure/discomfort development and vascular issues. The second section (Part II) reviews and qualitatively compares the four working postures recognized in ANSI/HFES 100-2007: reclined sitting, upright sitting, declined sitting and standing. The final section (Part III) is a summary of research on active chairs that revolves around the two types of movement patterns: 1- sustaining continual movement over a range of postures, occasionally reaching neutral lordosis, and 2- maintaining high frequency and duration of daily light contractile activity in the legs (or lower limbs).

Effect of exercise given to factory workers with ergonomics training on pain and functionality: A randomized controlled trial.

BACKGROUND: Exercise and manual therapy are used with pharmacological interventions to manage low back pain and prevent work-related musculoskeletal disorders. However, the potential benefits of incorporating exercise and ergonomics training for factory workers experiencing low back pain have not been definitively established. OBJECTIVE: The objective of this study was to assess the impact of ergonomics training with exercises on pain, functionality, sleep, and fatigue among factory employees experiencing low back pain. METHODS: This research was conducted as a randomized controlled trial involving workers with back pain employed in a plastic molding factory in Gebze, Kocaeli. Both groups received ergonomics training, but only the experimental group was given exercise training inclusive of stretching and core stabilization exercises. The workers in the experimental group were instructed to perform the exercises regularly for three days a week over a period of eight weeks. The McGill Pain Questionnaire (MPQ), the Visual Analogue Scale (VAS), the Fatigue Severity Scale (FSS), the Pittsburgh Sleep Quality Index (PSQI), and the Oswestry Disability Index (ODI) were used for pre-and post-treatment assessment. RESULTS: The ODI, FSS, PSQI, and MPQ scores were significantly reduced in both groups. In the intergroup comparison, the exercise group showed a significantly greater decrease in all test scores compared to the control group. CONCLUSION: The exercise group showed a statistically significant decrease in ODI, FSS, MPQ, and PSQI scores compared to the control group. This study demonstrated that exercise is a more effective practice than ergonomic training for factory workers suffering from chronic low back pain.

Assessment of Surgeons' Stress Levels with Digital Sensors during Robot-Assisted Surgery: An Experimental Study.

Robot-Assisted Minimally Invasive Surgery (RAMIS) marks a paradigm shift in surgical procedures, enhancing precision and ergonomics. Concurrently it introduces complex stress dynamics and ergonomic challenges regarding the human-robot interface and interaction. This study explores the stress-related aspects of RAMIS, using the da Vinci XI Surgical System and the Sea Spikes model as a standard skill training phantom to establish a link between technological advancement and human factors in RAMIS environments. By employing different physiological and kinematic sensors for heart rate variability, hand movement tracking, and posture analysis, this research aims to develop a framework for quantifying the stress and ergonomic loads applied to surgeons. Preliminary findings reveal significant correlations between stress levels and several of the skill-related metrics measured by external sensors or the SURG-TLX questionnaire. Furthermore, early analysis of this preliminary dataset suggests the potential benefits of applying machine learning for surgeon skill classification and stress analysis. This paper presents the initial findings, identified correlations, and the lessons learned from the clinical setup, aiming to lay down the cornerstones for wider studies in the fields of clinical situation awareness and attention computing.

Ergonomic benefit using heads-up display compared to conventional surgical microscope in Japanese ophthalmologists.

PURPOSE: Occupational musculoskeletal disorders are prevalent in ophthalmic surgeons and can impact surgeons' well-being and productivity. Heads-up displays may reduce ergonomic stress compared to conventional microscopes. This cross-sectional, non-interventional study compared ergonomic experience between heads-up display and conventional ocular microscopes. METHODS: The study protocol was approved by the independent ethics committee and nonprofit organization MINS Institutional Review Board. An online questionnaire was distributed to a sample of ophthalmic surgeons in Japan with experience operating with heads-up display. The questionnaire captured surgeon-specific variables, the standardized Nordic Musculoskeletal Questionnaire, and custom questions to compare heads-up display and conventional microscope and understand long-term impacts of musculoskeletal disorders. RESULTS: Analysis was conducted on responses from 67 surgeons with a mean 25 years of practice and 2.7 years using heads-up display. Many surgeons agreed or strongly agreed that heads-up display reduced the severity (40%) and frequency (40%) of pain and discomfort, improved posture (61%), and improved overall comfort (61%). Of respondents who experienced asthenopia (n = 59) or pain/discomfort during operation (n = 61), 54% reported improvement in asthenopia and 72% reported feeling less pain/discomfort since using heads-up display. Overall, 69% reported preference for heads-up display. CONCLUSION: This study provides novel data on musculoskeletal disorders and the long-term impacts of ergonomic strain reported by ophthalmologists building on existing literature demonstrating ergonomic and other advantages of heads-up display. Future studies with objective ergonomic assessment are warranted to validate these findings.

A Brain-Controlled and User-Centered Intelligent Wheelchair: A Feasibility Study.

Recently, due to physical aging, diseases, accidents, and other factors, the population with lower limb disabilities has been increasing, and there is consequently a growing demand for wheelchair products. Modern product design tends to be more intelligent and multi-functional than in the past, with the popularization of intelligent concepts. This supports the design of a new, fully functional, intelligent wheelchair that can assist people with lower limb disabilities in their day-to-day life. Based on the UCD (user-centered design) concept, this study focused on the needs of people with lower limb disabilities. Accordingly, the demand for different functions of intelligent wheelchair products was studied through a questionnaire survey, interview survey, literature review, expert consultation, etc., and the function and appearance of the intelligent wheelchair were then defined. A brain-machine interface system was developed for controlling the motion of the intelligent wheelchair, catering to the needs of disabled individuals. Furthermore, ergonomics theory was used as a guide to determine the size of the intelligent wheelchair seat, and eventually, a new intelligent wheelchair with the features of climbing stairs, posture adjustment, seat elevation, easy interaction, etc., was developed. This paper provides a reference for the design upgrade of the subsequently developed intelligent wheelchair products.

Designing digital patient experiences: The digital health design framework.

BACKGROUND: Digital health (DH) brings considerable benefits, but it comes with potential risks. Human Factors (HF) play a critical role in providing high-quality and acceptable DH solutions. Consultation with designers is crucial for reflecting on and improving current DH design practices. OBJECTIVES: We investigated the general DH design processes, challenges, and corresponding strategies that can improve the digital patient experience (PEx). METHODS: A semi-structured interview study with 24 design professionals. All audio recordings were transcribed, deidentified, grammatically corrected, and imported into ATLAS.ti for data analysis. Three coders participated in data coding following the thematic analysis approach. RESULTS: We identified eight DH design stages and grouped them into four phases: preparation, problem-thinking, problem-solving, and implementation. The analysis presented twelve design challenges associated with contextual, practical, managerial, and commercial aspects that can hinder the design process. We identified eight common strategies used by respondents to tackle these challenges. CONCLUSIONS: We propose a Digital Health Design (DHD) framework to improve the digital PEx. It provides an overview of design deliverables, activities, stakeholders, challenges, and corresponding strategies for each design stage.

Defining a systems framework for characterizing physical work demands with wearable sensors.

Measuring the physical demands of work is important in understanding the relationship between exposure to these job demands and their impact on the safety, health, and well-being of working people. However, work is changing and our knowledge of job demands should also evolve in anticipation of these changes. New opportunities exist for noninvasive long-term measures of physical demands through wearable motion sensors, including inertial measurement units, heart rate monitors, and muscle activity monitors. Inertial measurement units combine accelerometers, gyroscopes, and magnetometers to provide continuous measurement of a segment's motion and the ability to estimate orientation in 3-dimensional space. There is a need for a system-thinking perspective on how and when to apply these wearable sensors within the context of research and practice surrounding the measurement of physical job demands. In this paper, a framework is presented for measuring the physical work demands that can guide designers, researchers, and users to integrate and implement these advanced sensor technologies in a way that is relevant to the decision-making needs for physical demand assessment. We (i) present a literature review of the way physical demands are currently being measured, (ii) present a framework that extends the International Classification of Functioning to guide how technology can measure the facets of work, (iii) provide a background on wearable motion sensing, and (iv) define 3 categories of decision-making that influence the questions that we can ask and measures that are needed. By forming questions within these categories at each level of the framework, this approach encourages thinking about the systems-level problems inherent in the workplace and how they manifest at different scales. Applying this framework provides a systems approach to guide study designs and methodological approaches to study how work is changing and how it impacts worker safety, health, and well-being.

Equivalent weight: Application of the assessment method on real task conducted by railway workers wearing a back support exoskeleton.

Commonly used risk indexes, such as the NIOSH Lifting Index, do not capture the effect of exoskeletons. This makes it difficult for Health and Safety professionals to rigorously assess the benefit of such devices. The community requires a simple method to assess the effectiveness of back-support exoskeleton's (BSE) in possibly reducing ergonomic risk. The method introduced in this work is termed "Equivalent Weight" (EqW) and it proposes an interpretation of the effect built on the benefit delivered through reduced activation of the erector spinae (ES). This manifests itself as an apparent reduction of the lifted load perceived by the wearer. This work presents a pilot study where a practical application of the EqW method is used to assess the ergonomic risk in manual material handling (MMH) when using a back support exoskeleton (StreamEXO). The results are assessed by combining observational measurements from on-site testing with five different workers and quantitative measures of the muscle activity reduction achieved during laboratory evaluation with ten workers. These results will show that when lifting, lowering, and carrying a 19 kg load the StreamEXO can reduce risk by up to two levels (from "high" to "low") in the target sub-tasks. The Lifting index (LI) was reduced up to 64% when examining specific sub-tasks and the worker's movement conduction.

Integrating human factors engineering into your pediatric radiology practice.

Human factors engineering involves the study and development of methods aimed at enhancing performance, improving safety, and optimizing user satisfaction. The focus of human factors engineering encompasses the design of work environments and an understanding of human mental processes to prevent errors. In this review, we summarize the history, applications, and impacts of human factors engineering on the healthcare field. To illustrate these applications and impacts, we provide several examples of how successful integration of a human factors engineer in our pediatric radiology department has positively impacted various projects. The successful integration of human factors engineering expertise has contributed to projects including improving response times for portable radiography requests, deploying COVID-19 response resources, informing the redesign of scheduling workflows, and implementation of a virtual ergonomics program for remote workers. In sum, the integration of human factors engineering insight into our department has resulted in tangible benefits and has also positioned us as proactive contributors to broader hospital-wide improvements.

A systematic review of camera monitor system display layout designs: Integration of existing knowledge.

Despite the growing interest in mirrorless vehicles equipped with a camera monitor system (CMS), the human factors research findings on CMS display layout design have not been synthesized yet, hindering the application of the knowledge and the identification of future research directions. In an effort to address the 'lack of integration of the existing knowledge', this literature review addresses the following research questions: 1) what CMS display layout designs have been considered/developed by academic researchers and by automakers, respectively?; 2) among possible CMS display layout design alternatives, which ones have not yet been examined through human factors evaluation studies?; and 3) how do the existing human factors studies on the evaluation of different CMS display layout designs vary in the specifics of research? This review provides significant implications for the ergonomic design of CMS display layouts, including some potential design opportunities and future research directions.

Reducing musculoskeletal disorders in iron ore mine operators: A fuzzy-based intervention approach.

BACKGROUND: This study focuses on evaluating the exposure to whole-body vibration (WBV) and association of musculoskeletal disorders (MSDs) with various risk factors among dumper operators in the mining industry. Despite the issue's significance, prior research has been limited. OBJECTIVE: The study introduces a novel fuzzy-based approach for identifying, selecting, and prioritizing safety measures to mitigate MSD risks. METHODS: Data collection comprised face-to-face interviews, anthropometric measurements, Rapid Upper Limb Assessment (RULA) scoring for posture assessment, and the Nordic Musculoskeletal questionnaire for assessment of MSD prevalence. Multiple linear and logistic regression models were used to analyse the contributing risk factors to MSDs and WBV exposure. These risk factors formed the basis for a practical approach to select appropriate safety measures based on fuzzy based aggregation method of expert's judgment aimed at mitigating the risk of MSDs. RESULTS: The results revealed that the risk factors such as poor work posture, WBV exposure and poor seat design were significantly associated with neck (adjusted odds ratio aOR = 4.81), upper limb and shoulder (aOR = 3.28), upper back (aOR = 5.09), and lower back pain (aOR = 3.67) at p < 0.05. Using these factors to formulate safety measures to reduce MSD risk, the minimization of sharp turns and abrupt changes in elevation in designing the haul roads, scheduled maintenance practices, and ergonomic seat design were found as important safety measures in this study. CONCLUSION: Our unique methodological approach in occupational health research could be highly beneficial for tailoring safety measures at the unit level with minimal effort.

Effectiveness of and preference for a picture-based home office ergonomics assessment compared to a traditional in-person office ergonomics assessment: A case study from a Canadian University during the COVID-19 pandemic.

During the COVID-19 pandemic, telework best practices decreased in importance compared to the need for social distancing. It is important that ergonomics assessments for home office workstations are equally as effective as assessment for traditional offices to maintain teleworker wellbeing. The purpose of this case study is to compare a remote, picture-based, home office assessment to a traditional, in-person, office assessment for employees of one Canadian University. Intraclass Correlation Coefficients (ICCs) and Bland-Altman Analyses (BAAs) revealed that the two methods provide repeatable results, with good agreement. Feedback from the participants suggested that picture-based assessments were as effective as in-person assessments; but that picture-based assessments could be improved with video conferencing to discuss findings and ask follow-up questions. Participants found value in remote assessments and, while they preferred in-person assessments, picture-based assessments are suitable when needed as they allow for many assessments to be completed without violating social distancing restrictions.