Digital Health Technology Use Among Older Adults: Exploring the Impact of Frailty on Utilization, Purpose, and Satisfaction in Korea.

BACKGROUND: The importance of digital technology is increasing among older adults. In this study, the digital health technology utilization status, purpose, and satisfaction of older adults were investigated according to frailty. METHODS: A face-to-face survey was conducted among adults aged 65 years or older. Frailty was defined using the Korean version of the fatigue, resistance, ambulation, illnesses, and loss of weight scale. RESULTS: A total of 505 participants completed the survey, with 153 (30.3%) identified as pre-frail or frail and 352 (69.7%) as healthy. All respondents used smartphones; 440 (87.1%) were application users, and 290 (57.4%) were healthcare application users. Wearable devices were used by only 36 patients (7.1%). Pre-frail or frail respondents used social media more frequently than healthy respondents (19.4% vs. 7.4%, P < 0.001). Among the respondents, 319 (63.2%) were not able to install or delete the application themselves, and 277 (54.9%) stated that the application was recommended by their children (or partner). Pre-frail and frail respondents used more healthcare applications to obtain health information (P = 0.002) and were less satisfied with wearable devices (P = 0.02). CONCLUSION: The usage rate of digital devices, including mobile phones among older adults in Korea is high, whereas that of wearable devices is low. There was a notable difference in the services used by pre-frail and frail respondents compared to healthy respondents. Therefore, when developing digital devices for pre-frail and frail older adults, it is crucial to incorporate customized services that meet their unique needs, particularly those services that they frequently use.

The Hospitalist-Oncologist co-ManagemEnt (HOME) system improves hospitalization outcomes of patients with cancer.

BACKGROUND: The hospitalist system has been introduced to improve the quality and safety of inpatient care. As its effectiveness has been confirmed in previous studies, the hospitalist system is spreading in various fields. However, few studies have investigated the feasibility and value of hospitalist-led care of patients with cancer in terms of quality and safety measures. This study aimed to evaluate the efficacy of the Hospitalist-Oncologist co-ManagemEnt (HOME) system. METHODS: Between January 1, 2019, and January 31, 2021, we analyzed 591 admissions before and 1068 admissions after the introduction of HOME system on January 1, 2020. We compared the length of stay and the types and frequencies of safety events between the conventional system and the HOME system, retrospectively. We also investigate rapid response system activation, cardiopulmonary resuscitation, unplanned intensive care unit transfer, all-cause in-hospital mortality, and 30-day re-admission or emergency department visits. RESULTS: The average length of stay (15.9 days vs. 12.9 days, P < 0.001), frequency of safety events (5.6% vs. 2.8%, P = 0.006), rapid response system activation (7.3% vs. 2.2%, P < 0.001) were significantly reduced after the HOME system introduction. However, there was no statistical difference in frequencies of cardiopulomonary resuscitation and intensive care unit transfer, all-cause in-hospital morality, 30-day unplanned re-admission or emergency department visits. CONCLUSIONS: The study suggests that the HOME system provides higher quality of care and safer environment compared to conventional oncologist-led team-based care, and the efficiency of the medical delivery system could be increased by reducing the hospitalization period without increase in 30-day unplanned re-admission.

MDED-Framework: A Distributed Microservice Deep-Learning Framework for Object Detection in Edge Computing.

The demand for deep learning frameworks capable of running in edge computing environments is rapidly increasing due to the exponential growth of data volume and the need for real-time processing. However, edge computing environments often have limited resources, necessitating the distribution of deep learning models. Distributing deep learning models can be challenging as it requires specifying the resource type for each process and ensuring that the models are lightweight without performance degradation. To address this issue, we propose the Microservice Deep-learning Edge Detection (MDED) framework, designed for easy deployment and distributed processing in edge computing environments. The MDED framework leverages Docker-based containers and Kubernetes orchestration to obtain a pedestrian-detection deep learning model with a speed of up to 19 FPS, satisfying the semi-real-time condition. The framework employs an ensemble of high-level feature-specific networks (HFN) and low-level feature-specific networks (LFN) trained on the MOT17Det dataset, achieving an accuracy improvement of up to AP50 and AP0.18 on MOT20Det data.

Understanding contributing factors to exoskeleton use-intention in construction: a decision tree approach using results from an online survey.

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 Behavioural 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.Practitioner summary: This study used decision trees to identify key factors influencing the use-intention of occupational exoskeletons (EXOs) in construction, using online survey data. Key factors identified included EXOs becoming standard equipment, fatigue reduction, and performance improvement. Final trees provide intuitive visual representations of the decision-making process for workers to use EXOs.

Effects of an arm-support exoskeleton on perceived work intensity and musculoskeletal discomfort: An 18-month field study in automotive assembly.

BACKGROUND: Exoskeleton (EXO) technologies are a promising ergonomic intervention to reduce the risk of work-related musculoskeletal disorders, with efficacy supported by laboratory- and field-based studies. However, there is a lack of field-based evidence on long-term effects of EXO use on physical demands. METHODS: A longitudinal, controlled research design was used to examine the effects of arm-support exoskeleton (ASE) use on perceived physical demands during overhead work at nine automotive manufacturing facilities. Data were collected at five milestones (baseline and at 1, 6, 12, and 18 months) using questionnaires. Linear mixed models were used to understand the effects of ASE use on perceived work intensity and musculoskeletal discomfort (MSD). Analyses were based on a total of 41 participants in the EXO group and 83 in a control group. RESULTS: Across facilities, perceived work intensity and MSD scores did not differ significantly between the EXO and control groups. In some facilities, however, neck and shoulder MSD scores in the EXO group decreased over time. Wrist MSD scores in the EXO group in some facilities remained unchanged, while those scores increased in the control group over time. Upper arm and low back MSD scores were comparable between the experimental groups. CONCLUSION: Longitudinal effects of ASE use on perceived physical demands were not found, though some suggestive results were evident. This lack of consistent findings is discussed, particularly supporting the need for systematic and evidence-based ASE implementation approaches in the field that can guide the optimal selection of a job for ASE use.

Accuracy and Diversity of Wearable Device-Based Gait Speed Measurement Among Older Men: Observational Study.

BACKGROUND: Gait speed measurements are widely used in clinical practice, as slow gait is a major predictor of frailty and a diagnostic criterion for sarcopenia. With the development of wearable devices, it is possible to estimate the gait speed in daily life by simply wearing the device. OBJECTIVE: This study aims to accurately determine the characteristics of daily life gait speed and analyze their association with sarcopenia. METHODS: We invited community-dwelling men aged >50 years who had visited the outpatient clinic at a tertiary university hospital to participate in the study. Daily life gait speed was assessed using a wearable smart belt (WELT) for a period of 4 weeks. Data from participants who wore the smart belt for at least 10 days during this period were included. After 4 weeks, data from a survey about medical and social history, usual gait speed measurements, handgrip strength measurements, and dual-energy x-ray absorptiometry were analyzed. RESULTS: A total of 217,578 daily life gait speed measurements from 106 participants (mean age 71.1, SD 7.6 years) were analyzed. The mean daily life gait speed was 1.23 (SD 0.26) m/s. The daily life gait speed of the participants varied according to the time of the day and day of the week. Daily life gait speed significantly slowed down with age (P<.001). Participants with sarcopenia had significantly lower mean daily life gait speed (mean 1.12, SD 0.11 m/s) than participants without sarcopenia (mean 1.23, SD 0.08 m/s; P<.001). Analysis of factors related to mean daily life gait speed showed that age and skeletal muscle mass of the lower limbs were significantly associated characteristics. CONCLUSIONS: More diverse and accurate information about gait speed can be obtained by measuring daily life gait speed using a wearable device over an appropriate period, compared with one-time measurements performed in a laboratory setting. Importantly, in addition to age, daily life gait speed is significantly associated with skeletal muscle mass of the lower limbs.

A Smart Diaper System Using Bluetooth and Smartphones to Automatically Detect Urination and Volume of Voiding: Prospective Observational Pilot Study in an Acute Care Hospital.

BACKGROUND: Caregivers of patients who wear conventional diapers are required to check for voiding every hour because prolonged wearing of wet diapers causes health problems including diaper dermatitis and urinary tract infections. However, frequent checking is labor intensive and disturbs patients' and caregivers' sleep. Furthermore, assessing patients' urine output with diapers in an acute care setting is difficult. Recently, a smart diaper system with wetness detection technology was developed to solve these issues. OBJECTIVE: We aimed to evaluate the applicability of the smart diaper system for urinary detection, its accuracy in measuring voiding volume, and its effect on incontinence-associated dermatitis (IAD) occurrence in an acute care hospital. METHODS: This prospective, observational, single-arm pilot study was conducted at a single tertiary hospital. We recruited 35 participants aged ≥50 years who were wearing diapers due to incontinence between August and November 2020. When the smart diaper becomes wet, the smart diaper system notifies the caregiver to change the diaper and measures voiding volume automatically. Caregivers were instructed to record the weight of wet diapers on frequency volume charts (FVCs). We determined the voiding detection rate of the smart diaper system and compared the urine volume as automatically calculated by the smart diaper system with the volume recorded on FVCs. Agreement between the two measurements was estimated using a Bland-Altman plot. We also checked for the occurrence or aggravation of IAD and bed sores. RESULTS: A total of 30 participants completed the protocol and 390 episodes of urination were recorded. There were 108 records (27.7%) on both the FVCs and the smart diaper system, 258 (66.2%) on the FVCs alone, 18 (4.6%) on the smart diaper system alone, and 6 (1.5%) on the FVCs with sensing device lost. The detection rate of the smart diaper system was 32.8% (126/384). When analyzing records concurrently listed in both the FVCs and the smart diaper system, linear regression showed a strong correlation between the two measurements (R2=0.88, P<.001). The Bland-Altman assessment showed good agreement between the two measurements, with a mean difference of -4.2 mL and 95% limits of agreement of -96.7 mL and 88.3 mL. New occurrence and aggravation of IAD and bed sores were not observed. Bed sores improved in one participant. CONCLUSIONS: The smart diaper system showed acceptable accuracy for measuring urine volume and it could replace conventional FVCs in acute setting hospitals. Furthermore, the smart diaper system has the potential advantage of preventing IAD development and bed sore worsening. However, the detection rate of the smart diaper system was lower than expected. Detection rate polarization among participants was observed, and improvements in the user interface and convenience are needed for older individuals who are unfamiliar with the smart diaper system.

An exploratory study comparing three work/rest schedules during simulated repetitive precision work.

The pattern of work and rest can influence both physical fatigue and task performance in manual operations. However, there is relatively limited evidence regarding the influences of specific work/rest schedules in tasks requiring high repetitiveness and precision demands, along with relatively low exertion levels. Eighteen participants completed an exploratory study that simulated such tasks, to compare the effects of three distinct work/rest schedules (i.e. short frequent [short] and long infrequent breaks [long], and a self-selected schedule) on muscle fatigue, task performance (in terms of accuracy and speed), and preference. Schedules with long or self-selected breaks generally induced less muscle fatigue, compared with the short break condition. Participants preferred the self-selected condition the most and the long-break condition the least. The different schedules tested did not influence task performance. A self-selected schedule may be beneficial for repetitive precision task, to achieve a balance across muscle fatigue, task performance, and individual preference. Practitioner summary: Influences of three work/rest schedules (i.e. short and long breaks, and a self-selected schedule) on fatigue, performance, and preference were explored during repetitive precision tasks. Schedules with long or self-selected breaks induced less muscle fatigue and none of the three schedules influenced performance. A self-selected schedule was the most preferred.

Perturbation-based balance training targeting both slip- and trip-induced falls among older adults: a randomized controlled trial.

BACKGROUND: Falls are the leading cause of injuries among older adults. Perturbation-based balance training (PBT) is an innovative approach to fall prevention that aims to improve the reactive balance response following perturbations such as slipping and tripping. Many of these PBT studies have targeted reactive balance after slipping or tripping, despite both contributing to a large proportion of older adult falls. The goal of this randomized controlled trial was to evaluate the effects of PBT targeting slipping and tripping on laboratory-induced slips and trips. To build upon prior work, the present study included: 1) a control group; 2) separate training and assessment sessions; 3) PBT methods potentially more amenable for use outside the lab compared to methods employed elsewhere, and 4) individualized training for older adult participants. METHODS: Thirty-four community-dwelling, healthy older adults (61-75 years) were assigned to PBT or a control intervention using minimization. Using a parallel design, reactive balance (primary outcome) and fall incidence were assessed before and after four sessions of BRT or a control intervention involving general balance exercises. Assessments involved exposing participants to an unexpected laboratory-induced slip or trip. Reactive balance and fall incidence were compared between three mutually-exclusive groups: 1) baseline participants who experienced a slip (or trip) before either intervention, 2) post-control participants who experienced a slip (or trip) after the control intervention, and 3) post-PBT participants who experienced a slip (or trip) after PBT. Neither the participants nor investigators were blinded to group assignment. RESULTS: All 34 participants completed all four sessions of their assigned intervention, and all 34 participants were analyzed. Regarding slips, several measures of reactive balance were improved among post-PBT participants when compared to baseline participants or post-control participants, and fall incidence among post-PBT participants (18%) was lower than among baseline participants (80%). Regarding trips, neither reactive balance nor fall incidence differed between groups. CONCLUSIONS: PBT targeting slipping and tripping improved reactive balance and fall incidence after laboratory-induced slips. Improvements were not observed after laboratory-induced trips. The disparity in efficacy between slips and trip may have resulted from differences in dosage and specificity between slip and trip training. TRIAL REGISTRATION: Name of Clinical Trial Registry: clinicaltrials.gov Trial Registration number: NCT04308239. Date of Registration: March 13, 2020 (retrospectively registered).

Effects of Two Passive Back-Support Exoskeletons on Muscle Activity, Energy Expenditure, and Subjective Assessments During Repetitive Lifting.

OBJECTIVE: The aim of this study was to explore the efficacy of two different passive back-support exoskeleton (BSE) designs during repetitive lifting in different postures. BACKGROUND: Although BSEs have been proposed as a potential intervention for reducing physical demands, limited information is available about the impacts of different exoskeleton designs in diverse work scenarios. METHOD: Eighteen participants (gender-balanced) performed lab-based simulations of repetitive lifting tasks. These tasks were performed in 12 different conditions, involving two BSEs and a control condition, two levels of lifting symmetry (symmetric and asymmetric), and two postures (standing and kneeling). Outcome measures described muscle activity and energy expenditure, along with perceived discomfort, balance, and usability. RESULTS: Using both BSEs significantly reduced peak activity of the trunk extensor muscles (by ~10%-28%) and energy expenditure (by ~4%-13%) in all conditions tested. Such reductions, though, were task dependent and differed between the two BSEs. In most of the tested conditions, using BSEs positively affected subjective responses regarding perceived exertion and usability. CONCLUSION: Our results suggest that the beneficial effects of a BSE are task specific and depend on the specific BSE design approach. More work is needed, though, to better characterize this task specificity and to determine the generalizability of BSE effects on objective and subjective outcomes for a wider range of conditions and users. APPLICATION: Our results provide new evidence to guide the selection and application of passive BSE designs in diverse lifting tasks.

Biomechanical Evaluation of Passive Back-Support Exoskeletons in a Precision Manual Assembly Task: "Expected" Effects on Trunk Muscle Activity, Perceived Exertion, and Task Performance.

OBJECTIVE: To assess the efficacy of two different passive back-support exoskeleton (BSE) designs, in terms of trunk muscle activity, perceived low-back exertion, and task performance. BACKGROUND: BSEs have the potential to be an effective intervention for reducing low-back physical demands, yet little is known about the impacts of different designs in work scenarios requiring varying degrees of symmetric and asymmetric trunk bending during manual assembly tasks. METHOD: Eighteen participants (gender balanced) completed lab-based simulations of a precision manual assembly task using a "grooved pegboard." This was done in 26 different conditions (20 unsupported; 6 supported, via a chair), which differed in vertical height, horizontal distance, and orientation. RESULTS: Using both BSEs reduced metrics of trunk muscle activity in many task conditions (≤47% reductions when using BackX™ and ≤24% reductions when using Laevo™). Such reductions, though, were more pronounced in the conditions closer to the mid-sagittal plane and differed between the two BSEs tested. Minimal effects on task completion times or ratings of perceived exertion were found for both BSEs. CONCLUSION: Our findings suggest that using passive BSEs can be beneficial for quasi-static manual assembly tasks, yet their beneficial effects can be task specific and specific to BSE design approaches. Further work is needed, though, to better characterize this task specificity and to assess the generalizability of different BSE design approaches in terms of physical demands, perceived exertion, and task performance. APPLICATION: These results can help guide the choice and application of passive BSE designs for diverse work scenarios involving nonneutral trunk postures.

Modelling performance during repetitive precision tasks using wearable sensors: a data-driven approach.

In modern manufacturing systems, especially assembly lines, human input is a critical resource to provide dexterity and flexibility. However, the repetitive precision tasks common in assembly lines can have adverse effects on workers and overall system performance. We present a data-driven approach to evaluating task performance using wearable sensor data (kinematics, electromyography and heart rate). Eighteen participants (gender-balanced) completed repeated cycles of maze tracking and assembly/disassembly. Various combinations of input data types and classification algorithms were used to model task performance. The use of the linear discriminant analysis (LDA) algorithm and kinematic data provided the most promising classification performance. The highest model accuracy was found using the LDA algorithm and all data types, with respective levels of 62.4, 88.6, 85.8 and 94.1% for predicting maze errors, maze speed, assembly/disassembly errors and assembly/disassembly speed. The presented approach provides the possibility for real-time, on-line and comprehensive monitoring of system performance in assembly-lines or similar industries. Practitioner summary: This paper proposed models the repetitive precision task performance using data collected from wearable sensors. The use of the LDA algorithm and kinematic data provided the most promising classification performance. The presented approach provides the possibility for real-time, on-line and comprehensive monitoring of system performance in assembly lines or similar industries. Abbreviations: AD: anterior deltoid; BB: biceps brachii; ECR: extensor carpi radialis; ECU: extensor carpi ulnaris; FCR: flexor carpi radialis; FCU: flexor carpi ulnaris; FN: false negatives; FP: false positives; HR: heart rate; HRR: heart rate reserve; IMUs: inertial measurement units; kNN: k-nearest neighbors; LDA: linear discriminant analysis; MD: medial deltoid; MF: median power frequency; MNF: mean power frequency; MVIC: maximum voluntary isometric contraction; nRMS: normalized root-mean-square amplitudes; PD: posterior deltoid; RandFor: random forests; RHR: resting heart rate; RMS: root-mean-square amplitudes; sEMG: surface electromyographic; SVM: support vector machines; TB: triceps brachii medial; TN: true negatives; TP: true positives; t-SNE: t-distributed Stochastic Neighbor Embedding; UT: upper trapezius.

Impact of task design on task performance and injury risk: case study of a simulated drilling task.

Existing evidence is limited regarding the influence of task design on performance and ergonomic risk, or the association between these two outcomes. In a controlled experiment, we constructed a mock fuselage to simulate a drilling task common in aircraft manufacturing, and examined the effect of three levels of workstation adjustability on performance as measured by productivity (e.g. fuselage completion time) and quality (e.g. fuselage defective holes), and ergonomic risk as quantified using two common methods (rapid upper limb assessment and the strain index). The primary finding was that both productivity and quality significantly improved with increased adjustability, yet this occurred only when that adjustability succeeded in reducing ergonomic risk. Supporting the inverse association between ergonomic risk and performance, the condition with highest adjustability created the lowest ergonomic risk and the best performance while there was not a substantial difference in ergonomic risk between the other two conditions, in which performance was also comparable. Practitioner Summary: Findings of this study supported a causal relationship between task design and both ergonomic risk and performance, and that ergonomic risk and performance are inversely associated. While future work is needed under more realistic conditions and a broader population, these results may be useful for task (re)design and to help cost-justify some ergonomic interventions.

Effect of muscle mass on toxicity and survival in patients with colon cancer undergoing adjuvant chemotherapy.

PURPOSE: The purpose of this study was to elucidate the effect of decreased muscle mass on the toxicity and survival of patients with colon cancer treated with adjuvant chemotherapy after surgery. METHODS: We reviewed the data of 229 consecutive patients with stage III colon cancer who received adjuvant oxaliplatin, 5-fluorouracil, and leucovorin chemotherapy at a single center between 2003 and 2010. Baseline muscle mass was assessed by measuring the cross-sectional area of the psoas muscle at the level of the fourth lumbar vertebra on computed tomography images. Effects of muscle mass on toxicity of chemotherapy and survival were assessed. RESULTS: The median age of the 229 patients was 61 years (range, 28-80) and 134 (58.5 %) were men. The mean psoas muscle mass index (PI, psoas muscle area divided by height(2) [mm(2)/m(2)]) was 548.3. A 1 SD decrement in the PI was associated with an increase in all grade 3-4 toxicities in univariate (OR = 1.69, 95 % CI = 1.18-2.27) and multivariate (OR = 1.56, 95 % CI = 1.05-2.38) analyses. In univariate analysis, the PI was not associated with overall survival. However, multivariate analysis showed that a 1 SD decrement in the PI increased the hazard of overall mortality by 85 % (HR = 1.85, 95 % CI = 1.10-3.13). This effect of the PI on mortality was maintained in subgroup analyses, especially in older and obese patients. CONCLUSIONS: Decreased muscle mass was associated with increased risk of grade 3-4 toxicity and poor prognosis in patients with stage III colon cancer.

Evaluation of two approaches for aligning data obtained from a motion capture system and an in-shoe pressure measurement system.

An in-shoe pressure measurement (IPM) system can be used to measure center of pressure (COP) locations, and has fewer restrictions compared to the more conventional approach using a force platform. The insole of an IPM system, however, has its own coordinate system. To use an IPM system along with a motion capture system, there is thus a need to align the coordinate systems of the two measurement systems. To address this need, the current study examined two different approaches-rigid body transformation and nonlinear mapping (i.e., multilayer feed-forward neural network (MFNN))-to express COP measurements from an IPM system in the coordinate system of a motion capture system. Ten participants (five male and five female) completed several simulated manual material handling (MMH) activities, and during these activities the performance of the two approaches was assessed. Results indicated that: (1) performance varied between MMH activity types; and (2) a MFNN performed better than or comparable to the rigid body transformation, depending on the specific input variable sets used. Further, based on the results obtained, it was argued that a nonlinear mapping vs. rigid body transformation approach may be more effective to account for shoe deformation during MMH or potentially other types of physical activity.

An evaluation of classification algorithms for manual material handling tasks based on data obtained using wearable technologies.

With recent progress in wearable measurement systems, physical exposures can be feasibly assessed at high precision in the workplace. Such systems, however, generally lack contextual information for a given job (e.g., task type, duration). To extract such information, we explored three classification algorithms to classify manual material handling (MMH) tasks during a simulated job in a laboratory, using several combinations of outputs from commercially available inertial motion capture and in-shoe pressure measurement systems. A total of 10 participants completed three replications of four cycles of a simulated job. Precision and recall values of ≥ ∼90% and 80%, respectively, and errors in estimated task duration of < ∼14%, could be achieved across the MMH task examined. Classification performance, however, varied between classification algorithms, input data sets and task types. Overall, combining wearable technology with task classification could be an effective approach for field-based exposure assessment, though field-testing is needed to demonstrate the applicability of this method. PRACTITIONER SUMMARY: Combining wearable technologies with task classification was explored to extract exposure context, specifically task type and duration. Results supported that task classification can facilitate the use of wearable technologies in field-based exposure assessment, specifically by aiding in task identification from within the rather large data sets obtained from these technologies.

Ergonomic evaluation of a wearable assistive device for overhead work.

Overhead work is an important risk factor for upper extremity (UE) musculoskeletal disorders. We examined the potential of a mechanical arm and an exoskeletal vest as a wearable assistive device (WADE) for overhead work. Twelve participants completed 10 minutes of simulated, intermittent overhead work, using each of three payloads (1.1, 3.4 and 8.1 kg) and with/without the WADE. Ratings of perceived discomfort (RPDs) and electromyography (EMG) were obtained for the upper arms, shoulders and low back. Using the WADE, UE RPDs decreased by ∼50% with the heavier payloads, whereas smaller (∼25%) and non-significant increases in low-back RPDs were found and were relatively independent of payload. Changes in RPDs with WADE use were consistent with physical demands indicated by EMG, though EMG-based differences in fatigue were less apparent. Participants generally preferred using the WADE, particularly with heavier payloads. These results supported the potential utility of a WADE as an intervention for overhead work.

Teleoperator-Robot-Human Interaction in Manufacturing: Perspectives from Industry, Robot Manufacturers, and Researchers.

OCCUPATIONAL APPLICATIONSIndustrial robots have become an important aspect in modern industry. In the context of human-robot collaboration, enabling teleoperated robots to work in close proximity to local/onsite humans can provide new opportunities to improve human engagement in a distributed workplace. Interviews with industry stakeholders highlighted several potential benefits of such teleoperator-robot-human collaboration (tRHC), including the application of tRHC to tasks requiring both expertise and manual dexterity (e.g., maintenance and highly skilled tasks in sectors including construction, manufacturing, and healthcare), as well as opportunities to expand job accessibility for individuals with disabilities and older individuals. However, interviewees also indicated potential challenges of tRHC, particularly related to human perception (e.g., perceiving remote environments), safety, and trust. Given these challenges, and the current limited information on the practical value and implementation of tRHC, we propose several future research directions, with a focus on human factors and ergonomics, to help realize the potential benefits of tRHC.

Background The increasing prevalence of robots in industrial environments is attributed in part to advancements in collaborative robot technologies, enabling robots to work in close proximity to humans. Simultaneously, the rise of teleoperation, involving remote robot control, poses unique opportunities and challenges for human-robot collaboration (HRC) in diverse and distributed workspaces.Purpose There is not yet a comprehensive understanding of HRC in teleoperation, specifically focusing on collaborations involving the teleoperator, the robot, and the local or onsite workers in industrial settings, here referred to as teleoperator-robot-human collaboration (tRHC). We aimed to identify opportunities, challenges, and potential applications of tRHC through insights provided from industry stakeholders, thereby supporting effective future industrial implementations.Methods Thirteen stakeholders in robotics, specializing in different domains (i.e., safety, robot manufacturing, aerospace/automotive manufacturing, and supply chains), completed semi-structured interviews that focused on exploring diverse aspects relevant to tRHC. The interviews were then transcribed and thematic analysis was applied to group responses into broader categories, which were further compared across stakeholder industries.Results We identified three main categories and 13 themes from the interviews. These categories include Benefits, Concerns, and Technical Challenges. Interviewees highlighted accessibility, ergonomics, flexibility, safety, time & cost saving, and trust as benefits of tRHC. Concerns raised encompassed safety, standards, trust, and workplace optimization. Technical challenges consisted of critical issues such as communication time delays, the need for high dexterity in robot manipulators, the importance of establishing shared situational awareness among all agents, and the potential of augmented and virtual reality in providing immersive control interfaces.Conclusions Despite important challenges, tRHC could offer unique benefits, facilitating seamless collaboration among the teleoperator, teleoperated robot(s), and onsite workers across physical and geographic boundaries. To realize such benefits and address the challenges, we propose several research directions to further explore and develop tRHC capabilities.

Wearing a back-support exoskeleton alters lower-limb joint kinetics during single-step recovery following a forward loss of balance.

We assessed the effects of a passive, back-support exoskeleton (BSE) on lower-limb joint kinetics during the initiation and swing phases of recovery from a forward loss of balance. Sixteen (8M, 8F) young, healthy participants were released from static forward-leaning postures and attempted to recover their balance with a single-step while wearing a BSE (backXTM) with different levels of support torque and in a control condition. The BSE provided âˆ¼ 15-20 Nm of external hip extension torque on the stepping leg at the end of initiation and beginning of swing phases. Participants were unable to generate sufficient hip flexion torque, power, and work to counteract this external torque, although they sustained hip flexion torque for a more prolonged period, resulting in slightly increased hip contribution to positive leg work (compared to control). However, net positive leg work, and the net contribution of hip joint (human + BSE) to total leg work decreased with BSE use. While all participants had changes in hip joint kinetics, a significant compensatory increase in ankle contribution to positive leg work was observed only among females. Our results suggest that BSE use adversely affects reactive stepping by decreasing the stepping leg kinetic energy for forward propulsion, and that the relative contributions of lower-limb joints to total mechanical work done during balance recovery are altered by BSE use. BSEs may thus need to be implemented with caution for dynamic tasks in occupational settings, as they may impair balance recovery following a forward loss of balance.

Perceived benefits, barriers, perceptions, and readiness to use exoskeletons in the construction industry: Differences by demographic characteristics.

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.