Use of a wearable electromyography armband to detect lift-lower tasks and classify hand loads.

We used an armband with embedded surface electromyography (sEMG) electrodes, together with machine-learning (ML) models, to automatically detect lifting-lowering activities and classify hand loads. Nine healthy participants (4 male and 5 female) completed simulated lifting-lowering tasks in various conditions and with two different hand loads (2.3 and 6.8 kg). We compared three sEMG signal feature sets (i.e., time, frequency, and a combination of both domains) and three ML classifiers (i.e., Random Forest, Support Vector Machine, and Logistic Regression). Both Random Forest and Support Vector Machine models, using either time-domain or time- and frequency-domain features, yielded the best performance in detecting lifts, with respective accuracies of 79.2% (start) and 86.7% (end). Similarly, both ML models yielded the highest accuracy (80.9%) in classifying the two hand loads, regardless of the sEMG features used, emphasizing the potential of sEMG armbands for assessing exposure and risks in occupational lifting tasks.

Exposures to select risk factors can be estimated from a continuous stream of inertial sensor measurements during a variety of lifting-lowering tasks.

Wearable inertial measurement units (IMUs) are used increasingly to estimate biomechanical exposures in lifting-lowering tasks. The objective of the study was to develop and evaluate predictive models for estimating relative hand loads and two other critical biomechanical exposures to gain a comprehensive understanding of work-related musculoskeletal disorders in lifting. We collected 12,480 lifting-lowering phases from 26 subjects (15 men and 11 women) performing manual lifting-lowering tasks with hand loads (0-22.7 kg) at varied workstation heights and handling modes. We implemented a Hierarchical model, that sequentially classified risk factors, including workstation height, handling mode, and relative hand load. Our algorithm detected lifting-lowering phases (>97.8%) with mean onset errors of 0.12 and 0.2 seconds for lifting and lowering phases. It estimated workstation height (>98.5%), handling mode (>87.1%), and relative hand load (mean absolute errors of 5.6-5.8%) across conditions, highlighting the benefits of data-driven models in deriving lifting-lowering occurrences, timing, and critical risk factors from continuous IMU-based kinematics.

The study developed and validated algorithms for detecting and predicting exposure to various risk factors during diverse lifting-lowering tasks. These factors encompass the occurrence, timing, workstation height, handling mode, and relative hand position. This approach facilitates the extraction of contextual information related to lifting tasks conducted in real-world settings through a continuous stream of inertial sensor measurements. Consequently, it can enable automated risk assessment for lifting activities in the field.

Barriers and Benefits of Online Group Exercise Programs for Older Adults.

Engaging in regular physical activity offers a myriad of benefits, including the improvement of mental health, social well-being, and cognitive function. Unfortunately, obstacles, such as transportation constraints, time limitations, and inadequate exercise facilities, hinder the regular participation of older adults in physical activity. Online group physical activity programs present a promising solution to enhance the involvement of older adults; however, several barriers impede their effective utilization. To explore these barriers and benefits, we conducted semi-structured interviews with participants and instructors of a community-based exercise program. Thematic analysis of interviews with 12 physical activity instructors and eight program participants unveiled key hindrances, including limited awareness and accessibility of online programs, challenges in assessing performance during exercise sessions, lack of social component, and technological difficulties. On the positive side, the benefits encompass convenience, wide accessibility, and enhanced social comfort. We also deliberate on future considerations to further bolster participation in these programs.

Freshwater Recovery and Removal of Cesium and Strontium from Radioactive Wastewater by Methane Hydrate Formation.

As human society has advanced, nuclear energy has provided energy security while also offering low carbon emissions and reduced dependence on fossil fuels, whereas nuclear power plants have produced large amounts of radioactive wastewater, which threatens human health and the sustainability of water resources. Here, we demonstrate a hydrate-based desalination (HBD) technology that uses methane as a hydrate former for freshwater recovery and for the removal of radioactive chemicals from wastewater, specifically from Cs- and Sr-containing wastewater. The complete exclusion of radioactive ions from solid methane hydrates was confirmed by a close examination using phase equilibria, spectroscopic investigations, thermal analyses, and theoretical calculations, enabling simultaneous freshwater recovery and the removal of radioactive chemicals from wastewater by the methane hydrate formation process described in this study. More importantly, the proposed HBD technology is applicable to radioactive wastewater containing Cs+ and Sr2+ across a broad concentration range of low percentages to hundreds of parts per million (ppm) and even subppm levels, with high removal efficiency of radioactive chemicals. This study highlights the potential of environmentally sustainable technologies to address the challenges posed by radioactive wastewater generated by nuclear technology, providing new insights for future research and development efforts.

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.

Resilient functioning is associated with altered structural brain network topology in adolescents exposed to childhood adversity.

Childhood adversity is one of the strongest predictors of adolescent mental illness. Therefore, it is critical that the mechanisms that aid resilient functioning in individuals exposed to childhood adversity are better understood. Here, we examined whether resilient functioning was related to structural brain network topology. We quantified resilient functioning at the individual level as psychosocial functioning adjusted for the severity of childhood adversity in a large sample of adolescents (N = 2406, aged 14-24). Next, we examined nodal degree (the number of connections that brain regions have in a network) using brain-wide cortical thickness measures in a representative subset (N = 275) using a sliding window approach. We found that higher resilient functioning was associated with lower nodal degree of multiple regions including the dorsolateral prefrontal cortex, the medial prefrontal cortex, and the posterior superior temporal sulcus (z > 1.645). During adolescence, decreases in nodal degree are thought to reflect a normative developmental process that is part of the extensive remodeling of structural brain network topology. Prior findings in this sample showed that decreased nodal degree was associated with age, as such our findings of negative associations between nodal degree and resilient functioning may therefore potentially resemble a more mature structural network configuration in individuals with higher resilient functioning.

Real-time vibrotactile feedback system for reducing trunk flexion exposure during construction tasks.

Workplaces are increasingly evaluating the use of wearables for ergonomic assessment and providing biofeedback as a real-time postural intervention to improve workers' posture. However, the effectiveness of such intervention systems has yet to be thoroughly investigated in different types of industrial tasks. This study tested the immediate effects of using vibrotactile feedback in simulated construction work tasks including lifting-lowering, shoveling, and tying rebar, to investigate the potential for such an intervention as a way to instruct workers in reducing excessive trunk flexion exposures. Fourteen male participants completed simulated work tasks with three different feedback locations, namely, no feedback, back, and wrist. The results demonstrate that the 95th, 90th, and 50th percentiles of trunk flexion angles are significantly lower for lifting-lowering and shoveling tasks when the feedback system is used. No significant postural changes were observed for the rebar tying task at any combination of percentile and feedback location. The rating of perceived exertion (RPE) for each task did not differ significantly between feedback conditions. Productivity remained the same with the feedback for lifting-lowering and rebar tying, while it was significantly reduced (4.5% of working rate reduction) in shoveling. Participants rated the wrist as the most preferred feedback location. The results of this study suggest that vibrotactile feedback has potential as an effective postural intervention for ergonomic risk factors in selected construction work tasks. Implications for the future design of real-time wearable, sensor-based vibrotactile feedback systems for postural control intervention during dynamic work tasks are discussed.

Statistical discrimination using different machine learning models reveals dissimilar key compounds of soybean leaves in targeted polyphenol-metric metabolomics in terms of traits and cultivation.

Soybean (SB) leaves (SLs) contain diverse flavonoids with health-promoting properties. To investigate the chemical constituents of SB and their correlations across phenotypes, growing periods, and environmental factors, a validated separation method for mass detection was used with targeted metabolomics. Thirty-six polyphenols (1 coumestrol, 5 flavones, 18 flavonols, and 12 isoflavones) were identified in SLs, 31 of which were quantified. Machine learning (ML) modelling was used to differentiate between the variety, bean color, growing period, and cultivation area and identify the key compounds responsible for these differences. The isoflavone and flavonol profiles were influenced by the growing period and cultivation area based on bootstrap forest modelling. The neural model showed the best predictive capacity for SL differences among the various ML models. Discriminant polyphenols can differ depending on the ML method applied; therefore, a cautious approach should be ensured when using statistical ML outputs, including orthogonal partial least squares discriminant analysis.

Obstacle clearance performance in individuals with high body mass index.

The objective of this study was to quantify performance in an obstacle clearance task among individuals with excess body weight or body mass index (BMI). Task performance was operationalized as the maximum obstacle height cleared, four duration measures of successful task completion and compensatory movements used in the process of task completion. Eighteen participants with a BMI exceeding 30 kg/m2 completed a laboratory experiment that required stepping over seven lightweight obstacles. Obstacle heights were sequentially increased from 36 cm in 5 cm increments until participants were unsuccessful or unable to clear the obstacle up to 66 cm. Successful task completions decreased from 100% at an obstacle height of 36 cm to 66.1% at 66 cm. Higher obstacle heights were associated with significantly fewer task completions, longer leading and trailing leg stance and overall task duration, and more frequent use of compensatory movements for successful obstacle clearance. Cox PH regression was used to test the association between probability of obstacle clearance and normalized obstacle height adjusting for BMI, standing balance, and type of compensatory movement used, namely, hover and pivot motions involving the leg, and hands for bracing. The probability of successful task completion significantly decreased with increases in BMI (hazard ratio, HR = 1.14, 95% CI: 1.05-1.25), and increased with use of a leg pivot motion (HR = 0.30, 95% CI: 0.09-0.96) during task completion, after adjusting for standing balance and other types of compensatory movements. Overall, the results demonstrated that obstacle clearance performance is affected by an individual's BMI and the use of compensatory behaviors for regaining stability. The ability to recruit internal and external stabilization techniques could potentially serve as a clinical indicator of reduced fall risk and be the focus of fall prevention interventions. Implications for evaluating stability, fall risk, and identifying modifiable factors for fall prevention in the obese population are discussed.

Effects of vibrotactile feedback on yoga practice.

Participating in physical exercise using remote platforms is challenging for people with vision impairment due to their lack of vision. Thus, there is a need to provide nonvisual feedback to this population to improve the performance and safety of remote exercise. In this study, the effects of different nonvisual types of feedback (verbal, vibrotactile, and combined verbal and vibrotactile) for movement correction were tested with 22 participants with normal vision to investigate the feasibility of the feedback system and pilot tested with four participants with impaired vision. The study with normal-vision participants found that nonvisual feedback successfully corrected an additional 11.2% of movements compared to the no-feedback condition. Vibrotactile feedback was the most time-efficient among other types of feedback in correcting poses. Participants with normal vision rated multimodal feedback as the most strongly preferred modality. In a pilot test, participants with impaired vision also showed a similar trend. Overall, the study found providing vibrotactile (or multimodal) feedback during physical exercise to be an effective way of improving exercise performance. Implications for future training platform development with vibrotactile or multimodal feedback for people with impaired vision are discussed.

Vibrotactile feedback in virtual motor learning: A systematic review.

Vibrotactile feedback can be effectively applied to motor (physical) learning in virtual environments, as it can provide task-intrinsic and augmented feedback to users, assisting them in enhancing their motor performance. This review investigates current uses of vibrotactile feedback systems in motor learning applications built upon virtual environments by systematically synthesizing 24 peer-reviewed studies. We aim to understand: (1) the current state of the science of using real-time vibrotactile feedback in virtual environments for aiding the acquisition (or improvement) of motor skills, (2) the effectiveness of using vibrotactile feedback in such applications, and (3) research gaps and opportunities in current technology. We used the Sensing-Analysis-Assessment-Intervention framework to assess the scientific literature in our review. The review identifies several research gaps in current studies, as well as potential design considerations that can improve vibrotactile feedback systems in virtual motor learning applications, including the selection and placement of feedback devices and feedback designs.

Barley Sprout Water Extract and Saponarin Mitigate Triacylglycerol Accumulation in 3T3-L1 Adipocytes.

The mechanisms of action responsible for the reported hypolipidemic activity of barley sprouts have yet to be elucidated. The objective of this study was to compare the content of saponarin (the sole flavonoid present in barley sprout leaves), hypolipidemic activity between barley sprout water extract (BSW) and barley sprout ethanol extract (BSE), and the associated relevance to hypolipidemic activity in 3T3-L1 preadipocytes. BSW elicited superior antiadipogenic effects when compared with BSE in MDI mixture [IBMX 0.5 mM + dexamethasone 1 µM + insulin 1 µg/mL]-treated 3T3-L1 preadipocytes. BSW attenuated MDI-mediated triacylglycerol (TAG) accumulation by inhibiting fatty acid synthase (FAS). FAS protein expression was markedly and dose dependently attenuated by BSW, with higher doses suppressing expression to a level equivalent to the controls. BSW also significantly attenuated MDI-mediated increases in the expression of genes involved in TAG synthesis as well as FAS in 3T3-L1 preadipocytes. High-performance liquid chromatography analysis indicated that BSW contains more than four times more saponarin than BSE. Further investigation of saponarin-mediated hypotriacylglycerolemic activity and related gene expression revealed that saponarin significantly inhibited TAG accumulation, which was attributed to reductions in TAG synthesis-related gene expression. Taken together, these findings provide a basis for further development of barley sprout extract for functional health food purposes.

Integrative analysis of the plasma proteome and polygenic risk of cardiometabolic diseases.

Cardiometabolic diseases are frequently polygenic in architecture, comprising a large number of risk alleles with small effects spread across the genome1-3. Polygenic scores (PGS) aggregate these into a metric representing an individual's genetic predisposition to disease. PGS have shown promise for early risk prediction4-7 and there is an open question as to whether PGS can also be used to understand disease biology8. Here, we demonstrate that cardiometabolic disease PGS can be used to elucidate the proteins underlying disease pathogenesis. In 3,087 healthy individuals, we found that PGS for coronary artery disease, type 2 diabetes, chronic kidney disease and ischaemic stroke are associated with the levels of 49 plasma proteins. Associations were polygenic in architecture, largely independent of cis and trans protein quantitative trait loci and present for proteins without quantitative trait loci. Over a follow-up of 7.7 years, 28 of these proteins associated with future myocardial infarction or type 2 diabetes events, 16 of which were mediators between polygenic risk and incident disease. Twelve of these were druggable targets with therapeutic potential. Our results demonstrate the potential for PGS to uncover causal disease biology and targets with therapeutic potential, including those that may be missed by approaches utilizing information at a single locus.

Dysconnectivity of a brain functional network was associated with blood inflammatory markers in depression.

OBJECTIVE: There is increasing evidence for a subgroup of major depressive disorder (MDD) associated with heightened peripheral blood inflammatory markers. In this study, we aimed to understand the mechanistic brain-immune axis in inflammation-linked depression by investigating associations between functional connectivity (FC) of brain networks and peripheral blood immune markers in depression. METHODS: Resting-state functional magnetic resonance imaging (fMRI) and peripheral blood inflammatory markers (C-reactive protein; CRP, interleukin-6; IL-6 and immune cells) were collected on N = 46 healthy controls (HC; CRP ≤ 3 mg/L) and N = 83 cases of depression, stratified further into low CRP cases (loCRP cases; ≤ 3 mg/L; N = 50) and high CRP cases (hiCRP cases; > 3 mg/L; N = 33). In a two-part analysis, network-based statistics (NBS) was firstly used to ascertain whole-brain FC differences in HC vs hiCRP cases. Secondly, we investigated the association between this network of interconnected brain regions and continuous measures of peripheral CRP (N = 83), IL-6 (N = 72), neutrophils and CD4+ T-cells (N = 36) in depression cases only. RESULTS: Case-control NBS testing revealed a single network of abnormally attenuated FC in the high CRP depression cases compared to healthy controls. Connections within this network were mainly between brain regions located in the left insula/frontal operculum and posterior cingulate cortex, which were assigned to ventral attention and default mode canonical fMRI networks respectively. Within-group analysis across all depression cases, secondarily demonstrated that FC within the identified network significantly negatively scaled with CRP, IL-6 and neutrophils. CONCLUSIONS: The findings suggest that inflammation is associated with disruption of functional connectivity within a brain network deemed critical for interoceptive signalling, e.g. accurate communication of peripheral bodily signals such as immune states to the brain, with implications for the pathogenesis of inflammation-linked depression.

Functional Data Representation of Inertial Sensor-based Torso-Thigh, Knee, and Ankle Movements during Lifting.

This study examined the goodness-of-fit of using a sigmoid function to characterize time-series angular displacement trajectories during two-handed anterior lifting. Twenty-six participants performed two-handed anterior lifting with a low (4.5 kg) vs. high (22.7 kg) load at floor vs. knee lifting height. A sigmoid function with three parameters was fit to the torso-thigh included angle, knee flexion-extension (F-E), and ankle F-E angles in the sagittal plane obtained from body-worn inertial sensors. Mean ± SD RMSE between measured vs. fitted trajectories were 3.6 ± 2.9°, 3.9 ± 4.2°, and 2.7 ± 2.8° for the torso-thigh included angle, knee F-E, and ankle F-E angles, respectively. Findings suggest that the sigmoid function adequately describes the trajectory shape of two-handed lifting kinematics. Functional representations facilitate data aggregation and feature extraction in large time-series datasets encountered in inertial-based motion analysis and machine learning applications.

Wheeled Mobility Use on Accessible Fixed-Route Transit: A Field Study in Environmental Docility.

Multiple field studies provide qualitative accounts of usability barriers experienced by users of wheeled mobility devices on public transit. This study aimed to examine these usability barriers from the theoretical perspective of Environmental Docility by quantifying the relationship between functional capabilities of wheeled mobility device users and ingress-egress performance on accessible fixed-route transit vehicles in an urban setting. Twenty-eight wheeled mobility users each completed three trips on a predetermined route through the local public transit system. Ingress and egress times, user-reported usability ratings and open-ended comments were analyzed. Regression analyses indicated significant interactions between age and minimum parallel-park length on ingress and egress times. Specifically, lower functional capability reflected in older age and less maneuvering ability predicted decreased performance (longer ingress-egress times), indicating less adaptability to environmental demands and agreement with the Environmental Docility Hypothesis. Usability ratings and comments revealed difficulty with negotiating access ramps and turning maneuvers in the vehicle interior and in proximity to other passengers. Despite compliance with accessibility standards, current design of transit vehicles present substantial usability barriers for wheeled mobility users. Environmental Docility provides a theoretical basis to identifying modifiable factors related to person and environment for improving usability of public transit for people aging and/or with mobility impairments.

Recovery of N2O: Energy-Efficient and Structure-Driven Clathrate-Based Greenhouse Gas Separation.

N2O has 300 times more global warming potential than CO2 and is also one of the main stratospheric ozone-depleting substances emitted by human activities such as agriculture, industry, and the combustion of fossil fuels and solid waste. We present here an energy-efficient clathrate-based greenhouse gas-separation (CBGS) technology that can operate at room temperature for selectively recovering N2O from gas mixtures. Clathrate formation between α-form/ß-form hydroquinone (α-HQ/ß-HQ) and gas mixtures reveals guest-specific and structure-driven selectivity, revealing the preferential capture of N2O in ß-HQ and the molecular sieving characteristics of α-HQ. With a maximum gas storage capacity and cage occupancy of 54.1 cm3 g-1 and 0.86, respectively, HQ clathrate compounds including N2O are stable at room temperature and atmospheric pressure and thus can be easily synthesized, treated, and recycled via commercial CBGS processes. High selectivity for N2O recovery was observed during ß-HQ clathrate formation from N2O/N2 gas mixtures with N2O concentrations exceeding 20%, whereas α-HQ traps only N2 molecules from gas mixtures. Full characterization using X-ray diffraction, scanning electron microscopy, Raman spectroscopy, solid-state nuclear magnetic resonance, and compositional analysis and the formation kinetics of HQ clathrates was conducted to verify the peculiar selectivity behavior and to design the conceptual CBGS process. These results provide a new playground on which to tailor host-guest materials and develop commercial processes for the recovery and/or sequestration of greenhouse gases.

Measuring Effects of Two-Handed Side and Anterior Load Carriage on Thoracic-Pelvic Coordination Using Wearable Gyroscopes.

Manual carrying of heavy weight poses a major risk for work-related low back injury. Body-worn inertial sensors present opportunities to study the effects of ambulatory work tasks such as load carriage in more realistic conditions. An immediate effect of load carriage is reflected in altered gait kinematics. To determine the effects of load carriage mode and magnitude on gait parameters using body-worn angular rate gyroscopes, two laboratory experiments (n = 9 and n = 10, respectively) were conducted. Participants performed walk trials at self-selected speeds while carrying hand loads in two modes (two-handed side vs. anterior) at four load levels (empty-handed, 4.5 kg, 9.1 kg, and 13.6 kg). Six measures of postural sway and three measures of thoracic-pelvic coordination were calculated from data recorded by four body-worn gyroscopes for 1517 gait cycles. Results demonstrated that, after adjusting for relative walking speed, thoracic-pelvic sway, and movement coordination particularly in the coronal and transverse planes, characterized by gyroscope-based kinematic gait parameters, are systematically altered by the mode of load carriage and load magnitude. Similar trends were obtained for an anthropometrically homogenous (Expt-1) and diverse (Expt-2) sample after adjusting for individual differences in relative walking speed. Measures of thoracic-pelvic coordination and sway showed trends of significant practical relevance and may provide sufficient information to typify alterations in gait across two-handed side vs. anterior load carriage of different load magnitudes. This study contributes to understanding the effects of manual load carriage on thoracic-pelvic movement and the potential application of body-worn gyroscopes to measuring these gait adaptations in naturalistic work settings.

A Narrative Review on Contemporary and Emerging Uses of Inertial Sensing in Occupational Ergonomics.

Accurate, reliable, and cost-effective quantification of real-time biomechanical exposures in occupational settings remains an enduring pursuit in ergonomics. Miniaturized, wireless, body-worn inertial sensors offer opportunities to directly measure vast and personalized kinematics data in both laboratory and applied settings. This review investigated the contemporary and emerging uses of wearable inertial sensing technology in occupational ergonomics research related to biomechanical exposure assessment in physical work. A review and narrative synthesis of 78 peer-reviewed studies was conducted. A conceptual framework was used for scoping and synthesizing the reviewed scientific literature. Review findings help to contextualize contributions of this emerging technology to the broader goals of reducing work-relevant musculoskeletal trauma disorders. The review made evident that despite the growing interest in wearable inertial sensing technologies for ergonomics research, its use in applied settings still lags. The review also identified differences in sensor attachment locations and methods and measures for calibration and validation, and inconsistent criteria for reporting and assessing biomechanical exposures even across studies with similar objectives. Emerging applications include combining inertial sensing with predictive modeling for obtaining cumulative exposure data, and providing real-time feedback about biomechanical work demands. The manuscript concludes with research directions for enabling inertial sensing technologies as a tool for online biomechanical exposure assessment and feedback, which has particular appeal in non-repetitive work settings.