Handling Tasks Research Articles

Retraction Notice to: A pilot study to assess a risk of a high-risk group of low back pain membership in workers who perform the manual material handling tasks (Ann Occup Environ Med 2021;33:e34).

[This retracts the article e34 in vol. 33, PMID: 35024151.].

Application Framework of Collaborative Robot to Mold Assembly Processes

This study introduces an application framework for implementing collaborative robots to assist and collaborate with human workers in the mold assembly operation. In current practices, the molds are assembled manually, hence, possibility of ergonomics risk on the human occurs because of the heavyweight handling and repetitive force exertion tasks during the manual mold assembly. However, the requirement of human versatility to adapt to different mold types and frequent demand changes limits the shifting of the mold assembly from manual to full automation. Thus, this study proposes a human-robot collaboration (HRC) system to improve ergonomic problem on the human while maintaining the human ability in the mold assembly. The proposed application framework includes: (1) task assignment model assigns subtasks to agents available; (2) status recognition recognizes state of subtasks to update executing status; (3) reassignment of subtasks to cope with changes during the human-robot collaborative assembly operation. According to the agents’ capabilities, which determined based on task characteristics, the proposed framework implements collaborative robot to improve assembly time and ergonomic risk. By considering the potential of HRC systems for wider range of mold types and dimensions, the framework is then expanded to implement multi robots in the HRC mold assembly operation.

Sentiment Analysis on the Centralized Isolation Policy for Covid-19 Response in Bali Province

Coronavirus disease (Covid-19) is an infectious virus caused by SARS-CoV-2 virus, which has caused a global pandemic. The global pandemic is declared by the World Health Organization (WHO) on March 11th, 2020. Until late of April 2022, Covid-19 has caused the death of the total of more than 6 million people, and in Indonesia alone it has caused more than 150 thousand of death. The pandemic does not only impact health area, but also economy, politics, cultures, etc. In order to end the pandemic, WHO has sets out standard policies to be implemented, including by Indonesian government. Besides, each local goverment in Indonesia has also their own policies and regulations, including the government of Bali Province, for example the Community Activities Restrictions Enforcement or CARE (Indonesian: Pemberlakuan Pembatasan Kegiatan Masyarakat, commonly referred to as the PPKM), improvement in health care facilities and services, and also isolation policy for the people whom are infected by SARS-CoV-2 virus. To prevent the increase in death, Bali Province's COVID-19 Handling Task Force along with the district and city governments have prepared a centralized isolation policy and facilities for those whom are found to be Covid-19 positive without having any symptoms and for those with mild symtomps. This research has been conducted in order to get the public sentiment about this centralized isolation policy in Bali Province by using Tweet data from Twitter social media, based on Naive Bayes classification. From the experiments, the results of data Tweet classifications have accuracy more than 90%, which have shown that the public opinion is neutral. The results also mean that there is no contradition found in the application of centralized isolation policy in the province of Bali-Indonesia.

Risk Assessment of Musculoskeletal Disorders in Patient Handling Tasks Using MAPO and 3DSSPP Methods

Risk Assessment of Musculoskeletal Disorders in Patient Handling Tasks Using MAPO and 3DSSPP Methods

The Application of Health Protocols in the New Normal Era in Aqua Version Advertising with Aqua Goodness, We Continue to Move (Charles Sanders Peirce Model Semiotic Analysis)

This study aims to analyze the meaning of the message in advertising Aqua version with the goodness of Aqua, we continue to step. This study uses descriptive qualitative research using Charles Sanders Pierce's semiotic analysis model which will be useful in explaining icons, indexes, and symbols to find the application of health protocols in the new Normal Era in advertisements spread in the mass media. The results of this study state the implementation of health protocols marked in a scene, property, and certain color characteristics that occurred at the interval of the covid-19 pandemic. The findings refer to an appeal that has been submitted by the covid-19 handling task force in the form of rules that must be applied when outside the home in the form of 3M (washing hands, using masks and maintaining distance).

Evaluasi Kegiatan Sub Bagian Data dan Informasi Pada Gugus Tugas COVID 19 di Kabupaten Tulungagung

Background: Coronavirus Disease 19, commonly dubbed as COVID-19, has been widely spread across the globe since March 2020, and WHO has declared it a Pandemic. In Indonesia, the disease began to spread in June 2020. The spreading rate was so fast that it reached every part of the country, including the Tulungagung district in East Java. The Government of Tulungaggung has tried to curb the rapid spread of COVID-19 cases by establishing the “COVID-19 Handling Task Force Team”. The author was assigned in Data and Information in the task force, and of course, the performance is far from perfect. Therefore, an evaluation to measure the success rate of the programs conducted by the Sub Department of Data and Information of the COVID-19 Handling Task Force Team in Tulungagung District was made.Objectives: The purpose of this study was to evaluate the activities of the data and information sub-section on the Covid-19 task force in Tulungagung Regency.Methods: The works performed by volunteers in the COVID-19 Handling Task Force Team of Tulungagung District were observational participative, where the students are actively involved in controlling the cases. The students were given the task of the data and information. The primary responsibility of the data and information department is the evaluation of monitoring, information systems, and press release activities.Results: This final assignment/mini-thesis covers the implementation of activities at the Sub Department of Data and Information contains ten measured activities. The measurement was made by comparing the actual performance with the guideline in place.Conclusions: In conclusion, the analysis of activities at the Sub Department of Data and Information was made to 10 activity indicators. The result is that each indicator are consistent and aligned with the prevailing guidelines such as Ministry of Health Regulation number 45 of 2014 concerning Health Surveillance Implementation, COVID-19 Prevention and Control Guideline of 2020, and Behavior Change Communication (KPP) strategy in COVID-19 preventions.

A novel approach to quantify the assistive torque profiles generated by passive back-support exoskeletons

Industrial exoskeletons are a promising ergonomic intervention to reduce the risk of work-related musculoskeletal disorders by providing external physical support to workers. Passive exoskeletons, having no power supplies, are of particular interest given their predominance in the commercial market. Understanding the mechanical behavior of the torque generation mechanisms embedded in passive exoskeletons is, however, essential to determine the efficacy of these devices in reducing physical loads (e.g., in manual material handling tasks). We introduce a novel approach using a computerized dynamometer to quantify the assistive torque profiles of two passive back-support exoskeletons (BSEs) at different support settings and in both static and dynamic conditions. The feasibility of this approach was examined using both human subjects and a mannequin. Clear differences in assistive torque magnitudes were evident between the two BSEs, and both devices generated more assistive torques during trunk/hip flexion than extension. Assistive torques obtained from human subjects were often within similar ranges as those from the mannequin, though values were more comparable over a narrow range of flexion/extension angles due to practical limitations with the dynamometer and human subjects. Characterizing exoskeleton assistive torque profiles can help in better understanding how to select a torque profile for given task requirements and user anthropometry, and aid in predicting the potential impacts of exoskeleton use by incorporating measured torque profiles in a musculoskeletal modeling system. Future work is recommended to assess this approach for other occupational exoskeletons.

Technological robot-Machine tool collaboration for agile production.

The flexibility and efficiency in parts production can be significantly increased through the technological cooperation of industrial robots and machine tools. The paper presents an approach in which a robot, in addition to the classic handling tasks, enhance machine tools by additional manufacturing technologies and thus beneficially supports workpiece machining. This can take place in various configurations, starting with pre- and final machining by the robot outside the machine, through sequential cooperative machining of the workpiece clamped in the machine, to parallel, synchronized machining of a workpiece in the machine. The approach results in a novel type of collaborative manufacturing equipment for matrix production that will improve the versatility, efficiency and profitability in production.

A Mixed-Reality Tele-Operation Method for High-Level Control of a Legged-Manipulator Robot.

In recent years, legged (quadruped) robots have been subject of technological study and continuous development. These robots have a leading role in applications that require high mobility skills in complex terrain, as is the case of Search and Rescue (SAR). These robots stand out for their ability to adapt to different terrains, overcome obstacles and move within unstructured environments. Most of the implementations recently developed are focused on data collecting with sensors, such as lidar or cameras. This work seeks to integrate a 6DoF arm manipulator to the quadruped robot ARTU-R (A1 Rescue Tasks UPM Robot) by Unitree to perform manipulation tasks in SAR environments. The main contribution of this work is focused on the High-level control of the robotic set (Legged + Manipulator) using Mixed-Reality (MR). An optimization phase of the robotic set workspace has been previously developed in Matlab for the implementation, as well as a simulation phase in Gazebo to verify the dynamic functionality of the set in reconstructed environments. The first and second generation of Hololens glasses have been used and contrasted with a conventional interface to develop the MR control part of the proposed method. Manipulations of first aid equipment have been carried out to evaluate the proposed method. The main results show that the proposed method allows better control of the robotic set than conventional interfaces, improving the operator efficiency in performing robotic handling tasks and increasing confidence in decision-making. On the other hand, Hololens 2 showed a better user experience concerning graphics and latency time.

Modeling of the maximum endurance time of coal miners muscle fatigue for one-handed carrying tasks

To prevent safety production accidents caused by muscle fatigue among coal miners, a modified model of maximum tolerance time (TME) was established to predict the TME for one-handed handling tasks. Thirty-one participants including different types of coal miners volunteered to participate in one-handed handling of oil drums for loading, unloading and horizontal walking operations. The maximum voluntary contraction strength (fMVC), subjective fatigue rating (Erp) and TME of coal miners' backs and legs were measured before and after handling operations, as well as during the three task phases. An Erp one-dimensional linear regression prediction model was established under the effect of individual factors. A simplified TME prediction model was developed using power and exponential functions in the relative role of fMVC. A TME-modified model was further constructed considering the effects of weight and heart rate of coal miners. It was found that when fMVC ≤ 0.12, the simplified power model (median function model) provided higher estimates than the exponential model, and the predictions were closer to the true values. With fMVC < 0.2 or lower, incorporating indicators of instantaneous heart rate and body weight of coal miners, the TME modified model was used to accurately assess the TME of coal miners. It is suggested that workers engaged in manual handling operations on a daily basis should not carry a maximum weight of more than 22 kg on the back or legs to avoid musculoskeletal disorders that could lead to safety accidents.

Investigating gripping force during lifting tasks using a pressure sensing glove system

Lifting tasks remain one of the leading causes of musculoskeletal disorders (MSDs), primarily in the low back region. Lifting analysis tools are, therefore, designed for assessing the risk of low back pain. Shoulder musculoskeletal problems have emerged as common MSDs associated with manual handling tasks. It is hypothesized that gripping force is related to lifting conditions and may be used as a supplementary risk metric for MSDs in the shoulder and low back regions, because it measures additional hand exertions for coupling the lifted object during lifting. We assessed the capability tactile gloves for measuring the gripping force during lifting as a means for assessing different task conditions (lifting weight, lifting height, lifting direction, body rotation, and handle). Thirty participants wore the tactile gloves and performed simulated lifting tasks. Regression models were used to analyze the effects of the task variables on estimating the measured gripping force. Results demonstrated that 58% and 70% of the lifting weight variance were explained by the measured gripping force without and with considering the individual difference, respectively. In addition to the lifting risk measures commonly used by practitioners, this study suggests a potential for using gripping force as a supplementary or additional risk metric for MSDs.

The effect of a passive exoskeleton on trunk co-activation during liftings at different risk levels

The new Industry 4.0 scenarios offer opportunity for both the prevention of biomechanical overload risks and the implementation of extra return-to-work initiatives for people with disabilities. Wearable assistive devices (e.g., an industrial exoskeleton) can help to lower the risk of acquiring work-related musculoskeletal diseases (WMSDs) caused by manual material handling (MMH) tasks, among other things [1]. The most prevalent and expensive musculoskeletal diseases are WLBDs, which are primarily caused by manual lifting jobs [1]. This study aims to investigate the influence of TRUExo, a passive exoskeleton for the trunk composed of a textile and a mechanical component for energy restitution, on trunk coactivation in lifting activities at various risk levels (more details cannot currently be described because the device is under patent). Twelve healthy volunteers (age: 36.33±7.66 years; BMI: 22.34±2.21 kg/m2; 6 females and 6 males) completed the lifting tasks designed using the revised NIOSH lifting equation, [2], at progressively increasing lifting indexes (from 1 to 3). The tasks were performed with and without the TRUExo exoskeleton, and the activity of the erector spinae longissimus (RESL) and rectus abdominis superior (RAS) was recorded bilaterally using a 16-channel Wi-Fi transmission surface electromyograph (Mini Wave Infinity, Cometa, Milan, Italy) system at a sampling rate of 2000 Hz. Before beginning the lifting tasks, participants completed three repetitions of a specific exercise to record the isometric maximal voluntary contractions (iMVCs) for the muscles under investigation. Then, after sEMG processing and normalization respect to iMVC values, we computed the time-varying multi-muscle co-activation function (TMCf), [3]. Our findings reveal that the mean TMCf of all patients is lower with the passive exoskeleton than without it at each LI. The mean of the TMCf reduces significantly with LI when wearing the exoskeleton, according to two-way repeated-measures ANOVA and post-hoc analysis (Fig. 1B). The results reveal that the TMCf increases in relation to the risk levels both with and without the exoskeleton, but the TMCf is lower at each LI when the subject wears the exoskeleton ( Fig. 1 , B). These findings could lend credence to the notion that a passive exoskeleton worn during a working activity could alleviate biomechanical load and, as a result, lower the likelihood of WMSD occurrence. Furthermore, our findings highlight the TMCf's sensitivity to differentiate different risk levels even when wearing an exoskeleton, implying that it might be used as an operational tool to assess biomechanical risk in situations where traditional approaches (e.g., NIOSH's method) cannot be used.

An automatic procedure to classify biomechanical risk classes associated to lifting activities according to the Revised NIOSH Lifting Equation

In the field of occupational medicine, physical ergonomics studies, aimed at preventing work-related illnesses, have gained importance in recent years since both quantitative/semi-quantitative observational studies and instrumental methods have reported promising results. Among the instrumental methods, wearable devices capable to acquire signals such as acceleration and angular velocity, electromyography (EMG) [1] have potentially proved useful to help assessing – both automatically and more accurately – the work-related risk, which can lead to biomechanical overloading and the development of work-related musculoskeletal disorders (WRMD), especially in the case of workers involved in activities such as material handling and lifting tasks. In this context, a powerful method to monitor workers biomechanical risk is a National Institute for Occupational Safety and Health (NIOSH) quantitative formula (RNLE), which considers factors such as intensity, duration and frequency (together with other geometrical characteristics) of a lifting task [2]. The study was carried out enrolling 13 healthy subjects with no signs of musculoskeletal disorder wearing an inertial sensor (Opal, APDM Inc.) on the chest. Each subject performed a session based on two trials. Each trial consisted in 20 consecutive lifting of a plastic container. The first trial was performed in a condition with LI < 1 which corresponds to the No-risk class while the second trial was performed in a condition with LI > 1 which correspond to the Risk class. LI of 0.5 and 1.3 were derived from the RNLE by variously combining height, frequency and weight of lifting tasks. The collected acceleration and angular velocity signals along the three axes were filtered and then segmented to extract the region of interest (ROI) corresponding to the lifting by means of the Savitzky-Golay filter. For each ROI several features in the time and frequency domains were extracted and feed to machine learning algorithms to evaluate the discriminative power of these features to classify risk classes according to the RNLE. Table 1 shows the results of the machine learning (ML) analysis by means of some evaluation metrics using different ML algorithms. The ML analysis was carried out on a dataset composed of 520 instances (13 subject x 40 lifting), 114 features (19 features x 6 axes) and two classes (No-risk, risk). The goal of this research was to develop an automatic procedure - based on algorithms for digital signal processing and ML algorithms fed with appropriate time and frequency domains features extracted from sternum inertial data – able to classify lifting biomechanical risk classes according to the RNLE. The results of the ML analysis, especially Random Forest, showed high scores in evaluation metrics. The presented methodology could represent a valid integration to the conventional protocols used in ergonomics to evaluate the biomechanical risk more quickly and easily. These results are of direct practical relevance for occupational ergonomics, as they present the opportunity for automatic, economic and non-invasive (by placing an IMU on the sternum) detection of the risk associated with lifting. Future investigation on enriched dataset that will involve several scenarios and risk classes could confirm the potentiality of the proposed methodology.

A Review of Exoskeletons Considering Nurses.

Daily tasks of nurses include manual handling to assist patients. Repetitive manual handling leads to high risk of injuries due to the loads on nurses’ bodies. Nurses, in hospitals and care homes, can benefit from the advances in exoskeleton technology assisting their manual handling tasks. There are already exoskeletons both in the market and in the research area made to assist physical workers to handle heavy loads. However, those exoskeletons are mostly designed for men, as most physical workers are men, whereas most nurses are women. In the case of nurses, they handle patients, a more delicate task than handling objects, and any such device used by nurses should easily be disinfected. In this study, the needs of nurses are examined, and a review of the state-of-the-art exoskeletons is conducted from the perspective of to what extent the existing technologies address the needs of nurses. Possible solutions and technologies and particularly the needs that have not been addressed by the existing technologies are discussed.

Partisipasi Masyarakat dalam Program Kampung Wani Jogo Suroboyo di Bratang Gede Kota Surabaya

Covid-19 is a virus that has spread throughout the world, including Indonesia. Mayor Regulation No. 67 of 2020 regarding the handling of Covid-19, hereby the Surabaya City government wants to improve civil society by empowering the RT/RW level community through the formation of a Covid-19 handling task force, by establishing the KampungWani Jogo Suroboyo. The purpose of this research is to determine Community Participation in the Bratang Gede area, Ngagel Rejo village, in the implementation of the Program Kampung Wani Jogo Suroboyo and the supporting and inhibiting factors for the implementation of the Program KampungWani Jogo Suroboyo. The benefit of this research is to broaden the reader's knowledge regarding community participation in dealing with the Covid-19 pandemic. The method used in this research is a qualitative method with a case study approach using the theory of Community Participation, according to Huraerah, 2008. The results of this research indicate that Community Participation in the Covid-19 Pandemic Period in the Program Kampung Wani Jogo Suroboyo has been running quite well in accordance with existing regulations, namely Mayor Regulation No. 67 of 2020. This program is also supported by sufficient human resources and adequate infrastructure. However, the obstacles in using the Lawancovid application do not work well and residents obtain funding independently using village cash.

Biomechanical analysis of lifting on stable versus unstable surfaces—a laboratory-based proof-of-concept study

BackgroundMany workers performing manual handling tasks suffer from musculoskeletal disorders (MSD). Previous research has identified several loading aspects associated with manual handling, but it is still unknown if lifting on an unstable surface is associated with increased biomechanical loading of different body parts.AimThis proof-of-concept study aims to study what kinematic and kinetic movement parameters, such as movement time, joint angles, torque, and muscle activity are feasible and of importance when studying the effect of lifting on surfaces with varying degrees of stability in an experimental set-up.MethodsMeasurements were taken during three different surface conditions: stable, slightly unstable, and unstable. The participants were instructed to lift a box from the floor and place it on a table in front of them. The weight of the box varied from 0.5 to 15.5 kg. By using a motion capture system (VICON) with 28 reflective markers placed on the participants and one on the box, one Kistler force plate for measuring force levels and center of pressure movements (CoP), and four electromyographic transmitters (EMG), we analyzed the downward and upward phases of the lifting movement, using the Friedman’s test for repeated measures.ResultsStatistically significant results with less joint movements in the lower and upper back were seen with increased instability during both the downward and upward phases. The decrease in trunk movements with increased instability resulted in a somewhat more flexed knee position during the movement, a lower torque in the lower back, and a decrease in CoP movements, but no differences in movement time or muscle activity in back and knee muscles.ConclusionLifting while standing on unstable surfaces resulted in an alteration of both kinematics and kinetics parameters; however, further studies regarding whether this is an additional risk factor for developing lower back pain are needed. Muscle activity levels were not altered due to instability and due to the complexity of the measurement, and we suggest not including EMG measures in future experiments of this type.

Assessment of Surgeon Performance of Advanced Open Surgical Skills Using a Microskills-Based Novel Curriculum

The increase in minimally invasive surgical procedures has eroded exposure of general surgery residents to open operations. High-fidelity simulation, together with deliberate instruction, is needed for advanced open surgical skill (AOSS) development. To collect validity evidence for AOSS tools to support a shared model for instruction. This prospective cohort study included postresidency surgeons (PRSs) and second-year general surgery residents (R2s) at a single academic medical center who completed simulated tasks taught within the AOSS curriculum between June 1 and October 31, 2021. The AOSS curriculum includes 6 fine-suture and needle handling tasks, including deep suture tying (with and without needles) and continuous suturing using the pitch-and-catch and push-push-pull techniques (both superficial and deep). Teaching and assessment are based on specific microskills using a 3-dimensional printed iliac fossa model. The PRS group was timed and scored (5-point Likert scale) on 10 repetitions of each task. Six months after receiving instruction on the AOSS tasks, the R2 group was similarly timed and scored. The PRS group included 14 surgeons (11 male [79%]; 8 [57%] attending surgeons) who completed the simulation; the R2 group, 9 surgeons (5 female [55%]) who completed the simulation. Score and time variability were greater for the R2s compared with the PRSs for all tasks. The R2s scored lower and took longer on (1) deep pitch-and-catch suturing (69% of maximum points for a mean [SD] of 142.0 [31.7] seconds vs 77% for a mean [SD] of 95.9 [29.4] seconds) and deep push-push-pull suturing (63% of maximum points for a mean [SD] of 284.0 [72.9] seconds vs 85% for a mean [SD] of 141.4 [29.1] seconds) relative to the corresponding superficial tasks; (2) suture tying with a needle vs suture tying without a needle (74% of maximum points for a mean [SD] of 64.6 [19.8] seconds vs 90% for a mean [SD] of 54.4 [15.6] seconds); and (3) the deep push-push-pull vs pitch-and-catch techniques (63% of maximum points for a mean [SD] of 284.0 [72.9] seconds vs 69% of maximum points for a mean [SD] of 142.0 [31.7] seconds). For the PRS group, time was negatively associated with score for the 3 hardest tasks: superficial push-push-pull (ρ = 0.60; P = .02), deep pitch-and-catch (ρ = 0.73; P = .003), and deep push-push-pull (ρ = 0.81; P < .001). For the R2 group, time was negatively associated with score for the 2 easiest tasks: suture tying without a needle (ρ = 0.78; P = .01) and superficial pitch-and-catch (ρ = 0.79; P = .01). The findings of this cohort study offer validity evidence for a novel AOSS curriculum; reveal differential difficulty of tasks that can be attributed to specific microskills; and suggest that position on the surgical learning curve may dictate the association between competency and speed. Together these findings suggest specific, actionable opportunities to guide instruction of AOSS, including which microskills to focus on, when individual rehearsal vs guided instruction is more appropriate, and when to focus on speed.

Augmented reality (AR) posture training for manual material handling: iterative design, evaluation, and recommendation for AR interface

Manual material handling (MMH) tasks can pose risks of musculoskeletal disorders for workers, which makes posture training programs essential. The ultimate goal of this research was to design and evaluate an augmented reality (AR) based training platform, namely the virtual instructor application (VIA). Specifically, the usability problems revealed from the preliminary version (VIA-1) were addressed and enhanced features were implemented in the current version (VIA-2). The usability of VIA-2 was assessed by ten individuals with experience of MMH. Participants explored VIA-2 while performing a series of predefined tasks. A usability questionnaire was administered, and a brief interview was conducted. Results showed that VIA-2 had increased usability compared to VIA-1. While some visual content display issues occurred, a future minor refurnish can address these problems. Finally, the iterative design and evaluation scheme can be applied to the future design of AR-based training programs and evaluation protocols.

AN ORDINAL LOGISTIC REGRESSION MODEL FOR ANALYZING RISK ZONE STATUS OF COVID-19 SPREAD

Coronavirus disease 2019 (COVID-19) is a new type of virus that has been found to have infected human since it first appeared in Wuhan, China, in December 2019. This study aims to determine the factors that influence the risk zone status of COVID-19 spread in Indonesia using ordinal logistic regression. The ordinal logistic regression model in this study uses proportional odds model because the researcher assumes probability of predictor variable coefficients is the same for each respond category. The response variable is secondary data from the COVID-19 Handling Task Force, namely the status of the risk zone for the spread of COVID-19 who has 4 categorical levels, namely high, medium, low, and no cases. Predictor variables are elderly population, COVID-19 referral hospital, diabetes mellitus, hypertension, hand washing behavior, male population, and smoking habits. Based on results of the analysis, variables that significantly affect the risk zone status of COVID-19 spread in Indonesia are elderly population and diabetes mellitus. The Odds proportional figure shows that the higher percentage of the elderly population, the higher chance of an area with high-risk zone status (OR=1.171). The higher percentage of comorbidities diabetes mellitus, the higher chance of an area with high-risk zone status (OR=1.569).

Inertial Motion Capture-Based Estimation of L5/S1 Moments during Manual Materials Handling.

Inertial motion capture (IMC) has gained popularity in conducting ergonomic studies in the workplace. Because of the need to measure contact forces, most of these in situ studies are limited to a kinematic analysis, such as posture or working technique analysis. This paper aims to develop and evaluate an IMC-based approach to estimate back loading during manual material handling (MMH) tasks. During various representative workplace MMH tasks performed by nine participants, this approach was evaluated by comparing the results with the ones computed from optical motion capture and a large force platform. Root mean square errors of 21 Nm and 15 Nm were obtained for flexion and asymmetric L5/S1 moments, respectively. Excellent correlations were found between both computations on indicators based on L5/S1 peak and cumulative flexion moments, while lower correlations were found on indicators based on asymmetric moments. Since no force measurement or load kinematics measurement is needed, this study shows the potential of using only the handler’s kinematics measured by IMC to estimate kinetics variables. The assessment of workplace physical exposure, including L5/S1 moments, will allow more complete ergonomics evaluation and will improve the ecological validity compared to laboratory studies, where the situations are often simplified and standardized.