In-field and in-lab ergonomic assessment of manual materials handlingtasks using a passive back exoskeleton
Notice bibliographique
Résumé
Abstract: There is an interest in investigating the effects of physical assistance devices such as exoskeletons in terms of reducing the risk and rate of work-related musculoskeletal disorders. Most previous studies were conducted in laboratory environments since in-field evaluations are often challenging. However, the outcomes of in-lab and in-field evaluations may not always be comparable. Moreover, workers may use some assistive tools to lift or move heavy items while holding a bending posture, leading to different risks of low back pain. Thus, we conducted an experiment to assess the differences between the in-lab and in-field levels of ergonomic risks during the manual materials handling tasks, using two different assistive tools while wearing a passive exoskeleton. For the purpose of our study, 125-lbs circular disks were lifted using the assistive tools with and without wearing a passive back-support exoskeleton (BackX, SuitX, CA,USA). Each trial took 2 repetitions and 5 seconds standing still at the beginning of each motion. The in-lab data was recorded from 10 able-bodied participants (7 males, 3 females, body mass: 61±8 kg, body height:171±48 cm, age: 23±1.5 y.o.) and the in-field data were recorded from 10 ablebodied workers (9 males, 1 female, body mass: 75±12 kg, body height:175±11 cm, age: 36±6 y.o.). We collected data using electromyography (EMG) sensors and inertial measurement units (IMUs) to record muscle activity and body posture, respectively. Furthermore, the ergonomic risk assessment was performed using the rapid entire body assessment (REBA) score. The REBA scores measured using IMU data and the max normalized EMG amplitude for each task were compared between in-field and in-lab experiments. EMG amplitude of each participant was normalized to their previously measured maximum voluntary contraction. The muscle activity measured from in-field experiments was significantly larger for most muscles and smaller for some other muscles compared to the in-lab data (p < 0.05). Muscle activities while using either tools with exoskeleton were also significantly larger for some muscles and smaller for others when the task is performed in-field compared to in-lab. In addition, the REBA score of in-field workers using both tools while wearing the exoskeleton was significantly larger than the REBA score of the in-lab participants. The results of this study suggest the need for ergonomic risk assessment and occupational exoskeleton evaluation in real-world environments in addition to lab assessments. The sources of this difference between the in-lab and in-field results could be 1) potential differences between the task implementation in the two environments, 2) the lack of experience of in-lab participants compared to in-field workers and 3) the inconsistency of the male-to-female participants ratios between lab and field experiments.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».