Applying a fusion of wearable sensors and a cognitive inspired architecture to real-time ergonomics analysis of manual assembly tasks

Oyekan, John; Chen, Y.; Turner, Christopher; Tiwari, Ashutosh

doi:10.1016/j.jmsy.2021.09.015

Cited by 20 publications

(9 citation statements)

References 33 publications

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“…The application of flexible wearable devices provides new possibilities for intelligent equipment, medical care, security, environmental detection, and other fields. [168][169][170][171][172] Flexible and portable wearable devices play an important role in human-computer interaction, which is also a trend for future development. 173,174 Accurate perception of stimuli in real time is the basis of human-computer interaction.…”

Section: Response Mechanisms and Their Applications In Iwdsmentioning

confidence: 99%

Recent advances in the material design for intelligent wearable devices

Ye³

et al. 2023

Mater. Chem. Front.

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Section: Response Mechanisms and Their Applications In Iwdsmentioning

confidence: 99%

Recent advances in the material design for intelligent wearable devices

Ye³

et al. 2023

Mater. Chem. Front.

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“…Research exists that also looks at how they can be used to inform ergonomics, data collection and help in prevention of injuries in manufacturing systems that involve extensive manual activities. For example, in Oyekan et al [65], the authors introduced a cognitive framework together with wearable sensors that support engineers and workers in an aerospace manufacturing system. Shown in Figure 2, the CAWES (Cognitive Architecture for Wearable Sensors) is based on the application of the ACT-R framework [66] to develop a data fusion pipeline for data streams from multiple wearable sensors.…”

Section: Data From Wearable Sensors For Use In the Redesign Of Manufa...mentioning

confidence: 99%

Personalised Production in the Age of Circular Additive Manufacturing

Turner

Oyekan

2023

Applied Sciences

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This research examines the opportunities provided by advances in digital manufacturing technologies for the provision of products designed to meet the needs of an individual consumer. The ability to co-create products with customers could enable mass personalisation to become a popular and fast-growing mode of production. Additive manufacturing, in both 3D and 4D printing forms, opens up new opportunities for circular economy-compliant production of such highly personalised products. Industry 4.0 has been seen by many as an agenda for the utilisation of interconnected digital technologies in industry, with a particular focus on manufacturing. Industry 5.0 seeks to address challenges that have grown in importance since the inception of Industry 4.0, such as the efficient inclusion of human worker skills in tandem with automation solutions, to address highly complex manufacturing scenarios while mitigating many of the environmental issues inherent with current manufacturing practices, while using circular economy principles. In examining the production of smart fabrics, this paper puts forward a framework for circular production of additively manufactured personalised products, co-designed with inputs from consumers.

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“…These technologies hold promise for mitigating musculoskeletal disorders (MSDs) in factory settings and reducing workplace accidents. Sensors, capable of tracking posture, force, and repetitive motions, serve to identify hazardous behaviors promptly, enabling the implementation of corrective measures to prevent injuries [1][2][3]. Moreover, they are envisaged to enhance work efficiency and refine training protocols.…”

Section: Introductionmentioning

confidence: 99%

Highly sensitive and easy-to-attach wearable sensor for measuring finger force based on curvature changes in an ellipse-shaped finger ring

Ozaki,

Ohta,

Fujiyoshi

2024

Smart Mater. Struct.

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Technologies aimed at digitizing worker actions to enhance human labor tasks and mitigate accidents and disabilities have garnered significant attention. This study focuses on monitoring the force exerted by the fingers and developing a wearable fingertip force sensor based on a simple elliptical ring structure in conjunction with a commercially available resistive bend sensor. Resembling a ring accessory, the sensor is easy to attach and detach, and exhibits high sensitivity, with a resistance change of approximately 9% for a fingertip load of 1N. Furthermore, to mitigate crosstalk during finger flexion, we propose a combined configuration employing this ring-shaped sensor alongside another sensor designed for measuring and rectifying finger flexion angles. Additionally, we introduce an empirically derived fitting function and a straightforward calibration procedure to extract the function’s parameters. The results indicate that the proposed system achieves an average RMS error of 0.53 N for force estimations of approximately 5 N, even amidst finger bending and postural changes.

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Applying a fusion of wearable sensors and a cognitive inspired architecture to real-time ergonomics analysis of manual assembly tasks

Cited by 20 publications

References 33 publications

Recent advances in the material design for intelligent wearable devices

Recent advances in the material design for intelligent wearable devices

Personalised Production in the Age of Circular Additive Manufacturing

Highly sensitive and easy-to-attach wearable sensor for measuring finger force based on curvature changes in an ellipse-shaped finger ring

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