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Diaz-Olivares, Jose A.
Publications (3 of 3) Show all publications
Vega-Barbas, M., Diaz-Olivares, J. A., Lu, K., Forsman, M., Seoane, F. & Abtahi, F. (2019). P-Ergonomics Platform: Toward Precise, Pervasive, and Personalized Ergonomics using Wearable Sensors and Edge Computing. Sensors, 19(5), Article ID 1225.
Open this publication in new window or tab >>P-Ergonomics Platform: Toward Precise, Pervasive, and Personalized Ergonomics using Wearable Sensors and Edge Computing
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2019 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, no 5, article id 1225Article in journal (Refereed) Published
Abstract [en]

Preventive healthcare has attracted much attention recently. Improving people's lifestyles and promoting a healthy diet and wellbeing are important, but the importance of work-related diseases should not be undermined. Musculoskeletal disorders (MSDs) are among the most common work-related health problems. Ergonomists already assess MSD risk factors and suggest changes in workplaces. However, existing methods are mainly based on visual observations, which have a relatively low reliability and cover only part of the workday. These suggestions concern the overall workplace and the organization of work, but rarely includes individuals' work techniques. In this work, we propose a precise and pervasive ergonomic platform for continuous risk assessment. The system collects data from wearable sensors, which are synchronized and processed by a mobile computing layer, from which exposure statistics and risk assessments may be drawn, and finally, are stored at the server layer for further analyses at both individual and group levels. The platform also enables continuous feedback to the worker to support behavioral changes. The deployed cloud platform in Amazon Web Services instances showed sufficient system flexibility to affordably fulfill requirements of small to medium enterprises, while it is expandable for larger corporations. The system usability scale of 76.6 indicates an acceptable grade of usability.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
disease prevention, occupational healthcare, P-Ergonomics, precision ergonomics, musculoskeletal disorders, smart textiles, wearable sensors, wellbeing at work
National Category
Occupational Health and Environmental Health
Identifiers
urn:nbn:se:kth:diva-249891 (URN)10.3390/s19051225 (DOI)000462540400244 ()30862019 (PubMedID)2-s2.0-85062856566 (Scopus ID)
Available from: 2019-04-26 Created: 2019-04-26 Last updated: 2019-04-26Bibliographically approved
Yang, L., Lu, K., Diaz-Olivares, J. A., Seoane, F., Lindecrantz, K., Forsman, M., . . . Eklund, J. A. E. (2018). Towards Smart Work Clothing for Automatic Risk Assessment of Physical Workload. IEEE Access, 6, 40059-40072
Open this publication in new window or tab >>Towards Smart Work Clothing for Automatic Risk Assessment of Physical Workload
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2018 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 40059-40072Article in journal (Refereed) Published
Abstract [en]

Work-related musculoskeletal and cardiovascular disorders are still prevalent in today's working population. Nowadays, risk assessments are usually performed via self-reports or observations, which have relatively low reliability. Technology developments in textile electrodes (textrodes), inertial measurement units, and the communication and processing capabilities of smart phones/tablets provide wearable solutions that enable continuous measurements of physiological and musculoskeletal loads at work with sufficient reliability and resource efficiency. In this paper, a wearable system integrating textrodes, motion sensors, and real-time data processing through a mobile application was developed as a demonstrator of risk assessment related to different types and levels of workload and activities. The system was demonstrated in eight subjects from four occupations with various workload intensities, during which the heart rate and leg motion data were collected and analyzed with real-time risk assessment and feedback. The system showed good functionality and usability as a risk assessment tool. The results contribute to designing and developing future wearable systems and bring new solutions for the prevention of work-related disorders.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Energy expenditure, sitting, standing, occupational health, preventive healthcare, wearable sensors, sensorized garments
National Category
Other Engineering and Technologies not elsewhere specified
Identifiers
urn:nbn:se:kth:diva-233434 (URN)10.1109/ACCESS.2018.2855719 (DOI)000441214800001 ()2-s2.0-85050003765 (Scopus ID)
Note

QC 20180821

Available from: 2018-08-21 Created: 2018-08-21 Last updated: 2019-11-12Bibliographically approved
Abtahi, F., Lu, K., Diaz-Olivares, J. A., Forsman, M., Seoane, F. & Lindecrantz, K. (2018). Wearable Sensors Enabling Personalized Occupational Healthcare. In: Chatzigiannakis, I Tobe, Y Novais, P Amft, O (Ed.), INTELLIGENT ENVIRONMENTS 2018: . Paper presented at 14th International Conference on Intelligent Environments (IE), JUN 25-28, 2018, Sapienza Univ Roma, Dipartimento Ingn Informatica, Automatica & Gestionale, Roma, ITALY (pp. 371-376). IOS PRESS
Open this publication in new window or tab >>Wearable Sensors Enabling Personalized Occupational Healthcare
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2018 (English)In: INTELLIGENT ENVIRONMENTS 2018 / [ed] Chatzigiannakis, I Tobe, Y Novais, P Amft, O, IOS PRESS , 2018, p. 371-376Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents needs and potentials for wearable sensors in occupational healthcare. In addition, it presents ongoing European and Swedish projects for developing personalized, and pervasive wearable systems for assessing risks of developing musculoskeletal disorders and cardiovascular diseases at work. Occupational healthcare should benefit in preventing diseases and disorders by providing the right feedback at the right time to the right person. Collected data from workers can provide evidence supporting the ergonomic and industrial tasks of redesigning the working environment to reduce the risks.

Place, publisher, year, edition, pages
IOS PRESS, 2018
Series
Ambient Intelligence and Smart Environments, ISSN 1875-4163 ; 23
Keywords
P-Health, Ergonomic, Wearable Technologies
National Category
Medical Ergonomics
Identifiers
urn:nbn:se:kth:diva-259484 (URN)10.3233/978-1-61499-874-7-371 (DOI)000482617600045 ()978-1-61499-874-7 (ISBN)978-1-61499-873-0 (ISBN)
Conference
14th International Conference on Intelligent Environments (IE), JUN 25-28, 2018, Sapienza Univ Roma, Dipartimento Ingn Informatica, Automatica & Gestionale, Roma, ITALY
Note

QC 20190916

Available from: 2019-09-16 Created: 2019-09-16 Last updated: 2019-12-12Bibliographically approved
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