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  • 1.
    Abtahi, Farhad
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi. Karolinska Inst, Inst Environm Med, S-17165 Stockholm, Sweden..
    Lu, Ke
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi.
    Diaz-Olivares, Jose A.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi.
    Forsman, Mikael
    Karolinska Inst, Inst Environm Med, S-17165 Stockholm, Sweden..
    Seoane, Fernando
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Halsovagen 7, S-14157 Stockholm, Sweden.;Univ Boras, Swedish Sch Text, Allegatan 1, S-50190 Boras, Sweden.;Karolinska Univ Hosp, Dept Biomed Engn, S-17176 Solna, Sweden..
    Lindecrantz, Kaj
    Karolinska Inst, Inst Environm Med, S-17165 Stockholm, Sweden.;Univ Boras, Sci Pk,Allegatan 1, S-50190 Boras, Sweden..
    Wearable Sensors Enabling Personalized Occupational Healthcare2018Ingår i: INTELLIGENT ENVIRONMENTS 2018 / [ed] Chatzigiannakis, I Tobe, Y Novais, P Amft, O, IOS PRESS , 2018, s. 371-376Konferensbidrag (Refereegranskat)
    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.

  • 2.
    Vega-Barbas, Mario
    et al.
    Karolinska Inst, Inst Environm Med, Solnavagen 1, S-17177 Solna, Sweden.
    Diaz-Olivares, Jose A.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi.
    Lu, Ke
    Karolinska Inst, Inst Environm Med, Solnavagen 1, S-17177 Solna, Sweden..
    Forsman, Mikael
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi. Karolinska Inst, Inst Environm Med, Solnavagen 1, S-17177 Solna, Sweden.
    Seoane, Fernando
    Karolinska Inst, Dept Clin Sci Intervent & Technol, Halsovagen 7, S-14157 Huddinge, Sweden.;Univ Boras, Swedish Sch Text, Allegatan 1, S-50190 Boras, Sweden.;Karolinska Univ Hosp, Dept & T Biomed Engn, S-17176 Solna, Sweden..
    Abtahi, Farhad
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi. Karolinska Inst, Inst Environm Med, Solnavagen 1, S-17177 Solna, Sweden.
    P-Ergonomics Platform: Toward Precise, Pervasive, and Personalized Ergonomics using Wearable Sensors and Edge Computing2019Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, nr 5, artikel-id 1225Artikel i tidskrift (Refereegranskat)
    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.

  • 3.
    Yang, Liyun
    et al.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi.
    Lu, Ke
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi.
    Diaz-Olivares, Jose A.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi.
    Seoane, Fernando
    Univ Boras, Swedish Sch Text, S-50190 Boras, Sweden.;Karolinska Inst, Inst Clin Sci Intervent & Technol, S-14157 Huddinge, Sweden.;Karolinska Univ Hosp, Dept Biomed Engn, S-14157 Huddinge, Sweden..
    Lindecrantz, Kaj
    Karolinska Inst, Inst Environm Med, S-17177 Stockholm, Sweden.;Univ Boras, Swedish Sch Text, S-50190 Boras, Sweden..
    Forsman, Mikael
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi. nstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
    Abtahi, Farhad
    Karolinska Inst, Inst Environm Med, S-17177 Stockholm, Sweden..
    Eklund, Jörgen A. E.
    KTH, Skolan för kemi, bioteknologi och hälsa (CBH), Medicinteknik och hälsosystem, Ergonomi.
    Towards Smart Work Clothing for Automatic Risk Assessment of Physical Workload2018Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 6, s. 40059-40072Artikel i tidskrift (Refereegranskat)
    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.

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