Dispositivos vestíveis e produtividade no trabalho: uma análise bibliométrica da integração em ambientes profissionais

Dispositivos vestíveis e produtividade no trabalho: uma análise bibliométrica da integração em ambientes profissionais

Autores

DOI:

https://doi.org/10.58951/dataset.2024.018

Palavras-chave:

Tecnologias vestíveis, Dispositivos vestíveis, Internet das coisas, Transformação digital

Resumo

Este estudo analisa a percepção e a aceitação dos trabalhadores sobre o uso de dispositivos vestíveis no ambiente de trabalho. Foi realizada uma revisão bibliométrica apoiada por análise de redes complexas, por meio da qual foram identificados os temas motores da área. Os resultados apontam o aumento no uso destas tecnologias e os fatores atrelados a aceitação ou rejeição dos funcionários. A percepção dos trabalhadores e os benefícios potenciais das tecnologias vestíveis também são discutidos. Os achados revelam ainda os fatores que influenciam a aceitação da tecnologia e destacam características organizacionais e tecnológicas que facilitam a adoção para um uso diário eficaz. O estudo contribui para a literatura ao avaliar a viabilidade e aceitação de tecnologias vestíveis dentro das empresas e ressalta que a falta de envolvimento dos funcionários na seleção dos dispositivos é uma barreira significativa à adoção.

Referências

Abdolmohammadi, M. J., & Baker, C. R. (2006). Accountants’ value preferences and moral reasoning. Journal of Business Ethics, 69(1), 11–25. https://doi.org/10.1007/s10551-006-9064-y DOI: https://doi.org/10.1007/s10551-006-9064-y

Ailneni, R. C., Syamala, K. R., Kim, I. S., & Hwang, J. (2019). Influence of the wearable posture correction sensor on head and neck posture: Sitting and standing workstations. Work, 62(1), 27–35. https://doi.org/10.3233/WOR-182839 DOI: https://doi.org/10.3233/WOR-182839

Barkallah, E., Freulard, J., Otis, M. J. D., Ngomo, S., Ayena, J. C., & Desrosiers, C. (2017). Wearable devices for classification of inadequate posture at work using neural networks. Sensors (Switzerland), 17(9). https://doi.org/10.3390/s17092003 DOI: https://doi.org/10.3390/s17092003

Boerema, S. T., Essink, G. B., Tönis, T. M., van Velsen, L., & Hermens, H. J. (2016). Sedentary behaviour profiling of officeworkers: A sensitivity analysis of sedentary cut-points. Sensors, 16(1). https://doi.org/10.3390/s16010022 DOI: https://doi.org/10.3390/s16010022

Brandt, M., Madeleine, P., Samani, A., Ajslev, J. Z. N., Jakobsen, M. D., Sundstrup, E., & Andersen, L. L. (2018). Effects of a participatory ergonomics intervention with wearable technical measurements of physical workload in the construction industry: Cluster randomized controlled trial. Journal of Medical Internet Research, 20(12). https://doi.org/10.2196/10272 DOI: https://doi.org/10.2196/10272

Buller, M. J., Welles, A. P., & Friedl, K. E. (2018). Wearable physiological monitoring for human thermal-work strain optimization. Journal of Applied Physiology, 124(2), 432–441. https://doi.org/10.1152/japplphysiol.00353.2017 DOI: https://doi.org/10.1152/japplphysiol.00353.2017

Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry. Scientometrics, 22(1), 155–205. https://doi.org/10.1007/BF02019280 DOI: https://doi.org/10.1007/BF02019280

Choi, B., Hwang, S., & Lee, S. H. (2017). What drives construction workers’ acceptance of wearable technologies in the workplace?: Indoor localization and wearable health devices for occupational safety and health. Automation in Construction, 84, 31–41. https://doi.org/10.1016/j.autcon.2017.08.005 DOI: https://doi.org/10.1016/j.autcon.2017.08.005

Choi, B., Jebelli, H., & Lee, S. H. (2019). Feasibility analysis of electrodermal activity (EDA) acquired from wearable sensors to assess construction workers’ perceived risk. Safety Science, 115, 110–120. https://doi.org/10.1016/j.ssci.2019.01.022 DOI: https://doi.org/10.1016/j.ssci.2019.01.022

Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5(1), 146–166. https://doi.org/10.1016/j.joi.2010.10.002 DOI: https://doi.org/10.1016/j.joi.2010.10.002

Cobo, M. J., Lõpez-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2012). SciMAT: A new science mapping analysis software tool. Journal of the American Society for Information Science and Technology, 63(8), 1609–1630. https://doi.org/10.1002/asi.22688 DOI: https://doi.org/10.1002/asi.22688

Coulter, N., Monarch, I., & Konda, S. (1998). Software engineering as seen through its research literature: A study in co-word analysis. Journal of the American Society for Information Science, 49(13), 1206–1223. https://doi.org/10.1002/(sici)1097-4571(1998)49:13<1206::aid-asi7>3.3.co;2-6 DOI: https://doi.org/10.1002/(SICI)1097-4571(1998)49:13<1206::AID-ASI7>3.0.CO;2-F

Distler, V., Lallemand, C., & Koenig, V. (2020). How Acceptable Is This? How User Experience Factors Can Broaden our Understanding of The Acceptance of Privacy Trade-offs. Computers in Human Behavior, 106. https://doi.org/10.1016/j.chb.2019.106227 DOI: https://doi.org/10.1016/j.chb.2019.106227

Donati, L. A. P. (2005). O computador como veste-interface: (re) configurando os espaços de atuação [Universidade Estadual de Campinas]. https://doi.org/http://10.0.186.133/T/UNICAMP.2005.328408

Eriksson, T. (2011). Reward Systems and Incentives in a Project Based Organisation [Chalmers University of Technology]. https://publications.lib.chalmers.se/records/fulltext/155093.pdf

Flaherty, J. L. yn. (2014). Digital Diagnosis: Privacy and the Regulation of Mobile Phone Health Applications. American Journal of Law & Medicine, 40(4), 416–441.

Fontana, J. M., Farooq, M., & Sazonov, E. (2014). Automatic ingestion monitor: A novel wearable device for monitoring of ingestive behavior. IEEE Transactions on Biomedical Engineering, 61(6), 1772–1779. https://doi.org/10.1109/TBME.2014.2306773 DOI: https://doi.org/10.1109/TBME.2014.2306773

Francés, L., Morer, P., Rodriguez, M. I., & Cazón, A. (2019). Design and development of a low-cost wearable glove to track forces exerted by workers in car assembly lines. Sensors (Switzerland), 19(2). https://doi.org/10.3390/s19020296 DOI: https://doi.org/10.3390/s19020296

Giddens, L., Leidner, D., & Gonzalez, E. (2017). The role of fitbits in corporate wellness programs: Does step count matter? Proceedings of the Annual Hawaii International Conference on System Sciences, 2017-January, 3627–3635. https://doi.org/10.24251/hicss.2017.438 DOI: https://doi.org/10.24251/HICSS.2017.438

Gope, P., & Hwang, T. (2016). BSN-Care: A Secure IoT-Based Modern Healthcare System Using Body Sensor Network. IEEE Sensors Journal, 16(5), 1368–1376. https://doi.org/10.1109/JSEN.2015.2502401 DOI: https://doi.org/10.1109/JSEN.2015.2502401

Hallman, D. M., Mathiassen, S. E., van der Beek, A. J., Jackson, J. A., & Coenen, P. (2019). Calibration of self-reported time spent sitting, standing and walking among office workers: A compositional data analysis. International Journal of Environmental Research and Public Health, 16(17). https://doi.org/10.3390/ijerph16173111 DOI: https://doi.org/10.3390/ijerph16173111

Hamblen, M. (2015). As smartwatches gain traction, personal data privacy worries mount. Computerworld. May 22, 2015. Available from: <https://www.computerworld.com/article/1617871/as-smartwatches-gain-traction-personal-data-privacy-worries-mount-2.html>. Accessed September 10, 2024.

Hwang, S., & Lee, S. H. (2017). Wristband-type wearable health devices to measure construction workers’ physical demands. Automation in Construction, 83, 330–340. https://doi.org/10.1016/j.autcon.2017.06.003 DOI: https://doi.org/10.1016/j.autcon.2017.06.003

Jacobs, J. V., Hettinger, L. J., Huang, Y. H., Jeffries, S., Lesch, M. F., Simmons, L. A., Verma, S. K., & Willetts, J. L. (2019). Employee acceptance of wearable technology in the workplace. Applied Ergonomics, 78, 148–156. https://doi.org/10.1016/j.apergo.2019.03.003 DOI: https://doi.org/10.1016/j.apergo.2019.03.003

Jun, D., Johnston, V., McPhail, S. M., & O’Leary, S. (2019). Are Measures of Postural Behavior Using Motion Sensors in Seated Office Workers Reliable? Human Factors, 61(7), 1141–1161. https://doi.org/10.1177/0018720818821273 DOI: https://doi.org/10.1177/0018720818821273

Kajiwara, Y., Shimauchi, T., & Kimura, H. (2019). Predicting emotion and engagement of workers in order picking based on behavior and pulse waves acquired by wearable devices. Sensors (Switzerland), 19(1). https://doi.org/10.3390/s19010165 DOI: https://doi.org/10.3390/s19010165

Kalantari, M. (2017). Consumers adoption of wearable technologies: literature review, synthesis, and future research agenda. International Journal of Technology Marketing, 12(1), 1. https://doi.org/10.1504/ijtmkt.2017.10008634 DOI: https://doi.org/10.1504/IJTMKT.2017.10008634

Kristoffersson, A., & Lindén, M. (2020). A systematic review on the use of wearable body sensors for health monitoring: A qualitative synthesis. Sensors (Switzerland), 20(5). https://doi.org/10.3390/s20051502 DOI: https://doi.org/10.3390/s20051502

Lee, R. G., Chen, C. Y., Hsiao, C. C., & Lin, R. (2015). Heart rate monitoring systems in groups for reliability and validity assessment of cardiorespiratory fitness analysis. Biomedical Engineering - Applications, Basis and Communications, 27(6). https://doi.org/10.4015/S1016237215500556 DOI: https://doi.org/10.4015/S1016237215500556

Lee, W., Seto, E., Lin, K. Y., & Migliaccio, G. C. (2017). An evaluation of wearable sensors and their placements for analyzing construction worker’s trunk posture in laboratory conditions. Applied Ergonomics, 65, 424–436. https://doi.org/10.1016/j.apergo.2017.03.016 DOI: https://doi.org/10.1016/j.apergo.2017.03.016

Maltseva, K. (2020). Wearables in the workplace: The brave new world of employee engagement. Business Horizons, 63(4), 493–505. https://doi.org/10.1016/j.bushor.2020.03.007 DOI: https://doi.org/10.1016/j.bushor.2020.03.007

Mann, S. (1996). Smart clothing: the shift to wearable computing. Communications of the ACM, 39(8), 23–24. https://doi.org/https://doi.org/10.1145/232014.232021 DOI: https://doi.org/10.1145/232014.232021

Mettler, T., & Wulf, J. (2019). Physiolytics at the workplace: Affordances and constraints of wearables use from an employee’s perspective. Information Systems Journal, 29(1), 245–273. https://doi.org/10.1111/isj.12205 DOI: https://doi.org/10.1111/isj.12205

Nedungadi, P., Jayakumar, A., & Raman, R. (2018). Personalized Health Monitoring System for Managing Well-Being in Rural Areas. Journal of Medical Systems, 42(1). https://doi.org/10.1007/s10916-017-0854-9 DOI: https://doi.org/10.1007/s10916-017-0854-9

Oswald, D., Ahiaga-Dagbui, D. D., Sherratt, F., & Smith, S. D. (2020). An industry structured for unsafety? An exploration of the cost-safety conundrum in construction project delivery. Safety Science, 122. https://doi.org/10.1016/j.ssci.2019.104535 DOI: https://doi.org/10.1016/j.ssci.2019.104535

Pink, D. H. (2009). Drive: The Surprising Truth about What Motivates Us. New York: Riverhead Books.

Podgórski, D., Majchrzycka, K., Dąbrowska, A., Gralewicz, G., & Okrasa, M. (2017). Towards a conceptual framework of OSH risk management in smart working environments based on smart PPE, ambient intelligence and the Internet of Things technologies. International Journal of Occupational Safety and Ergonomics, 23(1), 1–20. https://doi.org/10.1080/10803548.2016.1214431 DOI: https://doi.org/10.1080/10803548.2016.1214431

Rowland, C. (2019). With fitness trackers in the workplace, bosses can monitor your every step — and possibly more. The Washington Post.

Sado, F., Yap, H. J., Ghazilla, R. A. R., & Ahmad, N. (2019). Design and control of a wearable lower-body exoskeleton for squatting and walking assistance in manual handling works. Mechatronics, 63. https://doi.org/10.1016/j.mechatronics.2019.102272 DOI: https://doi.org/10.1016/j.mechatronics.2019.102272

Salah, H., MacIntosh, E., & Rajakulendran, N. (2014). Wearable Tech: Leveraging Canadian Innovation to Improve Health. MaRS Market Insights, 1–45. https://www.marsdd.com/wp-content/uploads/2015/02/MaRSReport-WearableTech.pdf

Sazonov, Edward (Ed.). Wearable Sensors: Fundamentals, implementation and applications. Elsevier, 2014.

Schall, M. C., Sesek, R. F., & Cavuoto, L. A. (2018). Barriers to the Adoption of Wearable Sensors in the Workplace: A Survey of Occupational Safety and Health Professionals. Human Factors, 60(3), 351–362. https://doi.org/10.1177/0018720817753907 DOI: https://doi.org/10.1177/0018720817753907

Schulz, P. S., Zimmerman, L., & Johansson, P. (2018). Seasonal Work and Cardiovascular Risk Factors in Farmers. Journal of Cardiovascular Nursing, 33(4), E35–E39. https://doi.org/10.1097/JCN.0000000000000490 DOI: https://doi.org/10.1097/JCN.0000000000000490

Schwambach, G. C. S., López, Ó. H., Sott, M. K., Carvalho Tedesco, L. P., & Molz, R. F. (2022). Acceptance and perception of wearable technologies: A survey on Brazilian and European companies. Technology in Society, 68. https://doi.org/10.1016/j.techsoc.2021.101840 DOI: https://doi.org/10.1016/j.techsoc.2021.101840

Seo, Y., DiLeo, T., Powell, J. B., Kim, J. H., Roberge, R. J., & Coca, A. (2016). Comparison of estimated core body temperature measured with the BioHarness and rectal temperature under several heat stress conditions. Journal of Occupational and Environmental Hygiene, 13(8), 612–620. https://doi.org/10.1080/15459624.2016.1161199 DOI: https://doi.org/10.1080/15459624.2016.1161199

Seymour, S. (2008). Fashionable Technology: The Intersection of Design, Fashion, Science, and Technology. Springer Vienna. https://doi.org/10.1007/978-3-211-74500-7 DOI: https://doi.org/10.1007/978-3-211-74500-7

Shin, S. K. S., Amenuvor, F. E., Basilisco, R., & Owusu-Antwi, K. (2019). Brand Trust and Brand Loyalty: A Moderation and Mediation Perspective. Current Journal of Applied Science and Technology, 1–17. https://doi.org/10.9734/cjast/2019/v38i430376 DOI: https://doi.org/10.9734/cjast/2019/v38i430376

Stephenson, A., McDonough, S. M., Murphy, M. H., Nugent, C. D., Wilson, I. M., & Mair, J. L. (2020). Exploring the views of desk-based office workers and their employers’ beliefs regarding strategies to reduce occupational sitting time, with an emphasis on technology-supported approaches. Journal of Occupational and Environmental Medicine, 62(2), 149–155. https://doi.org/10.1097/JOM.0000000000001777 DOI: https://doi.org/10.1097/JOM.0000000000001777

Swan, M. (2013). The quantified self: Fundamental disruption in big data science and biological discovery. Big Data, 1(2), 85–99. https://doi.org/10.1089/big.2012.0002 DOI: https://doi.org/10.1089/big.2012.0002

Talukder, M. S., Sorwar, G., Bao, Y., Ahmed, J. U., & Palash, M. A. S. (2020). Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach. Technological Forecasting and Social Change, 150. https://doi.org/10.1016/j.techfore.2019.119793 DOI: https://doi.org/10.1016/j.techfore.2019.119793

Valero, E., Sivanathan, A., Bosché, F., & Abdel-Wahab, M. (2016). Musculoskeletal disorders in construction: A review and a novel system for activity tracking with body area network. Applied Ergonomics, 54, 120–130. https://doi.org/10.1016/j.apergo.2015.11.020 DOI: https://doi.org/10.1016/j.apergo.2015.11.020

van Eck, N. J., & Waltman, L. (2012). A New Methodology for Constructing a Publication-Level Classification System of Science. Journal of The American Society for Information Science and Technology, 63(12), 2378–2392. https://doi.org/10.48550/arXiv.1203.0532 DOI: https://doi.org/10.1002/asi.22748

Wang, D., Dai, F., & Ning, X. (2015). Risk Assessment of Work-Related Musculoskeletal Disorders in Construction: State-of-the-Art Review. Journal of Construction Engineering and Management, 141(6), 04015008 (15 pp.). https://doi.org/10.1061/(asce)co.1943-7862.0000979 DOI: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000979

Wang, Y., Cang, S., & Yu, H. (2019). A survey on wearable sensor modality centred human activity recognition in health care. Expert Systems with Applications, 137, 167–190. https://doi.org/10.1016/j.eswa.2019.04.057 DOI: https://doi.org/10.1016/j.eswa.2019.04.057

Wen, D., Zhang, X., & Lei, J. (2017). Consumers’ perceived attitudes to wearable devices in health monitoring in China: A survey study. Computer Methods and Programs in Biomedicine, 140, 131–137. https://doi.org/10.1016/j.cmpb.2016.12.009 DOI: https://doi.org/10.1016/j.cmpb.2016.12.009

Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): A literature review. Journal of Enterprise Information Management, 28(3), 443–448. https://doi.org/10.1108/JEIM-09-2014-0088 DOI: https://doi.org/10.1108/JEIM-09-2014-0088

Yildirim, H., & Ali-Eldin, A. M. T. (2019). A model for predicting user intention to use wearable IoT devices at the workplace. Journal of King Saud University - Computer and Information Sciences, 31(4), 497–505. https://doi.org/10.1016/j.jksuci.2018.03.001 DOI: https://doi.org/10.1016/j.jksuci.2018.03.001

Zhang, M., Luo, M., Nie, R., & Zhang, Y. (2017). Technical attributes, health attribute, consumer attributes and their roles in adoption intention of healthcare wearable technology. International Journal of Medical Informatics, 108, 97–109. https://doi.org/10.1016/j.ijmedinf.2017.09.016. DOI: https://doi.org/10.1016/j.ijmedinf.2017.09.016

Downloads

Publicado

17/09/2024

Como Citar

Schwambach, G. C. dos S., Sott , M. K., & Schwambach, R. E. (2024). Dispositivos vestíveis e produtividade no trabalho: uma análise bibliométrica da integração em ambientes profissionais. Dataset Reports, 3(1), 101–106. https://doi.org/10.58951/dataset.2024.018

Edição

Seção

Artigo Original
Loading...