Body Posture Position Alarm Prototype Based on NodeMCU ESP8266
DOI:
https://doi.org/10.12928/biste.v5i4.9543Keywords:
Alarm, Back Support Shoulder, ESP8266, Flexible Sensor, NodeMCUAbstract
Lack of physical activity has a negative impact, namely reduced motor coordination abilities and changes in posture or shape of the spine. Sitting positions that are more static and less ergonomic, such as sitting in a hunched position, can trigger significant muscle activation. Therefore, in an effort to prevent bone abnormalities, research was carried out regarding a prototype body posture alarm based on the NodeMCU ESP8266. This prototype uses a flexible sensor to read spinal curvature integrated into the NodeMCU ESP8266 and a buzzer as the output. This prototype will be attached to the back support shoulder, so this prototype design can also help repair bones that have been damaged due to bad sitting habits. In general, this prototype reminds users to always be in a normal body position by making a sound when the body position is not normal. From the test results, the prototype works well. NodeMCu's speed in capturing WiFi signals is fast enough so that the prototype works quickly, flexible sensor readings are accurate without using an amplifier. The back support shoulder design is very efficient in helping users to maintain a normal body position.
References
Q. Song, X. Zhang, M. Mao, W. Sun, C. Zhang, Y. Chen, and L. Li, “Relationship of proprioception, cutaneous sensitivity, and muscle strength with the balance control among older adults,” Journal of sport and health science, vol. 10, no. 5, pp. 585-593, 2021, https://doi.org/10.1016/j.jshs.2021.07.005.
A. H. Wibowo and A. Mawadati, “The analysis of employees’ work posture by using rapid entire body assessment (REBA) and rapid upper limb assessment (RULA),” In IOP conference series: earth and environmental science, vol. 704, no. 1, p. 012022, 2021, https://doi.org/10.1088/1755-1315/704/1/012022.
H. Mughal, A. R. Javed, M. Rizwan, A. S. Almadhor and N. Kryvinska, "Parkinson’s Disease Management via Wearable Sensors: A Systematic Review," in IEEE Access, vol. 10, pp. 35219-35237, 2022, https://doi.org/10.1109/ACCESS.2022.3162844.
C. Bontrup, W. R. Taylor, M. Fliesser, R. Visscher, T. Green, P. M. Wippert, and R. Zemp, “Low back pain and its relationship with sitting behaviour among sedentary office workers,” Applied ergonomics, vol. 81, p. 102894, 2019, https://doi.org/10.1016/j.apergo.2019.102894.
C. K. Wong et al., “Prevalence, incidence, and factors associated with non-specific chronic low back pain in community-dwelling older adults aged 60 years and older: a systematic review and meta-analysis,” The journal of pain, vol. 23, no. 4, pp. 509-534, 2022, https://doi.org/10.1016/j.jpain.2021.07.012.
M. K. Ijaz, K. Shomenov, D. Otegen, E. Shehab, and M. H. Ali, “Design and development of a 3D printed water driven spinal posture corrector,” The International Journal of Advanced Manufacturing Technology, vol. 124, no. 5-6, pp. 1457-1471, 2023, https://doi.org/10.1007/s00170-022-10611-7.
R. Bootsman, P. Markopoulos, Q. Qi, Q. Wang, and A. A. Timmermans, “Wearable technology for posture monitoring at the workplace,” International Journal of Human-Computer Studies, vol. 132, pp. 99-111, 2019, https://doi.org/10.1016/j.ijhcs.2019.08.003.
P. Mikalef, M. Boura, G. Lekakos, and J. Krogstie, “Big data analytics and firm performance: Findings from a mixed-method approach,” Journal of Business Research, vol. 98, pp. 261-276, 2019, https://doi.org/10.1016/j.jbusres.2019.01.044.
Z. Wan, Y. Song and Z. Cao, "Environment Dynamic Monitoring and Remote Control of Greenhouse with ESP8266 NodeMCU," 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), pp. 377-382, 2019, https://doi.org/10.1109/ITNEC.2019.8729519.
B. Schäfer and H. Stuckenschmidt, "Arrow R-CNN for Flowchart Recognition," 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), pp. 7-13, 2019, https://doi.org/10.1109/ICDARW.2019.00007.
V. Lakshmikantha, A. Hiriyannagowda, A. Manjunath, A. Patted, J. Basavaiah, and A. A. Anthony, “IoT based smart water quality monitoring system,” Global Transitions Proceedings, vol. 2, no. 2, pp. 181-186. 2021, https://doi.org/10.1016/j.gltp.2021.08.062.
J. M. S. Waworundeng, M. A. T. Kalalo and D. P. Y. Lokollo, "A Prototype of Indoor Hazard Detection System using Sensors and IoT," 2020 2nd International Conference on Cybernetics and Intelligent System (ICORIS), pp. 1-6, 2020, https://doi.org/10.1109/ICORIS50180.2020.9320809.
L. -C. Kuo and C. -C. Tai, "Robust Image-Based Water-Level Estimation Using Single-Camera Monitoring," in IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1-11, no. 5007611, 2022, https://doi.org/10.1109/TIM.2022.3161691.
F. Bandini et al., “Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: Comparison of radar altimetry, LIDAR and photogrammetry techniques,” Remote Sensing of Environment, vol. 237, p. 111487, 2020, https://doi.org/10.1016/j.rse.2019.111487.
A. J. Moshayedi, A. S. Roy, L. Liao and S. Li, "Raspberry Pi SCADA Zonal based System for Agricultural Plant Monitoring," 2019 6th International Conference on Information Science and Control Engineering (ICISCE), Shanghai, China, 2019, pp. 427-433, 2019, https://doi.org/10.1109/ICISCE48695.2019.00092.
A. M. R. Ulil, S. Sukaridhoto, A. Tjahjono, and D. K. Basuki, “The vehicle as a mobile sensor network base IoT and big data for pothole detection caused by flood disaster,” In IOP Conference Series: Earth and Environmental Science, vol. 239, no. 1, p. 012034, 2019, https://doi.org/10.1088/1755-1315/239/1/012034.
C. E. Medina-Ortega, M. A. Patiño-Noguera, J. Revelo-Fuelagán, and J. E. Candelo-Becerra, “Programmable Electronic Load Prototype for the Power Quality Analysis of an Experimental Microgrid,” Sustainability, vol. 14, no. 18, p. 11258, 2022, https://doi.org/10.3390/su141811258.
Y. Gong, X. Cheng, Z. Wu, Y. Liu, P. Yu and X. Hu, "A Flexible Tactile Sensor Array for Dynamic Triaxial Force Measurement Based on Aligned Piezoresistive Nanofibers," in IEEE Sensors Journal, vol. 21, no. 19, pp. 21989-21998, 2021, https://doi.org/10.1109/JSEN.2021.3103781.
T. P. F. Bento, C. V. dos Santos Genebra, N. M. Maciel, G. P. Cornelio, S. F. A. P. Simeão, and A. de Vitta, “Low back pain and some associated factors: is there any difference between genders?. Brazilian journal of physical therapy, vol. 24(1), 79-87, 2020, https://doi.org/10.1016/j.bjpt.2019.01.012.
Shiri, R., Falah‐Hassani, K., Heliövaara, M., Solovieva, S., Amiri, S., Lallukka, T., ... & Viikari‐Juntura, E. (2019). Risk factors for low back pain: a Population‐Based longitudinal study. Arthritis care & research, 71(2), 290-299, 2019, https://doi.org/10.1002/acr.23710.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Candra Dwi Setyawan, Arief Wisaksono
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
This journal is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
