Real-time Sitting Correction Using Arduino-Based Ultrasonic Sensor at the Workplace
DOI:
https://doi.org/10.51173/jt.v6i4.1823Keywords:
Accuracy, DC Motor, Microcontroller, Ultrasonic Sensor, Smart ChairAbstract
People who work from home or in offices typically sit at a computer for most of their workday, often sitting with bad posture. Therefore, the decision was made to develop chairs to find a solution for the medical problems that arise from sitting for long periods during work. The intended audience for the chair includes office workers, students, and homemakers. Gamers who spend a lot of time sitting in their chairs could benefit from the technology. This research aims to solve the problem of unhealthy sitting. The hardware configuration includes a DC motor, power supply, microcontroller, ultrasonic sensor, buzzer, and a chair. The software configuration uses Arduino software to evaluate the system's overall accuracy. Four categorization models are used: true positive, false positive, true negative, and false negative. The system development process has been exceptionally successful, achieving a total accuracy of approximately 97.434%. For future work, it is expected to increase the accuracy of the system with an IR sensor and speaker to alert the user.
Downloads
References
A. Arrogi, F. Boen, and J. Seghers, "Validation of a smart chair and corresponding smartphone app as an objective measure of desk-based sitting," Journal of occupational health, vol. 61, no. 1, pp. 121-127, January. 2019, https://doi.org/10.1002/1348-9585.12033.
T. Aminosharieh Najafi, A. Abramo, K. Kyamakya, and A. Affanni, "Development of a Smart Chair Sensors System and Classification of Sitting Postures with Deep Learning Algorithms," Sensors, vol. 22, no.15, p. 5585, July, 2022, https://doi.org/10.3390/s22155585.
J. Roh, J. Hyeong, and S. Kim, "Estimation of various sitting postures using a load-cell-driven monitoring system," International Journal of Industrial Ergonomics, vol. 74, p. 102837, October, 2019, https://doi.org/10.1016/j.ergon.2019.102837.
J. Liu, "Development of an Intelligent Office Chair by Combining Vibrotactile and Visual Feedbacks," in Journal of Physics: Conference Series, 2021, Sanya, China, 2021, vol. 1877, p. 012015, DOI 10.1088/1742-6596/1877/1/012015.
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, December, 2019, https://doi.org/10.1016/j.ijhcs.2019.08.003.
T. Bodin, K. Berglund, and M. Forsman, "Activity in neck-shoulder and lower arm muscles during computer and smartphone work," International Journal of Industrial Ergonomics, vol. 74, p. 102870, November, 2019, https://doi.org/10.1016/j.ergon.2019.102870.
Y. Liang, Y. Li, H. Yin, and L. Yin, "Intelligent Active Correction Seat Based on Neural Network Sitting Posture Recognition," Journal of Artificial Intelligence Practice, vol. 5, no. 2, pp. 34-41, August, 2022, https://doi.org/10.23977/jaip.2022.050205.
S. Matuska, M. Paralic, and R. Hudec, "A smart system for sitting posture detection based on force sensors and mobile application,” Mobile Information Systems, vol. 2020, November, 2020, https://doi.org/10.1155/2020/6625797.
L. Feng, Z. Li, C. Liu, X. Chen, X. Yin, and D. Fang, "SitR: sitting posture recognition using RF signals," IEEE Internet of Things Journal, vol. 7, no.12, pp. 11492-11504, August, 2020, https://doi.org/10.1109/JIOT.2020.3019280.
Y. Arakawa, "Sensing and changing human behavior for workplace wellness," Journal of information processing, vol. 27, pp. 614-623, January, 2019, https://doi.org/10.2197/ipsjjip.27.614 .
A. C. Kumar and V. Sridhar, "Design and Analytics of Smart Posture Monitoring System," in Journal of Physics: Conference Series, Chennai, India, 2021, p. 012048, DOI 10.1088/1742-6596/2115/1/012048.
W. Min, H. Cui, Q. Han, and F. Zou, "A scene recognition and semantic analysis approach to unhealthy sitting posture detection during screen-reading," Sensors, vol. 18, no. 9, p. 3119, September, 2018, https://doi.org/10.3390/s18093119.
H. Jeong and W. Park, "Developing and evaluating a mixed sensor smart chair system for real-time posture classification: Combining pressure and distance sensors," IEEE Journal of Biomedical and Health Informatics, vol. 25, no. 5, pp. 1805-1813, October, 2020, https://doi.org/10.1109/JBHI.2020.3030096.
B. Kundaliya, S. Patel, J. Patel, P. Barot, and S. Hadia, "An IoT and Cloud Enabled Smart Chair for Detection and Notification of Wrong Seating Posture," research square, vol. 1, Aug., 2022, https://doi.org/10.21203/rs.3.rs-1999906/v1.
S. Channak, T. Klinsophon, and P. Janwantanakul, "The effects of chair intervention on lower back pain, discomfort and trunk muscle activation in office workers: a systematic review," International Journal of Occupational Safety and Ergonomics, vol. 28, no. 3, pp. 1722-1731, Jun, 2022, https://doi.org/10.1080/10803548.2021.1928379.
G. Flutur, B. Movileanu, L. Károly, I. Danci, D. Cosovanu, and O. P. Stan, "Smart Chair System for Posture Correction," in 2019 22nd Euromicro Conference on Digital System Design (DSD), Kallithea, Greece, 2019, pp. 436-441, https://doi.org/10.1109/DSD.2019.00069.
M. Li, Z. Jiang, Y. Liu, S. Chen, M. Wozniak, R. Scherer, et al., "Sitsen: Passive sitting posture sensing based on wireless devices," International Journal of Distributed Sensor Networks, vol. 17, no, 7, p. 15501477211024846, July, 2021, https://doi.org/10.1177/15501477211024846.
M. Usman, Z. Noor, I. Farooq, A. Arsalan, M. Ehatisham-ul-Haq, and A. Raheel, "A smart chair design for recognizing human-object interactions using pressure sensors," in 2020 IEEE 23rd International Multitopic Conference (INMIC), Bahawalpur, Pakistan, 2020, pp. 1-6, https://doi.org/10.1109/INMIC50486.2020.9318102.
L. Feng, Z. Li, and C. Liu, "Are you sitting right?-sitting posture recognition using RF signals," in 2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM), Victoria, BC, Canada, 2019, pp. 1-6, https://doi.org/10.1109/PACRIM47961.2019.8985070.
Q. Hu, X. Tang, and W. Tang, "A smart chair sitting posture recognition system using flex sensors and FPGA implemented artificial neural network," IEEE Sensors Journal, vol. 20, no. 14, pp. 8007-8016, July, 2020, https://doi.org/10.1109/JSEN.2020.2980207.
A. R. Kett, F. Sichting, and T. L. Milani, "The effect of sitting posture and postural activity on low back muscle stiffness," Biomechanics, vol. 1, pp. 214-224, 2021, https://doi.org/10.3390/biomechanics1020018.
D. Sikligar, L. Nguessan, D. Pham, J. Grupper, A. Beaudette, A. Ling, et al., "Design of a Textile Sensor Embedded Shirt for Posture Monitoring," in Frontiers in Biomedical Devices, 2022, p. V001T04A009, https://doi.org/10.1115/DMD2022-1063.
K. N. Devi, J. Anand, R. Kothai, J. M. A. Krishna, and R. Muthurampandian, "Sensor based posture detection system," Materials Today: Proceedings, vol. 55, pp. 359-364, 2022, https://doi.org/10.1016/j.matpr.2021.09.556.
Ibitoye, M. O., Y. Ahmed, T. M. Ajibola, and I. O., Oladejo. “Posture Monitoring Device for Abnormal Spine Musculoskeletal Detection Using Flex Sensor”. ELEKTRIKA- Journal of Electrical Engineering, vol. 21, no. 3, pp. 47-51, 2022, https://doi.org/10.11113/elektrika.v21n3.379.
V. K. Sinha, K. K. Patro, P. Pławiak, and A. J. Prakash, "Smartphone-based human sitting behaviors recognition using inertial sensor," Sensors, vol. 21, p. 6652, 2021, https://doi.org/10.3390/s21196652.
M.-C. Tsai, E. T.-H. Chu, and C.-R. Lee, "An Automated Sitting Posture Recognition System Utilizing Pressure Sensors," Sensors, vol. 23, p. 5894, 2023, https://doi.org/10.3390/s23135894.
Lead-Acid-Battery. (2023, June. 11). Lead-Acid-Battery [Online]. Available: https://www.amazon.sa/-/en/12V-7AH-Lead-Acid-Battery/dp/B081TRZMV4.
Power-Supply. (2023, June. 11). Power-Supply [Online]. Available: https://www.amazon.in/Invento-8944130045352-Power-Supply-Strip/dp/B01LYBXXES.
Microcontroller. (2023, June. 11). Microcontroller [Online]. Available: https://components101.com/microcontrollers/pic12f675-pinout-datasheet.
DC motor. (2023, June. 11). DC motor [Online]. Available: https://www.ebay.com/p/7052726596.
Ultrasonic-Sensor-Module-HC-SR-04. (2023, June. 11). Ultrasonic-Sensor-Module-HC-SR-04 [Online]. Available: https://www.amazon.in/Ultrasonic-Sensor-Module-HC-SR-04-Robokart/dp/B00ZNB01HI.
Arduino. Arduino software. (2023, June. 11). Arduino software [Online]. Available: https://store.arduino.cc/usa/arduino-uno-rev3.
H. F. Jameel, M. F. Mahmood, and S. M. Yaseen, "Design and Implementation of a Peristaltic Pump Based on an Air Bubble Sensor," International Journal Bioautomation, vol. 26, no. 4, p. 361, December, 2022, https://doi.org/10.7546/ijba.2022.26.4.000866.
G. Kucukyildiz, H. Ocak, S. Karakaya, and O. Sayli, "Design and implementation of a multi sensor based brain computer interface for a robotic wheelchair," Journal of Intelligent & Robotic Systems, vol. 87, pp. 247-263, January, 2017, https://doi.org/10.1007/s10846-017-0477-x.
H. F. Jameel, S. L. Mohammed, and S. K. Gharghan, "Electroencephalograph-Based Wheelchair Controlling System for the People with Motor Disability Using Advanced BrainWear," in 2019 12th International Conference on Developments in eSystems Engineering (DeSE), Kazan, Russia, 2019, pp. 843-848.
C. Ma, W. Li, R. Gravina, and G. Fortino, "Posture detection based on smart cushion for wheelchair users," Sensors, vol. 17, no. 4, p. 719, 2017, https://doi.org/10.3390/s17040719.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Huda Farooq Jameel
This work is licensed under a Creative Commons Attribution 4.0 International License.
