Sitting Posture Recognition Systems: Comprehensive Literature Review and Analysis
Source abstract
Abstract
Sitting posture recognition systems have gained significant attention due to their potential applications in various domains, including healthcare, ergonomics, and human-computer interaction. This paper presents a comprehensive literature review and analysis of existing sitting posture recognition systems. Through an extensive examination of relevant research articles and conference papers, we identify and analyze the underlying technologies, methodologies, datasets, performance metrics, and applications associated with these systems. The review encompasses both traditional methods, such as vision-based approaches and sensor-based techniques, as well as emerging technologies such as machine learning and deep learning algorithms. Additionally, we examine the challenges, constraints, and future trends in the field of sitting posture recognition systems. Researchers, practitioners, and policymakers who want to comprehend the most recent developments and latest trends in sitting posture recognition technology will find great value in this study.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ergonomics and Musculoskeletal Disorders
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait
References (100+)
Show source-provided references
1. Biddle, S., and Mutrie, N. (2007). Psychology of Physical Activity: Determinants, Well-Being and Interventions, Routledge.10.4324/9780203019320 ↗
2. The effect of smartphone usage time on posture and respiratory function10.1589/jpts.28.186 ↗
3. Prevalence and associated factors related to arm, neck and shoulder complaints in a selected sample of computer office workers10.21608/EPX.2018.22041 ↗
4. Sitting time and risk of cardiovascular disease and diabetes: A systematic review and meta-analysis10.1016/j.amepre.2019.04.015 ↗
5. World Health Organization (2019). Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World, World Health Organization.
6. International Labour Organization (ILO) (2021, January 14–16). Teleworking arrangements during the COVID-19 crisis and beyond. Proceedings of the 2nd Employment Working Group Meeting under the 2021 Italian Presidency of the G20, Online.
7. Australian Bureau of Statistics (2018). (2017–2018). National Health Survey: First Results, Australian Bureau of Statistics.
8. Church, T.S., Thomas, D.M., Tudor-Locke, C., Katzmarzyk, P.T., Earnest, C.P., Rodarte, R.Q., Martin, C.K., Blair, S.N., and Bouchard, C. (2011). Trends over 5 decades in US occupation-related physical activity and their associations with obesity. PLoS ONE, 6.10.1371/journal.pone.0019657 ↗
9. (2000). Ergonomics: Evaluation of Static Working Postures (Standard No. ISO 11226: 2000 (E)).
10. Effects of Different Sitting Postures on Back Shape and Hip Pressure
11. Gupta, M., Sharma, S., Bhatia, M., and Gupta, N. (2024). Similarity index retrieval for school kids’ sitting posture identification. Predictive Data Modelling for Biomedical Data and Imaging, River Publishers.10.1201/9781003516859-11 ↗
12. Prevalence of chronic pain and high-impact chronic pain among adults—United States, 201610.15585/mmwr.mm6736a2 ↗
13. Low back symptoms among hospital nurses, associations to individual factors and pain in multiple body regions10.1016/j.ergon.2009.11.004 ↗
14. Knowledge, Attitude, and Practice of Pediculus Capitis Prevention and Control and Their Predictors among Schoolchildren in Woreta Town, Northwest Ethiopia, 2018: A School-Based Cross-Sectional Study10.1155/2020/3619494 ↗
15. A call to action for musculoskeletal research funding: The growing economic and disease burden of musculoskeletal conditions in the United States is not reflected in musculoskeletal research funding10.2106/JBJS.22.00693 ↗
16. Ordean, M.-N., Oarcea, A., Stan, S.-D., Dumitru, D.-M., Cobîlean, V., and Bîrză, M.-C. (2022). Analysis of Available Solutions for the Improvement of Body Posture in Chairs. Appl. Sci., 12.10.3390/app12136489 ↗
17. Kwanashie, A., Irving, R.W., Manlove, D.F., and Sng, C.T.S. (2015). Profile-based optimal matchings in the student/project allocation problem. Combinatorial Algorithms, Proceedings of the 25th International Workshop, IWOCA 2014, Duluth, MN, USA, 15–17 October 2014, Springer. Revised Selected Papers 25.10.1007/978-3-319-19315-1_19 ↗
18. Sit less and move more for cardiovascular health: Emerging insights and opportunities10.1038/s41569-021-00547-y ↗
19. Breaking up sitting time after stroke (BUST-stroke)10.1177/1747493018801222 ↗
20. Effects of sitting posture and jaw clenching on neck and trunk muscle activities during typing10.1111/joor.13152 ↗
21. Dehcheshmeh, T.F., Majelan, A.S., and Maleki, B. (2023). Correlation between depression and posture (A systematic review). Curr. Psychol.10.1007/s12144-023-04630-0 ↗
22. Kalra, T. (2017). Postures. Holistic Healthcare: Possibilities and Challenges, Routledge.10.1201/9781315366241-3 ↗
23. Active workstations: A literature review on workplace sitting10.1016/j.jbmt.2024.01.001 ↗
24. Asymmetrical change in the pelvis and the spine during cross-legged sitting postures10.1007/s12206-013-0865-5 ↗
25. Real time visualization of asymmetrical sitting posture10.1016/j.procs.2019.08.024 ↗
26. Salsali, M., Sheikhhoseini, R., Sayyadi, P., Hides, J.A., Dadfar, M., and Piri, H. (2023). Association between physical activity and body posture: A systematic review and meta-analysis. BMC Public Health, 23.10.1186/s12889-023-16617-4 ↗
27. Krauter, C., Angerbauer, K., Calepso, A.S., Achberger, A., Mayer, S., and Sedlmair, M. (2024, January 11–16). Sitting Posture Recognition and Feedback: A Literature Review. Proceedings of the CHI Conference on Human Factors in Computing Systems, Honolulu, HI, USA.10.1145/3613904.3642657 ↗
28. Methods for sitting posture evaluation: Static posture and applications10.1111/j.1475-1305.2007.00334.x ↗
29. The effects of an office ergonomics training and chair intervention on worker knowledge, behavior and musculoskeletal risk10.1016/j.apergo.2007.12.009 ↗
30. The impact of ergonomics intervention on psychosocial factors and musculoskeletal symptoms among office workers10.1016/j.ergon.2011.08.007 ↗
31. A replicated field intervention study evaluating the impact of a highly adjustable chair and office ergonomics training on visual symptoms10.1016/j.apergo.2011.09.006 ↗
32. The effectiveness of a training method using self-modeling webcam photos for reducing musculoskeletal risk among office workers using computers10.1016/j.apergo.2011.05.015 ↗
33. Smart office chairs with sensors for detecting sitting positions and sitting habits: A review10.5552/drvind.2022.0002 ↗
34. Odesola, D.F., Kulon, J., Verghese, S., Partlow, A., and Gibson, C. (2024). Smart Sensing Chairs for Sitting Posture Detection, Classification, and Monitoring: A Comprehensive Review. Sensors, 24.10.20944/preprints202403.1695.v1 ↗
35. Knitronix (2024, September 10). Matrix Textile Pressure Sensor Datasheet. Knitronix, Available online: https://www.knitronix.com/datasheet/datasheet_matrix.pdf.
36. Pizarro, F., Villavicencio, P., Yunge, D., Rodríguez, M., Hermosilla, G., and Leiva, A. (2018). Easy-to-build textile pressure sensor. Sensors, 18.10.3390/s18041190 ↗
37. Electronics, I. (2024, September 10). FSR 406 Data Sheet—Sensor Technologies. Available online: www.interlinkelectronics.com.
38. Sadun, A.S., Jalani, J., and Sukor, J.A. (2016). Force Sensing Resistor (FSR): A brief overview and the low-cost sensor for active compliance control. First International Workshop on Pattern Recognition, SPIE.10.1117/12.2242950 ↗
39. Go Tronic (2024, September 10). Datasheet 3134-Micro Load Cell (0–20kg)-CZL635. Available online: https://www.gotronic.fr/pj-460.pdf.
40. Estimation of various sitting postures using a load-cell-driven monitoring system10.1016/j.ergon.2019.102837 ↗
41. Spectra Symbol (2024, September 10). FS-Series-Flex-Sensor. Datasheet, Available online: https://sot.wpengine.com/wp-content/uploads/2014/07/FS-Series-Flex-Sensor.pdf.
42. Resistive flex sensors: A survey10.1088/0964-1726/25/1/013001 ↗
43. Amazon (2024, September 10). ICStation Foil Resistance Strain Gauge 350-ohm BF350-3AA. Available online: https://cdn.sparkfun.com/datasheets/Sensors/ForceFlex/hx711_english.pdf.
44. Lin, Q., Peng, S., Wu, Y., Liu, J., Hu, W., Hassan, M., Seneviratne, A., and Wang, C.H. (2020, January 21–24). E-jacket: Posture detection with loose-fitting garment using a novel strain sensor. Proceedings of the 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Sydney, Australia.10.1109/IPSN48710.2020.00-47 ↗
45. (2024, September 10). DEWESoft, DS-IMU/GYRO–Software User Manual. Available online: https://downloads.dewesoft.com/manuals/dewesoft-ds-imu-ds-gyro-manual-en.pdf.
46. Yin, M., Li, J., and Wang, T. (2024). A Low-Cost Inertial Measurement Unit Motion Capture System for Operation Posture Collection and Recognition. Sensors, 24.10.3390/s24020686 ↗
47. Logitech (2024, September 10). HD Webcam C270. Available online: http://www.logitech.com/en-roeu/product/hd-webcam-c270.
48. Zhao, S., and Su, Y. (2024, January 26–28). Sitting Posture Recognition Based on the Computer’s Camera. Proceedings of the 2024 2nd Asia Conference on Computer Vision, Image Processing and Pattern Recognition, Xiamen, China.10.1145/3663976.3664014 ↗
49. MediWiki (2024, September 18). Hardware_info. Available online: https://openkinect.org/wiki/Hardware_info.
50. The Kinect: A low-cost, high-resolution, short-range 3D camera10.1002/esp.3332 ↗
51. (2024, September 10). Universal Smart Cards, UHF Tag—H47. Datasheet, Available online: https://www.usmartcards.co.uk/index.php?route=product/product/download&pdf=2884&document_id=662.
52. Feng, L., Li, Z., and Liu, C. (2019, January 21–23). Are you sitting right?-sitting posture recognition using RF signals. Proceedings of the 2019 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM), Victoria, BC, Canada.10.1109/PACRIM47961.2019.8985070 ↗
53. Indoware (2024, September 10). Ultrasonic Ranging Module HC—SR04. Datasheet, Available online: https://cdn.sparkfun.com/datasheets/Sensors/Proximity/HCSR04.pdf.
54. Cho, H., Choi, H.-J., Lee, C.-E., and Sir, C.-W. (2019, January 18–21). Sitting posture prediction and correction system using arduino-based chair and deep learning model. Proceedings of the 2019 IEEE 12th Conference on Service-Oriented Computing and Applications (SOCA), Kaohsiung, Taiwan.10.1109/SOCA.2019.00022 ↗
55. Multimodal data-based deep learning model for sitting posture recognition toward office workers’ health promotion10.1016/j.sna.2022.114150 ↗
56. Efficient Sitting Posture Recognition for Wheelchair Users: An Unsupervised Data-Driven Framework10.1109/MIM.2023.10146559 ↗
57. Zhou, F., Zhao, H., and Nie, Z. (2021, January 22–24). Safety helmet detection based on YOLOv5. Proceedings of the 2021 IEEE International Conference on Power Electronics, Computer Applications (ICPECA), Shenyang, China.10.1109/ICPECA51329.2021.9362711 ↗
58. A comparative study on real-time sitting posture monitoring systems using pressure sensors
59. Liang, G., Cao, J., and Liu, X. (2017, January 13–17). Smart cushion: A practical system for fine-grained sitting posture recognition. Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, HI, USA.
60. Lamberti, P., La Mura, M., De Gregorio, M., Tucci, V., and Egiziano, L. (2022, January 7–9). Smart Seat With Real-Time Asymmetrical Sitting Alert. Proceedings of the 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4. 0&IoT), Trento, Italy.10.1109/MetroInd4.0IoT54413.2022.9831582 ↗
61. Muppavram, S., Patel, N., and Nadeem, M. (2018, January 4–6). Posture Alert. Proceedings of the 2018 IEEE Region 10 Symposium, Tensymp 2018, Sydney, Australia.10.1109/TENCONSpring.2018.8692017 ↗
62. Smart-Cover: A real time sitting posture monitoring system10.1016/j.sna.2020.112451 ↗
63. An adaptive approach: Smart traffic congestion control system
64. Ahmad, J., Andersson, H., and Sidén, J. (November, January 29). Sitting posture recognition using screen printed large area pressure sensors. Proceedings of the 2017 IEEE Sensors, Glasgow, UK.10.1109/ICSENS.2017.8233944 ↗
65. A portable sitting posture monitoring system based on a pressure sensor array and machine learning10.1016/j.sna.2021.112900 ↗
66. Shen, Z., Wan, X., Jin, Y., Gao, G., Wang, Q., and Liu, W. (2021). SeatPlus: A Smart Health Chair Supporting Active Sitting Posture Correction. International Conference on Human-Computer Interaction, Springer.10.1007/978-3-030-78224-5_37 ↗
67. Sitting posture recognition using a spiking neural network10.1109/JSEN.2020.3016611 ↗
68. Gelaw, T.A., and Hagos, M.T. (2022). Posture Prediction for Healthy Sitting Using a Smart Chair. Advances of Science and Technology, Proceedings of the 9th EAI International Conference, ICAST 2021, Hybrid. Event, Bahir Dar, Ethiopia, 27–29 August 2021, Springer. Proceedings, Part. I.10.1007/978-3-030-93709-6_26 ↗
69. Bourahmoune, K., and Amagasa, T. (2019, January 10–16). AI-powered Posture Training: Application of Machine Learning in Sitting Posture Recognition Using the LifeChair Smart Cushion. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), Macao, China.10.24963/ijcai.2019/805 ↗
70. Fan, Z., Hu, X., Chen, W.-M., Zhang, D.-W., and Ma, X. (2022). A deep learning based 2-dimensional hip pressure signals analysis method for sitting posture recognition. Biomed. Signal Process Control, 73.10.1016/j.bspc.2021.103432 ↗
71. La Mura, M., De Gregorio, M., Lamberti, P., and Tucci, V. (2023). Iot system for real-time posture asymmetry detection. Sensors, 23.10.3390/s23104830 ↗
72. Wang, Y. (2022, January 7–9). Research and Application of Sitting Posture Correction Design Based on Artificial Intelligence. Proceedings of the 2022 4th International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM), Hamburg, Germany.10.1109/AIAM57466.2022.00178 ↗
73. Tsai, M.-C., Chu, E.T.-H., and Lee, C.-R. (2023). An automated sitting posture recognition system utilizing pressure sensors. Sensors, 23.10.3390/s23135894 ↗
74. FSR-based smart system for detection of wheelchair sitting postures using machine learning algorithms and Techniques10.1155/2022/1901058 ↗
75. Luna-Perejón, F., Montes-Sánchez, J.M., Durán-López, L., Vazquez-Baeza, A., Beasley-Bohórquez, I., and Sevillano-Ramos, J.L. (2021). IoT device for sitting posture classification using artificial neural networks. Electronics, 10.10.3390/electronics10151825 ↗
76. Ma, C., Li, W., Gravina, R., and Fortino, G. (2017). Posture detection based on smart cushion for wheelchair users. Sensors, 17.10.3390/s17040719 ↗
77. Design and modeling of a textile pressure sensor for sitting posture classification10.1109/JSEN.2009.2037330 ↗
78. Roh, J., Park, H., Lee, K.J., Hyeong, J., Kim, S., and Lee, B. (2018). Sitting posture monitoring system based on a low-cost load cell using machine learning. Sensors, 18.10.3390/s18010208 ↗
79. Pereira, L., and da Silva, H.P. (2023). A novel smart chair system for posture classification and invisible ECG monitoring. Sensors, 23.10.3390/s23020719 ↗
80. A smart chair sitting posture recognition system using flex sensors and FPGA implemented artificial neural network10.1109/JSEN.2020.2980207 ↗
81. A note on structuring employability skills for accounting students
82. Providing a cushion for wireless healthcare application development10.1109/MPOT.2009.934698 ↗
83. Ishac, K., and Suzuki, K. (2018). Lifechair: A conductive fabric sensor-based smart cushion for actively shaping sitting posture. Sensors, 18.10.3390/s18072261 ↗
84. Tang, H.-Y., Tan, S.-H., Su, T.-Y., Chiang, C.-J., and Chen, H.-H. (2021). Upper body posture recognition using inertial sensors and recurrent neural networks. Appl. Sci., 11.10.3390/app112412101 ↗
85. Qian, Z., Bowden, A.E., Zhang, D., Wan, J., Liu, W., Li, X., Baradoy, D., and Fullwood, D.T. (2018). Inverse piezoresistive nanocomposite sensors for identifying human sitting posture. Sensors, 18.10.3390/s18061745 ↗
86. Najafi, T.A., Abramo, A., Kyamakya, K., and Affanni, A. (2022). Development of a smart chair sensors system and classification of sitting postures with deep learning algorithms. Sensors, 22.10.3390/s22155585 ↗
87. A privacy-preserving and unobtrusive sitting posture recognition system via pressure array sensor and infrared array sensor for office workers10.1016/j.aei.2022.101690 ↗
88. Katayama, H., Mizomoto, T., Rizk, H., and Yamaguchi, H. (2022, January 21–25). You work we care: Sitting posture assessment based on point cloud data. Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Pisa, Italy.10.1109/PerComWorkshops53856.2022.9767292 ↗
89. Ye, J.F. (2020, January 7–8). Design and implementation of sitting posture monitoring system. Proceedings of the 2020 International Conference on Robots & Intelligent System (ICRIS), Sanya, China.10.1109/ICRIS52159.2020.00072 ↗
90. Cai, W., Zhao, D., Zhang, M., Xu, Y., and Li, Z. (2021). Improved Self-Organizing Map-Based Unsupervised Learning Algorithm for Sitting Posture Recognition System. Sensors, 21.10.3390/s21186246 ↗
91. Martínez-Estrada, M., Vuohijoki, T., Poberznik, A., Shaikh, A., Virkki, J., Gil, I., and Fernández-García, R. (2023). A Smart Chair to Monitor Sitting Posture by Capacitive Textile Sensors. Materials, 16.10.3390/ma16134838 ↗
92. Bourahmoune, K., Ishac, K., and Amagasa, T. (2022). Intelligent posture training: Machine-learning-powered human sitting posture recognition based on a pressure-sensing iot cushion. Sensors, 22.10.3390/s22145337 ↗
93. Huang, M., Huang, H., Chen, I., Chen, K., and Wang, A. (2021). Artificial intelligence aided course scheduling system. Journal of Physics: Conference Series, Proceedings of the International Conference on Communications, Information System and Software Engineering (CISSE 2020), Guangzhou, China, 18–20 December 2020, IOP Publishing.
94. Wang, H., Zhao, J., Li, J., and Wang, K. (2019, January 11–12). The sitting posture monitoring method based on notch sensor. Proceedings of the 2019 IEEE International Conference on Industrial Internet (ICII), Orlando, FL, USA.10.1109/ICII.2019.00058 ↗
95. Leone, A., Rescio, G., Caroppo, A., Siciliano, P., and Manni, A. (2023). Human postures recognition by accelerometer sensor and ML architecture integrated in embedded platforms: Benchmarking and performance evaluation. Sensors, 23.10.3390/s23021039 ↗
96. Machine Learning Algorithms Application For The Proposed Sitting Posture Monitoring System10.1016/j.procs.2022.07.031 ↗
97. Wan, Q., Zhao, H., Li, J., and Xu, P. (2021). Hip positioning and sitting posture recognition based on human sitting pressure image. Sensors, 21.10.3390/s21020426 ↗
98. Intelligent Active Correction Seat Based on Neural Network Sitting Posture Recognition
99. Otoda, Y., Mizumoto, T., Arakawa, Y., Nakajima, C., Kohana, M., Uenishi, M., and Yasumoto, K. (2018, January 12–14). Census: Continuous posture sensing chair for office workers. Proceedings of the 2018 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA.10.1109/ICCE.2018.8326275 ↗
100. Gupta, R., Gupta, A., and Aswal, R. (2021, January 19–20). Detection of poor posture using wearable sensors and unsupervised learning. Proceedings of the 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India.10.1109/ICACCS51430.2021.9441893 ↗