SleepCon: Sleeping Posture Recognition Model using Convolutional Neural Network

Jesmeen M. Z. H., Thangavel Bhuvaneswari, Abdul Hadi Mazbah, Yeo Boon Chin, Lim Heng Siong, Nor Hidayati Abdul Aziz

Abstract


Recognition of sleep patterns and posture has sparked interest in various clinical applications. Sleep postures can be monitored autonomously and constantly to provide useful information for decreasing health risks. Existing systems mostly use images to train the model to learn based on many sensors. For example, a camera, pressure sensor, and electrocardiogram. In this study, a model (named as SleepCon) was designed using deep learning, which will have the capability to train with any threshold image obtained from any sensor. This paper presented a system where data was obtained from a camera installed on the top of a mattress. The camera located the movement of the body posture on the mattress while the subject was lying down on the mattress. In doing so, CNN and other pre-processed steps took place to collect data and then analyze the data to recognize different sleep postures. This model was stored for use in real-time applications. The system can recognize the three major postures, i.e., left, right, and supine. A real-time application is also developed and operates the stored SleepCon model through an accompanying desktop application for detecting the posture live. The accuracy of classification was greater than 90%, while the actual application accuracy was 100% after carrying out the experiment on the SleepCon model.

 

Doi: 10.28991/ESJ-2023-07-01-04

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Keywords


Sleeping Posture Recognition; Convolutional Neural Network (CNN); Recognition Model; Classification.

References


Scholkmann, F., Boss, J., & Wolf, M. (2012). An efficient algorithm for automatic peak detection in noisy periodic and quasi-periodic signals. Algorithms, 5(4), 588–603. doi:10.3390/a5040588.

Lee, W. H., & Ko, M. S. (2017). Effect of sleep posture on neck muscle activity. Journal of Physical Therapy Science, 29(6), 1021–1024. doi:10.1589/jpts.29.1021.

Gordon, S., Grimmer, K., & Trott, P. (2007). Sleep Position, Age, Gender, Sleep Quality and Waking Cervico-Thoracic Symptoms. Internet Journal of Allied Health Sciences and Practice, 5(1). doi:10.46743/1540-580x/2007.1134.

Nojiri, A., Okumura, C., & Ito, Y. (2014). Sleep Posture Affects Sleep Parameters Differently in Young and Senior Japanese as Assessed by Actigraphy. Health, 06(21), 2934–2944. doi:10.4236/health.2014.621332.

Ramar, K., Malhotra, R. K., Carden, K. A., Martin, J. L., Abbasi-Feinberg, F., Aurora, R. N., Kapur, V. K., Olson, E. J., Rosen, C. L., Rowley, J. A., Shelgikar, A. V., & Trotti, L. M. (2021). Sleep is essential to health: An American Academy of Sleep Medicine position statement. Journal of Clinical Sleep Medicine, 17(10), 2115–2119. doi:10.5664/jcsm.9476.

Ong, H. S., Lim, C. S., Constance Png, A. L., Kong, J. W., & Peh, A. L. H. (2021). Chronobiology and the case for sleep health interventions in the community. Singapore Medical Journal, 62(5), 220–224. doi:10.11622/smedj.2021058.

Pham, T., Lin, C. K., Leek, D., Chandrashekhar, R., & Annaswamy, T. M. (2020). Obstructive sleep Apnea’s association with the cervical spine abnormalities, posture, and pain: a systematic review. Sleep Medicine, 75, 468–476. doi:10.1016/j.sleep.2020.09.008.

Estivalet, K. M., Thomas, C., Ponte, A. S., Pinto, D. da S. P., & Delboni, M. C. C. (2020). Interference of the Carpal Tunnel syndrome symptoms on occupational performance. Brazilian Journal of Pain, 3(3), 234–238. doi:10.5935/2595-0118.20200052.

Bernal Monroy, E., Polo Rodríguez, A., Espinilla Estevez, M., & Medina Quero, J. (2020). Fuzzy monitoring of in-bed postural changes for the prevention of pressure ulcers using inertial sensors attached to clothing. Journal of Biomedical Informatics, 107, 103476. doi:10.1016/j.jbi.2020.103476.

Wu, L., Shi, P. L., Tao, S. S., Tao, J. H., & Wu, G. C. (2021). Decreased sleep quality in patients with systemic lupus erythematosus: a meta-analysis. Clinical Rheumatology, 40(3), 913–922. doi:10.1007/s10067-020-05300-3.

Lin, F., Zhuang, Y., Song, C., Wang, A., Li, Y., Gu, C., Li, C., & Xu, W. (2017). SleepSense: A Noncontact and Cost-Effective Sleep Monitoring System. IEEE Transactions on Biomedical Circuits and Systems, 11(1), 189–202. doi:10.1109/TBCAS.2016.2541680.

Liu, J. H., Ma, Q.H., Sun, H. P., Xu, Y., & Pan, C. W. (2021). Depressive symptom as a mediator of the influence of self-reported sleep quality on falls: a mediation analysis. Aging & Mental Health, 25(4), 728–733. doi:10.1080/13607863.2020.1711860.

Davoodnia, V., & Etemad, A. (2019). Identity and Posture Recognition in Smart Beds with Deep Multitask Learning. 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). doi:10.1109/smc.2019.8914459.

Tang, K., Kumar, A., Nadeem, M., & Maaz, I. (2021). CNN-Based Smart Sleep Posture Recognition System. IoT, 2(1), 119–139. doi:10.3390/iot2010007.

Liu, J., Chen, X., Chen, S., Liu, X., Wang, Y., & Chen, L. (2019). TagSheet: Sleeping Posture Recognition with an Unobtrusive Passive Tag Matrix. IEEE INFOCOM Conference on Computer Communications. doi:10.1109/infocom.2019.8737599.

Grimm, T., Martinez, M., Benz, A., & Stiefelhagen, R. (2016). Sleep position classification from a depth camera using Bed Aligned Maps. 2016 23rd International Conference on Pattern Recognition (ICPR). doi:10.1109/icpr.2016.7899653.

Martinez, M., Schauerte, B., Stiefelhagen, R. (2013). “BAM!” Depth-Based Body Analysis in Critical Care. Computer Analysis of Images and Patterns. CAIP 2013, Lecture Notes in Computer Science, 8047, Springer, Berlin, Germany. doi:10.1007/978-3-642-40261-6_56.

Huang, Y. F., Hsu, Y. H., Chang, C. C., Liu, S. H., Wei, C. C., Yao, T. Y., & Lin, C. B. (2017). An Improved Sleep Posture Recognition Based on Force Sensing Resistors. Intelligent Information and Database Systems. ACIIDS 2017, Lecture Notes in Computer Science, 10192. Springer, Cham, Switzerland. doi:10.1007/978-3-319-54430-4_31.

Liu, Z., Wang, X., SU, M., & Lu, K. (2019). A Method to Recognize Sleeping Position Using an CNN Model Based on Human Body Pressure Image. 2019 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS). doi:10.1109/icpics47731.2019.8942566.

Hu, Q., Tang, X., & Tang, W. (2021). A Real-Time Patient-Specific Sleeping Posture Recognition System Using Pressure Sensitive Conductive Sheet and Transfer Learning. IEEE Sensors Journal, 21(5), 6869–6879. doi:10.1109/JSEN.2020.3043416.

Matar, G., Lina, J. M., & Kaddoum, G. (2020). Artificial Neural Network for in-Bed Posture Classification Using Bed-Sheet Pressure Sensors. IEEE Journal of Biomedical and Health Informatics, 24(1), 101–110. doi:10.1109/JBHI.2019.2899070.

Matar, G., Lina, J.-M., Carrier, J., Riley, A., & Kaddoum, G. (2016). Internet of Things in sleep monitoring: An application for posture recognition using supervised learning. 2016 IEEE 18th International Conference on E-Health Networking, Applications and Services (Healthcom). doi:10.1109/healthcom.2016.7749469.

Pouyan, M. B., Birjandtalab, J., Heydarzadeh, M., Nourani, M., & Ostadabbas, S. (2017). A pressure map dataset for posture and subject analytics. 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI). doi:10.1109/bhi.2017.7897206.

Mohammadi, S. M., Enshaeifar, S., Hilton, A., Dijk, D. J., & Wells, K. (2021). Transfer Learning for Clinical Sleep Pose Detection Using a Single 2D IR Camera. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 290–299. doi:10.1109/TNSRE.2020.3048121.

Byeon, Y. H., Lee, J. Y., Kim, D. H., & Kwak, K. C. (2020). Posture recognition using ensemble deep models under various home environments. Applied Sciences (Switzerland), 10(4). doi:10.3390/app10041287.

Enokibori, Y., & Mase, K. (2018). Data augmentation to build high performance DNN for in-bed posture classification. Journal of Information Processing, 26, 718–727. doi:10.2197/ipsjjip.26.718.


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DOI: 10.28991/ESJ-2023-07-01-04

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Copyright (c) 2022 Jesmeen Mohd Zebaral Hoque, Dr. Thangavel Bhuvaneswari, Abdul Hadi Mazbah, Dr. Yeo Boon Chin, Prof.Dr. Lim Heng Siong, Dr.Nor hidayati Binti Abdul Aziz