Abstract
Most of the research performed in the area of movement analysis of sleeping subjects has been targeted at sleep stage classification or monitoring of sleep disorders. In this paper, we present an innovative approach and show how movement analysis of sleeping subjects can be used to enable new lifestyle related applications. The first application we propose shows how a sleeping subject’s movement pattern can be used to build an intelligent wake-up light system. The second application targets an intelligent baby monitor that informs parents about changes of their baby’s pose in its sleep. For the two proposed systems, we present design considerations and initial results showing the potential of camera-based movement analysis in sleep related applications outside the common interest.
Similar content being viewed by others
References
Åkerstedt T, Gillberg M (1990) Subjective and objective sleepiness in the active individual. Int J Neurosci 52:29–37
Allen RP, Hening WA (2009) Actigraph assessment of periodic leg movements and restless legs syndrome. In: Restless Legs Syndrome, W.B. Saunders, Philadelphia, pp 142–149
Ancoli-Israel S et al (2003) The role of actigraphy in the study of sleep and circadian rhythms. Sleep 26(3):342–392
Ando K, Kripke DF (1996) Light attenuation by the human eyelid. Biol Psychiatry 39(1):22–25
Aubert X et al (2008) Estimation of vital signs in bed from a single unobtrusive mechanical sensor: Algorithms and real-life evaluation. In: 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. EMBS 2008
Berson DM, Dunn FA, Takao M (2002) Phototransduction by retinal ganglion cells that set the circadian clock. Science 295(5557):1070–1073
Bradski G (2000) The OpenCV Library. Dr. Dobb’s Journal of Software Tools
Brainard GC, Hanifin JP, Greeson JM, Byrne B, Glickman G, Gerner E, Rollag MD, Brainard GC (2001) Action spectrum for melatonin regulation in humans: evidence for a novel circadian photoreceptor. J Neurosci 21(16):6405–6412
Cagnacci A, Elliott JA, Yen SS (1992) Melatonin: a major regulator of the circadian rhythm of core temperature in humans. J Clin Endocrinol Metab 75(2):447–452
Cuppens K, Lagae L et al (2010) Automatic video detection of body movement during sleep based on optical flow in pediatric patients with epilepsy. Med Biol Eng Comput 48(9):923–931
Etzioni T, Pillar G (2007) Movement disorders in sleep. Harefuah 146(7):544–548
Fairchild MD (2005) Color Appearance Models, 2nd edn. Wiley-IS&T Series in Imaging Science and Technology, Chichester
Ferrara M, De Gennaro L (2000) The sleep inertia phenomenon during the sleep-wake transition: theoretical and operational issues. Aviat Space Environ Med 71(8):843–848
Franklin GF, Powell DJ, Emami-Naeini A (2001) Feedback Control of Dynamic Systems, 4th edn. Prentice Hall PTR, Upper Saddle River
Gardner R, Grossman W (1976) Normal motor patterns in sleep in man. Adv Sleep Res 2:67–107
Gimenez MC, Hessels M, van de Werken M, de Vries B, Beersma DG, Gordijn MC (2010) Effects of artificial dawn on subjective ratings of sleep inertia and dim light melatonin onset. Chronobiol Int 27(6):1219–1241
Gori S, Ficca G et al (2004) Body movements during night sleep in healthy elderly subjects and their relationships with sleep stages. Brain Res Bull 63(5):393–397
Harada T et al (2000) Sensor pillow system: monitoring respiration and body movement in sleep. In: Proceedings of 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems 1, pp 351–356
Heinrich A, Aubert X, de Haan G (2013) Body movement analysis during sleep based on video motion estimation. In: e-Health Networking Applications and Services (Healthcom), 2013. 15th IEEE International Conference on (2013)
Heinrich A, Geng D, Znamenskiy D, Vink J, de Haan G (2014) Robust and sensitive video motion detection for sleep analysis. In: IEEE Journal of Biomedical and Health Informatics (J-BHI) 18(3)
Huang C, Ai H, Li Y, Lao S (2007) High-performance rotation invariant multiview face detection. Pattern Anal Mach Intell IEEE Trans 29(4):671–686
iwaku: iwaku wake-up light (2014) http://www.iwaku.com/product/item13. [Online; Accessed 20 Mar 2014]
Jeung A, Mostafavi H, Riaziat M et al (2008) Method and system for monitoring breathing activity of a subject. Patent US 7403638:B2
Lehrl S, Gerstmeyer K, Jacob JH, Frieling H, Henkel AW, Meyrer R, Wiltfang J, Kornhuber J, Bleich S (2007) Blue light improves cognitive performance. J Neural Transm 114(4):457–460
Liao W, Kuo J, Yang C, Chen IY (2010) iWakeUp: a video-based alarm clock for smart bedrooms. J Chin Inst Eng 33(5):661–668
Liao WH, Kuo J (2013) Sleep monitoring system in real bedroom environment using texture-based background modeling approaches. J Ambient Intell Humaniz Comput 4(1):57–66
Liao WH, Yang CM (2008) Video-based activity and movement pattern analysis in overnight sleep studies. In: Int’l Conf. on Pattern Recognition, pp 1–4
Mansor M, Rejab M, Jamil SF, Jamil AF, Junoh A, Ahmad J (2012) Fast infant pain detection method. In: 2012 International Conference on Computer and Communication Engineering (ICCCE), pp 918–921
Muzet A, Naitoh P et al (1972) Body movements during sleep as a predictor of state change. Psychon Sci 29:7–10
Ou LC, Luo MR, Woodcock A, Wright A (2004) A study of colour emotion and colour preference. part i: Colour emotions for single colours. Color Res Appl 29(3):232–240
Parmet S, Burke A, Golub R (2012) Sudden infant death syndrome. JAMA 307(16):1766
Philips: Philips HF3490 Wake-up Light (2014) http://www.philips.co.uk/c-p/HF3490_01 [Online; Accessed 20 Mar 2014]
Tassi P, Muzet A (2000) Sleep inertia. Sleep Med Rev 4(4):341–353
Van De Werken M, Gimenez MC, De Vries B, Beersma DG, Van Someren EJ, Gordijn MC (2010) Effects of artificial dawn on sleep inertia, skin temperature, and the awakening cortisol response. J Sleep Res 19(3):425–435
Viola P, Jones MJ (2004) Robust real-time face detection. Int J Comput Vis 57(2):137–154
Wang CW, Ahmed A, Hunter A (2006) Vision analysis in detecting abnormal breathing activity in application to diagnosis of obstructive sleep apnoea. In: Engineering in Medicine and Biology Society (EMBS), 2006. 28th Annual International Conference of the IEEE, pp 4469–4473
Wang CW, Hunter A, Gravill N, Matusiewicz S (2010) Real time pose recognition of covered human for diagnosis of sleep apnoea. Comput Med Imaging Graph 34(6):523–533
Wilde-Frenz J, Schulz H (1983) Rate and distribution of body movements during sleep in humans. Percept Mot Skills 56:275–283
Wyszecki G, Stiles WS (2000) Color Science: Concepts and Methods, Quantitative Data and Formulae (Wiley Series in Pure and Applied Optics), 2nd edn. Wiley-Interscience
Acknowledgments
The authors would like to thank Jingzhou Luo for his contributions to this work.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Heinrich, A., Jeanne, V. & Zhao, X. Lifestyle applications from sleep research. J Ambient Intell Human Comput 5, 829–842 (2014). https://doi.org/10.1007/s12652-014-0233-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-014-0233-z