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Sensor Information Processing for Wearable IoT Devices

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Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 174))

Abstract

Sensing technology is one of the core enablers of IoT and the improvement in sensing technology has lead to the proliferation of small form-factor, cost-effective and accurate sensors for wide variety of wearable applications. With wearable devices receiving widespread acceptance, their requirements are becoming more demanding, with the focus shifting from simple monitoring to context aware intelligent devices. This chapter presents a comprehensive description of the technical opportunities and challenges in the design of sensor information processing systems for wearables. A systematic survey of the state of the art architectures for sensor fusion for different application classes of wearable’s is presented. A discussion on design considerations for architecting sensor processing systems, including hardware, networking protocols, and algorithms at the edge, cloud level is provided. The chapter is concluded with a discussion on innovation directions in smart sensing and information processing in wearable devices.

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References

  1. Sensoriafitness.com: Sensoria Fitness. [online] Available at: http://www.sensoriafitness.com/smartsocks/ (2019). Accessed 25 Jul 2019

  2. Abiresearch.com: Wearable Device Market Share and Forecasts. [online] Available at: https://www.abiresearch.com/market-research/product/1019580-wearable-device-market-share-and-forecasts/ (2019). Accessed 25 Jul 2019

  3. Insight, C., Portela, R., Wood, B.; Optimistic Outlook for Wearables—CCS Insight. [online] CCS Insight. Available at: https://www.ccsinsight.com/press/company-news/optimistic-outlook-for-wearables/ (2019). Accessed 25 Jul 2019

  4. Cognolato, M., Atzori, M., Müller, H.: Head-mounted eye gaze tracking devices: an overview of modern devices and recent advances. J. Rehabil. Assist. Technol. Eng., 5 (2018)

    Article  Google Scholar 

  5. Park, J., Kim, J., Kim, S., Cheong, W.H., Jang, J., Park, Y.G., Ung, Jang: Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays. Appl. Sci. Eng. 4(1), 1–12 (2018)

    Google Scholar 

  6. Atheer: The Standard for Enterprise Augmented Reality (AR)|Atheer. [online] Available at: https://atheerair.com/ (2019). Accessed 25 Jul 2019

  7. Hänsel, K., Katevas K., Orgs, G., Richardson, D.C., Alomainy, A., Haddadi, H.: The potential of wearable technology for monitoring social interactions based on interpersonal synchrony. In: Proceedings of the ACM Conference on Wearable Systems and Applications (WearSys) (2018)

    Google Scholar 

  8. Bonato, P.: Advances in wearable technology and applications in physical medicine and rehabilitation. J. Neuroeng. Rehabil. 2(1) (2005)

    Google Scholar 

  9. Aliverti, A.: Wearable technology: role in respiratory health and disease. Breathe 13(2), 27–36 (2017)

    Article  Google Scholar 

  10. Shilkrot, R., Huber, J., Urgen, J., Nanayakkara, S., Maes, P.: Digital digits : a comprehensive survey of finger. ACM Comput. Surv. 48(2) (2015)

    Article  Google Scholar 

  11. Xenxo: Xenxo—The World’s Smartest Ring that you have been Waiting for. [online] Available at: https://www.xenxo.pro/ (2019). Accessed 25 Jul 2019

  12. Yatani, K., Truong, K.N.: BodyScope: a wearable acoustic sensor for activity recognition. In: The Proceedings of ACM Conference on Ubiquitous Computing, pp. 341–350 (2012)

    Google Scholar 

  13. Tedesco, S., Barton, J., O’Flynn, B.: A review of activity trackers for senior citizens: research perspectives, commercial landscape and the role of the insurance industry. Sensors, 17(6) (2017)

    Google Scholar 

  14. Dias, D., Cunha, J.S.: Wearable health devices—vital sign monitoring, systems and technologies, Sensors, 18(8) (2018). https://doi.org/10.3390/s18082414

    Article  Google Scholar 

  15. Venkataramani, D., Jadhav, A., Wadzirkar, S., Ambekar, J., Dive, K., Sharma, S., Khadse, G.: Infant monitoring using wearable computing. Int. J. Eng. Tech. Res. 11(3), 95–98 (2015)

    Google Scholar 

  16. Bennett, J., Rokas, Chen L.: Healthcare in the smart home: a study of past. Present. Futur., Sustain. 9(5), 1–23 (2017). https://doi.org/10.3390/su9050840

    Article  Google Scholar 

  17. Wearabletechdigest.com: Leo Fitness Intelligence- A Wearable Tracking Your Body’s Biosignal. [online] Available at: https://www.wearabletechdigest.com/leo-fitness-intelligence.html (2019). Accessed 25 Jul 2019

  18. dorsaVi EU: ViMove2: Analyse Patient Movement & Muscle Activity—dorsaVi EU. [online] Available at: https://www.dorsavi.com/uk/en/vimove/ (2019). Accessed 25 Jul 2019

  19. Dubosson, F., Ranvier, J., Bromuri, S., Calbimonte, J., Ruiz, J., Schumacher, M.: The open D1NAMO dataset: a multi-modal dataset for research on non- invasive type 1 diabetes management. Inform. Med. Unlocked 13, 92–100 (2018)

    Article  Google Scholar 

  20. Chalif, B.: Dartmouth Computer Science Technical Report TR2016-805. Security and Privacy Analysis of Medical Wearables (2016)

    Google Scholar 

  21. Miao, F., Cheng, Y., He, Y., He, Q., Li, Y.: A wearable context-aware ECG monitoring system integrated with built-in kinematic sensors of the smartphone. Sensors 15(5), 11465–11484 (2015). https://doi.org/10.3390/s150511465

    Article  Google Scholar 

  22. Marin, J.: Octopus: a design methodology for motion capture wearables. Sensors 17(8), 1–24 (2017). https://doi.org/10.3390/s17081875

    Article  Google Scholar 

  23. Wearable Tech|CrunchWear: Kapture—Wearable Tech|CrunchWear. [online] Available at: https://crunchwear.com/category/companies/kapture/ (2019). Accessed 25 Jul 2019

  24. Hester, J., Peters, T., Yun, T., Peterson, R., Skinner, J., Golla B., Sorber, J.: Demo abstract: the amulet wearable platform. In: Proceedings of the ACM Conference on Embedded Network Sensor Systems (SenSys), pp. 290–291 (2016)

    Google Scholar 

  25. Shottracker.com: ShotTracker| Automatically captures statistics for your entire team—Klaycamp Site. [online] Available at: https://shottracker.com/klaycamp (2019). Accessed 25 Jul 2019

  26. Skinput: Appropriating the Body as anInput Surface. Available at: http://www.chrisharrison.net/index.php/Research/Skinput (2019). Accessed 25 Jul 2019

  27. Game Golf Pro: Available at: https://www.gamegolf.com/home/?v=27f1fb0 (2019). Accessed 25 Jul 2019

  28. LumoBack: Available at: https://www.mobihealthnews.com/tag/lumoback (2019). Accessed 25 Jul 2019

  29. Anon: [online] Available at: https://vandrico.com/wearables/device/lumo-lift (2019) Accessed 25 Jul 2019

  30. Wang, W., Adamczyk, P.G.: Analyzing gait in the real world using wearable movement sensors and frequently repeated movement paths. Sensors 19(8) (2019)

    Article  Google Scholar 

  31. Hegde, N., Bries, M., Sazonov, E.: A comparative review of footwear-based wearable systems. Electronics 5(4) (2016)

    Article  Google Scholar 

  32. Sensoriafitness.com: Sensoria Home Page. [online] Available at: https://www.sensoriafitness.com/ (2019). Accessed 25 Jul 2019

  33. Lee, H., Ko, H., Jeong, C., Lee, J.: Wearable photoplethysmographic sensor based on different LED light intensities. IEEE Sens. J. 17(3), 587–588 (2017)

    Google Scholar 

  34. Shu, Y. Li, C., Wang, Z., Mi, W., Li, Y., Ren, T.L.: A pressure sensing system for heart rate monitoring with polymer -based pressure sensors and an anti-interference post processing circuit, Sensors 15(2), 3224–3235 (2015)

    Article  Google Scholar 

  35. Zuo, P., Wang, D.Zhang: Comparison of three different types of wrist pulse signals by their physical meanings and diagnosis performance. IEEE J. Biomed. Health Inform. 20(1), 119–127 (2016)

    Article  Google Scholar 

  36. Milici, J., Lorenzo, A., Lázaro, R., Villarino, D.Girbau: Wireless breathing sensor based on wearable modulated frequency selective surface. IEEE Sens. J. 17(5), 1285–1292 (2017)

    Article  Google Scholar 

  37. Mahbubet, et al.: A low-power wireless piezoelectric sensor-based respiration monitoring system realized in CMOS process. IEEE Sens. J. 17(6), 1858–1864 (2017)

    Article  Google Scholar 

  38. Atalay, O., Kennon, W.R., Demirok, E.: Weft-knitted strain sensor for monitoring respiratory rate and its electro-mechanical modeling. J. IEEE Sens. 15(1), 110–122 (2015)

    Article  Google Scholar 

  39. Aqueveque, C., Gutiérrez, F., Rodríguez, S., Pino, E.J., Morales, A., Wiechmann, E.P.: Monitoring physiological variables of mining workers at high altitude. IEEE Trans. Ind. Appl. 53(3), 2628–2634 (2017)

    Article  Google Scholar 

  40. Griggs, D., et al.: Design and development of continuous cuff-less bloodpressure monitoring devices. In: The Proceedings of IEEE SENSORS, pp. 1–3 (2016)

    Google Scholar 

  41. Shenoy, M.V., Karuppiah, A., Manjarekar, N.: A lightweight ANN based robust localization technique for rapid deployment of autonomous systems. J. Ambient Intell. Humaniz. Comput. (2019). https://doi.org/10.1007/s12652-019-01331-0

    Article  Google Scholar 

  42. Escalera, S., Athitsos, Vassilis, Guyon, I.: Challenges in multimodal gesture recognition. J. Mach. Learn. Res. 17, 1–54 (2016)

    MathSciNet  Google Scholar 

  43. Xu, P.: A Real-time hand gesture recognition and human-computer interaction system. CoRR, Vol. abs/1704.07296, pp. 1–8 (2017)

    Google Scholar 

  44. Dasarathy, B.V.: Sensor fusion potential exploitation innovative architectures and illustrative applications. Proc. IEEE, 24–38 (1997)

    Article  Google Scholar 

  45. Durrant Whyte, H.F.: Sensor models and multisensory integration. Int. J. Robot. Res. 7(6), 97–113 (1988)

    Article  Google Scholar 

  46. Elmenreich, W., Pitzek, S.: Using sensor fusion in a time-triggered network. In: Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society, Denver, USA, vol. 1, pp. 369–374 (2001)

    Google Scholar 

  47. Luo, R.C., Chou, Y.C., Chen, O.: Multisensor fusion and integration: Algorithms, applications, and future research directions. In: Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007, vol. 2(2), pp. 1986–1991. https://doi.org/10.1109/ICMA.2007.4303855 (2007)

  48. Ribas, A.D., Colonna, J.G., Figueiredo, C.M.S., Nakamura, E.F.: Similarity clustering for data fusion in Wireless Sensor Networks using k-means. In: Proceedings of the International Joint Conference on Neural Networks, pp. 1–7, (2012)

    Google Scholar 

  49. Smaili, C., El Najjar, F.: Multi-sensor fusion method using Bayesian network for precise multi-vehicle localization. In: Proceedings of the IEEE Conference on Intelligent Transportation Systems, ITSC, pp. 906–911 (2008). https://doi.org/10.1109/ITSC.2008.4732643

  50. Federal Trade Commission Staff Report: Internet of Things—Privacy and Security in a Connected World; FTC: Seattle. WA, USA (2013)

    Google Scholar 

  51. Naone, E.: Taking Control of Cars from afar. 14 March 2011. Available online: https://www.technologyreview.com/s/423292/taking-control-of-cars-from-afar/ (2011). Accessed on 11 April 2016

  52. Kijewski, M.: The Medical Devices Most Vulnerable to Hackers. Available online:https://www.medtechintelligence.com/feature_article/medical-devices-vulnerable-hackers/ (2018). Accessed on 10 April 2018

  53. Paganini, P.: Smartwatch Hacked, How to Access Data Exchanged with Smartphone, 11 December 2014. Available online: http://securityaffairs.co/wordpress/31007/intelligence/smartwatch-hacked.html (2014). Accessed on 5 April 2018

  54. Fitbit.com: Fitbit Versa|Smartwatch Family. [online] Available at: https://www.fitbit.com/in/versa (2019). Accessed 25 Jul 2019

  55. Melamed, T.: An active man-in-the-middle attack on bluetooth smart devices. Int. J. Saf. Secur. 8, 200–211 (2018)

    Article  Google Scholar 

  56. Arriba-Pérez, F., Caeiro-Rodríguez, M., Santos-Gago, J.M.: Collection and processing of data from wrist wearable devices in heterogeneous and multiple-user scenarios. Sensors (Switzerland), 16(9) (2019). https://doi.org/10.3390/s16091538

    Article  Google Scholar 

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Authors and Affiliations

  1. Birla Institute of Technology and Science, Pilani, Pilani Campus, Jhunjhunu, Rajasthan, India

    Meetha. V. Shenoy

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  1. Meetha. V. Shenoy
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Correspondence to Meetha. V. Shenoy .

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Editors and Affiliations

  1. CSIE Department, National Dong Hwa University, New Taipei City, Taiwan

    Sheng-Lung Peng

  2. Department of Computer Science and Engineering, Brainware University, Kolkata, West Bengal, India

    Souvik Pal

  3. Department of Communications Engineering, Xiamen University, Xiamen City, Fujian, China

    Lianfen Huang

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Shenoy, M.V. (2020). Sensor Information Processing for Wearable IoT Devices. In: Peng, SL., Pal, S., Huang, L. (eds) Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm. Intelligent Systems Reference Library, vol 174. Springer, Cham. https://doi.org/10.1007/978-3-030-33596-0_7

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