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Achieving Wellness by Monitoring the Gait Pattern with Behavioral Intervention for Lifestyle Diseases

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Fourth International Congress on Information and Communication Technology

Abstract

Obesity is becoming one of the prevalent lifestyle diseases across the globe; need to be deal with behavioral intervention through self-management and motivation in line with rigorous physical exercise. When it is a matter to handle obesity to regain the health, parameters like: self-motivation, self-control, guided treatment, counseling, monitored exercise, and medical assistance are essential in consideration list. Paper proposes the model encompassing three-dimensional care including nutritional intake, counseling, and gait monitoring during exercise. Considering the effect of obesity on biomechanics of foot, gait pattern analysis of obese person provides greater information regarding variations in spatio-temporal parameters. Ever-increasing contribution of behavioral intervention will maintain the line of action in the perfect direction. A selection of accelerometer, gyroscope, and electromyography sensors is appropriate for the cause to derive basic hardware. MSP430 processor and ZigBee module are used for processing information and establishing communication. Within close proximity and placement of nodes at a different level, nodes are able to achieve 90–94% packet delivery ratio in actual environment compare to the 100% packet delivery in simulation environment. Result suggests that with the adaption of accurate classification process, system could be useful for controlled exercise monitoring or for daily activity monitoring, which is working at low-power level with affordable wearable technology in achieving wellness.

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References

  1. Author, F.: Article title. Journal 2(5), 99–110 (2016). https://www.who.int/topics/obesity/en/

  2. Miller-Rosales, C., et al.: CREATE Wellness: a multi-component behavioral intervention for patients not responding to traditional cardiovascular disease management. Contemp. Clin. Trials Commun. 8, 140–146 (2017)

    Article  Google Scholar 

  3. Jegede, J.A., Adegoke, B.O.A., Olagbegi, O.M.: Effects of a twelve-week weight reduction exercise programme on selected spatiotemporal gait parameters of obese individuals. J. Obes. (2017)

    Google Scholar 

  4. Koushyar, H., et al.: Relative strength at the hip, knee, and ankle is lower among younger and older females who are obese. J. Geriatr. Phys. Ther. (2001) 40(3), 143 (2017)

    Article  Google Scholar 

  5. Rosso, V. et al.: Gait measurements in the transverse plane using a wearable system: an experimental study of test-retest reliability. In: Instrumentation and Measurement Technology Conference (I2MTC), 2017 IEEE International

    Google Scholar 

  6. Milner, C.E. et al.: Walking velocity and step length adjustments affect knee joint contact forces in healthy weight and obese adults. J. Orthop. Res. (2018)

    Google Scholar 

  7. Kathirgamanathan, B., Silva, P., Fernandez. J.: Does obesity affect the biomechanics of the foot? A preliminary computational and experimental study. In: Engineering Research Conference (MERCon), 2017 Moratuwa. IEEE 2017

    Google Scholar 

  8. Boateng, G. et al.: GeriActive: wearable app for monitoring and encouraging physical activity among older adults. BSN 2018

    Google Scholar 

  9. Andreu-Perez, J., et al.: From wearable sensors to smart implants—toward pervasive and personalized healthcare. IEEE Trans. Biomed. Eng. 62(12), 2750–2762 (2015)

    Article  Google Scholar 

  10. Misgeld, B.J.E., et al.: Body-sensor-network-based spasticity detection. IEEE J. Biomed. Health Inform. 20(3), 748–755 (2016)

    Article  Google Scholar 

  11. Chinchole, S., Samir, P.: Cloud and sensors based obesity monitoring system. In: 2017 International Conference on Intelligent Sustainable Systems (ICISS). IEEE 2017

    Google Scholar 

  12. Hegde, N. et al.: One size fits all electronics for insole-based activity monitoring. In: Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE. IEEE 2017

    Google Scholar 

  13. Hegde, N., et al.: Automatic recognition of activities of daily living utilizing insole-based and wrist-worn wearable sensors. IEEE J. Biomed. Health Inform. 22(4), 979–988 (2018)

    Article  Google Scholar 

  14. Sazonov, E., et al.: Posture and activity recognition and energy expenditure prediction in a wearable platform. IEEE J. Biomed. Health Informat. 19(4), 1339–1346 (2015)

    Article  Google Scholar 

  15. Debes, C., et al.: Monitoring activities of daily living in smart homes: understanding human behavior. IEEE Sig. Process. Mag. 33(2), 81–94 (2016)

    Article  Google Scholar 

  16. Sathe, N., Anil H., Rashmi P.: Pre-habilitation and wellness through gait analysis using body worn sensors. In: Proceedings of the 2018 International Conference on Communication Engineering and Technology. ACM 2018

    Google Scholar 

  17. Looney, S.M., Raynor. H.A.: Behavioral lifestyle intervention in the treatment of obesity. Health Serv. Insights 6, HSI-S10474 (2013)

    Google Scholar 

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Correspondence to Neha Sathe .

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Sathe, N., Hiwale, A. (2020). Achieving Wellness by Monitoring the Gait Pattern with Behavioral Intervention for Lifestyle Diseases. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Fourth International Congress on Information and Communication Technology. Advances in Intelligent Systems and Computing, vol 1027. Springer, Singapore. https://doi.org/10.1007/978-981-32-9343-4_17

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  • DOI: https://doi.org/10.1007/978-981-32-9343-4_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9342-7

  • Online ISBN: 978-981-32-9343-4

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