Artificial Intelligence Assisted Mobility Device Development

Authors

  • Shivali Upadhyay Gifted Gabber
  • Jothsna Kethar Gifted Gabber

DOI:

https://doi.org/10.47611/jsrhs.v12i2.4401

Keywords:

#ArtificialIntelligence, #MobilityDevice

Abstract

Artificial intelligence is rapidly gaining attention in the world for assisting humans with tasks that they could not achieve otherwise. In the medical industry specifically, artificial intelligence has made it possible to almost connect the original human body with another perfected body. This paper is intended to summarize the different conditions that may lead to someone needing a mobility device in the first place, what companies have preexisting parts that we can repurpose for the ideal artificial intelligence assisted mobility device, and the different AI technology that we can use to build this machine. 

The main methods utilized to collect the data used in this paper were collecting research from various scientific journals on the different conditions that can lead to the need for a mobility device, data collected from medical technology companies, and research on different artificial intelligence tools. Combining these pieces of research from different scientific journals and technological sources, it was found that the leading causes of falls are a result of cognitive impairment and balance-related issues. It was also concluded that the main pieces of equipment, are already present and would need to be manufactured in a way that the elderly user could use it on a daily basis. The overall research concluded to find that the artificial intelligence device would need to be flexible, durable, and greatest of all, prevent the user from falling or alarm a medical professional that someone is at risk of falling.

Downloads

Download data is not yet available.

Author Biography

Jothsna Kethar, Gifted Gabber

The 8-week session where the student will conduct research and write a scientific journal guided by Dr. Rajagopal Appavu, Assistant Professor, Vaccine Developer, Senior Data Scientist/Analyst, Toxicologist, and Chemist. After the draft has been approved by Professor, students will be guided to submit their scientific journal.

References or Bibliography

Al-Aama T. Falls in the elderly: spectrum and prevention. Can Fam Physician. 2011 Jul;57(7):771-6. Erratum in: Can Fam Physician. 2014 Mar;60(3):225. PMID: 21753098; PMCID: PMC3135440.

Kobayashi, K., Ando, K., Inagaki, Y., Suzuki, Y., Nagao, Y., Ishiguro, N., & Imagama, S. (2018). Characteristics of falls in orthopedic patients during hospitalization. Nagoya journal of medical science, 80(3), 341–349. https://doi.org/10.18999/nagjms.80.3.341

Bazarevsky, V., & Grishchenko, I. (2020, August 13). On-device, real-time body pose tracking with MediaPipe Blazepose. Google Research. Retrieved January 11, 2023, from https://ai.googleblog.com/2020/08/on-device-real-time-body-pose-tracking.html

Centers for Disease Control and Prevention. (2021, August 6). Facts about Falls. Centers for Disease Control and Prevention. Retrieved January 11, 2023, from https://www.cdc.gov/falls/facts.html#:~:text=Each%20year%2C%20millions%20of%20older,than%20half%20tell%20their%20doctor.&text=Falling%20once%20doubles%20your%20chances%20of%20falling%20again

Radiometer. Danaher. (n.d.). Retrieved January 11, 2023, from https://www.danaher.com/our-businesses/diagnostics/radiometer#:~:text=The%20company%20specializes%20in%20blood,flow%20in%20acute%20care%20settings

Advanced Digital Healthcare. Stryker. (n.d.). Retrieved January 11, 2023, from https://www.stryker.com/us/en/portfolios/medical-surgical-equipment/advanced-digital-healthcare.html

Miller, K., Kubota, T., & Lynch, S. (2020, June 11). Building a wearable that can catch you when you stumble. Stanford HAI. Retrieved January 13, 2023, from https://hai.stanford.edu/news/building-wearable-can-catch-you-when-you-stumble

Kukil. (2022, November 18). Building a Poor Body Posture Detection and Alert System using MediaPipe. LearnOpenCV. Retrieved January 11, 2023, from https://learnopencv.com/building-a-body-posture-analysis-system-using-mediapipe/

Wilby, M. L. (2018). Physical Mobility Impairment and Risk for Cardiovascular Disease. Health Equity, 3(1), 527-531. https://doi.org/10.1089/heq.2019.0065

Published

05-31-2023

How to Cite

Upadhyay, S., & Kethar, J. (2023). Artificial Intelligence Assisted Mobility Device Development. Journal of Student Research, 12(2). https://doi.org/10.47611/jsrhs.v12i2.4401

Issue

Section

HS Research Articles