Advancing total knee replacement surgery Assessment with Wearable Sensors and AI: A Case Study

Authors

  • Bhairavi Ugale
  • Ajay G
  • Anmol Saxena

DOI:

https://doi.org/10.37506/kwcqfk80

Keywords:

OA knee, Total Knee Replacement, wearable sensors, artificial intelligence, advanced diagnostics.

Abstract

Background: India has a higher prevalence of about 20-24%.of people suffering from osteoarthiritis. Due to
the load effect, forces between two and three times body weight are transmitted across the knee joint during a
normal stride, which accounts for the higher risk of OA.A Qualitative Analysis of Decision-Making for Total Knee
Replacement in Patients with Osteoarthritis. A cutting-edge wearable sensor system called Fitknees delivers
a complex arrangement of motion sensors that are carefully placed on the lower limb. These sensors outline
thorough kinematic data that include gait analysis, muscle strength, knee range of motion, and balance metrics.
Objective: Utilizing individualised measurements, using wearable sensors and AI tool to assess preoperative
evaluations and postoperative rehabilitation programs.
Results: camping between affected and unaffected side with the normative data provided by the AI.Conclusion:
advancement in the medical technologies have made it easier for medial professionals to detect and early diagnose
the diseases. Plan a better treatment plan with the aid of artificial intelligence to achieve better results.

Downloads

Download data is not yet available.

Author Biographies

  • Bhairavi Ugale

    BPT, Head of Clinical researcher, Ashva wearable technologies pvt ltd, Bangalore, Karnataka.

  • Ajay G

    MPT musculoskeletal and sports physiotherapist. Certified Manual therapist from FIMT.

  • Anmol Saxena

    Founder and CEO, Ashva Wearable Technologies Pvt Ltd, Bangalore, Karnataka, India.

References

Cui A, Li H, Wang D, Zhong J, Chen Y, Lu H. Global, region-al prevalence, incidence and risk factors of knee osteo-arthritis in population-based studies. EClinicalMedicine [Internet]. 2020;29–30(100587):100587. Availablefrom: http://dx.doi.org/10.1016/j.eclinm.2020.1005872.

Calce SE, Kurki HK, Weston DA, Gould L. The rela-tionship of age, activity, and body size on osteoarthritisin weight-bearing skeletal regions. Int J Paleopathol [In-ternet]. 2018;22:45–53. Available from: http://dx.doi.org/10.1016/j.ijpp.2018.04.001

Bager CL, Karsdal M, Bihlet A, Thudium C, ByrjalsenI, Bay-Jensen AC. Incidence of total hip and total kneereplacements from the prospective epidemiologic risk factor study: considerations for event driven clini-cal trial design. BMC MusculoskeletDisord [Internet]. 2019;20(1). Available from: http://dx.doi.org/10.1186/s12891-019-2680-3

Halewood C, Athwal KK, Amis AA. Pre-clinical assess-ment of total knee replacement anterior-posteriorconstraint. J Biomech [Internet]. 2018;73:153–60.Available from: http://dx.doi.org/10.1016/j.jbio-mech.2018.03.042

Suarez-Almazor ME, Richardson M, Kroll TL, Sharf BF.A qualitative analysis of decision-making for total kneereplacement in patients with osteoarthritis. J Clin Rheu-matol [Internet]. 2010;16(4):158–63. Available from:http://dx.doi.org/10.1097/RHU.0b013e3181df4de4

Root User. Home [Internet]. Ashva - Making Musculo-skeletal Healthcare Data-Driven. Ashva; 2022 [cited2023 Oct 11]. Available from: https://www.ashva.xyz

Integration of Convolutional Neural Networks for AI-En-hanced Post-Operative Assessment in Knee Arthroplas-ty: A Comparative Study” by Johnson et al. Journal ofOrthopedic Informatics. 2023;

Downloads

Published

2024-01-09

How to Cite

Advancing total knee replacement surgery Assessment with Wearable Sensors and AI: A Case Study. (2024). Indian Journal of Physiotherapy and Occupational Therapy - An International Journal, 18(1), 16-21. https://doi.org/10.37506/kwcqfk80