Title:An Empirical and Deep Learning Investigation of Working Conditions and
Musculoskeletal Outcomes in Wheat Farmers
Volume: 18
Issue: 7
Author(s): Ram Charan Bairwa, Makkhan Lal Meena, Govind Sharan Dangayach, Rahul Jain*Manish Kumar Jindal
Affiliation:
- Department of Mechanical Engineering, Rajasthan Technical University, Kota, Rajasthan, India
Keywords:
Agriculture, ergonomics, musculoskeletal disorders, risks, demographic, musculoskeletal discomfort.
Abstract:
Background: In developing countries, various farming activities are performed manually
with the help of traditional hand tools. Therefore, agriculture is recognized as one of the risky
occupations.
Objective: This research study aims to identify the critical working conditions of wheat farmers in
Rajasthan state, India.
Method: Data were collected through the survey conducted on 75 randomly selected wheat farmers
of Rajasthan. The survey questionnaire gathered information related to demographic, occupational,
and musculoskeletal discomfort faced by the farmers. In addition, a deep learning-based
posture detection study of the workers was performed to assess the postural risks through a rapid
upper limb assessment score.
Result: The collected data were analyzed further for fruitful insights. The survey outcomes
showed that awkward posture (41%) and repetitive movement (35%) were the most reported reasons
for the severe risks of musculoskeletal disorders among farmers. The posture evaluationbased
patent study outcomes showed that approximately 51% of subjects lie in the action category
4, which shows the higher level of risks in the activities performed by farmers.
Conclusion: It is suggested to apply the principles of physical ergonomics in the agriculture sector
and spread awareness among the farmers about the agriculture risks associated with farming
activities.
