Biofeedback on Forestry Machine Operators

Abstract

Aotearoa, New Zealand, has cultivated a sustainable and thriving forest sector, establishing it as a primary industry. Throughout the years, there has been a significant transition in the forest industry towards using mechanised methods. Operating machines and maintaining precise hand and arm movements can lead to muscle strain in operators. This strain is harmful and increases the risk of work-related musculoskeletal disorders. This thesis aims to utilise electromyography sensors to observe the muscle activity of operators in forestry machines while carrying out harvesting operations. The objective of this research is to examine the potential advantages of biofeedback training in enhancing operators' physiological functioning through visual feedback. Experimental testing phases were required prior to deployment in the field. The primary trial details electromyographic recordings gathered through field measurements using electromyographic (BTS FREEEMG 1000) sensors to assess the activity of the upper trapezius muscles. Recordings were conducted on 14 operators performing operational harvesting tasks. Tasks included felling, processing, loading, shovelling, fleeting, and sorting. Findings: EMG Biofeedback training allowed operators to observe and consciously control the contraction and relaxation of the upper trapezius muscles. Overall, the average muscle activity decreased during biofeedback training in most recordings. Results highlight the potential of EMG biofeedback training as a preventative tool for work-related musculoskeletal disorders in New Zealand.

This research is conducted as part of a master's project in collaboration with Scion and Waikato University with funding from the New Zealand Forest Growers Levy.