Myoelectric signal measurement during prolonged computer terminal work

Area of Science:

• Biomedical Engineering
• Neuroscience
• Ergonomics

Background:

• Prolonged low-level muscle contractions, common in computer work, pose ergonomic challenges.
• Analyzing myoelectric signals (MES) during such tasks is crucial for understanding muscle fatigue and motor control.
• Portable systems often face data storage limitations, hindering detailed analysis.

Purpose of the Study:

• To investigate myoelectric signal (MES) behavior during sustained, low-level contractions in computer users.
• To develop and apply a data reduction technique for portable MES data loggers.
• To compare MES parameters with and without microbreaks during computer work.

Main Methods:

• A portable multichannel MES data logger was used with a novel pre-processing technique for data reduction.
• MES data were collected from cervical paraspinal extensors, lumbar erector spinae, upper trapezius, and forearm extensors.
• Eighteen participants performed computer work for 80 minutes, with and without 30-second microbreaks every 20 minutes.

Main Results:

• No significant linear trend in MES amplitude or mean frequency was observed over time.
• Most data sets exhibited a cyclic trend in MES frequency and amplitude parameters, even without breaks.
• A higher median mean frequency was noted in cervical extensors during the microbreak protocol, though clinical significance is unclear.

Conclusions:

• A cyclic trend in myoelectric signals, potentially indicating cyclic motor unit recruitment, was discovered during sustained postural contractions.
• The developed data reduction technique effectively addresses limitations of portable MES data loggers.
• Further research is warranted to explore the implications of cyclic motor unit recruitment in sustained contractions.