Power Spectrum of Acceleration and Angular Velocity Signals as Indicators of Muscle Fatigue during Upper Limb Low-Load Repetitive Tasks

Abstract

Muscle fatigue is a risk factor for developing musculoskeletal disorders during low-load repetitive tasks. The objective of this study was to assess the effect of muscle fatigue on power spectrum changes of upper limb and trunk acceleration and angular velocity during a repetitive pointing task (RPT) and a work task. Twenty-four participants equipped with 11 inertial measurement units, that include acceleration and gyroscope sensors, performed a tea bag filling work task before and immediately after a fatiguing RPT. During the RPT, the power spectrum of acceleration and angular velocity increased in the movement and in 6–12 Hz frequency bands for sensors positioned on the head, sternum, and pelvis. Alternatively, for the sensor positioned on the hand, the power spectrum of acceleration and angular velocity decreased in the movement frequency band. During the work task, following the performance of the fatiguing RPT, the power spectrum of acceleration and angular velocity increased in the movement frequency band for sensors positioned on the head, sternum, pelvis, and arm. Interestingly, for both the RPT and work task, Cohens’ d effect sizes were systematically larger for results extracted from angular velocity than acceleration. Although fatigue-related changes were task-specific between the RPT and the work task, fatigue systematically increased the power spectrum in the movement frequency band for the head, sternum, pelvis, which highlights the relevance of this indicator for assessing fatigue. Angular velocity may be more efficient to assess fatigue than acceleration. The use of low cost, wearable, and uncalibrated sensors, such as acceleration and gyroscope, in industrial settings is promising to assess muscle fatigue in workers assigned to upper limb repetitive tasks.

Upper-Limb Kinematic Behavior and Performance Fatigability of Elderly Participants Performing an Isometric Task: A Quasi-Experimental Study

“…It is known that muscle fatigue leads to altered motor recruitment, and increased variability of force and movement [20,48,49], and that these changes are often associated with muscle fatigue [38] or the compensatory strategies that occur in the presence of fatigue, which gradually changed along the task time with the aim of relieving the effects of fatigue and maintaining performance for the maximum time possible [50,51].…”

“…Research on the application of IMUs for upper-limb movement analysis has grown in recent years, though their application is still at an early development stage and is especially targeted to the validation of specific protocols and proof-of-concept systems [26,34,36] and to movement analysis and characterization in specific clinical conditions [31,37]. As far as we are aware, there are only a few studies that have used IMUs to assess performance fatigability directly or indirectly during upper-limb [38,39] tasks, and none, during isometric tasks performed by elderly populations.…”

What are the best indicators of myoelectric manifestation of fatigue?

“…(C) Schematic top view of the RPT. Note that data collected from reflective markers are not used in the present study and results obtained from inertial measurements units sensors (orange rectangle boxes) were presented in a previous study [80].…”

“…Please, contact the corresponding author to request access to this figure. units sensors (orange rectangle boxes) were presented in a previous study [80].…”

A dataset for fatigue estimation during shoulder internal and external rotation movements using wearables

“…IMU sensors generally comprise a triaxial accelerometer (acc), triaxial gyroscope (gyr), and triaxial magnetometer (mag). These sensors can be attached to various body segments to capture orientation and motion data, providing insight into kinematic information during the physical task, and related changes caused by physical fatigue 30 , 31 . PPG sensors, often integrated into wearable devices, enable the non-invasive measurement of blood flow and heart rate variability, offering information about an individual’s physiological state 32 , 33 .…”