Time-frequency methods applied to muscle fatigue assessment during dynamic contractions.
This paper discusses the assessment of the electrical manifestations of muscle fatigue during dynamic contractions. In the past, the study of muscle fatigue was restricted to isometric constant force contractions because, in this contraction paradigm, the myoelectric signal may be considered as wide sense stationary over epochs lasting up to two or three seconds, and hence classic spectral estimation techniques may be applied. Recently, the availability of spectral estimation techniques specifically designed for nonstationary signal analysis made it possible to extend the employment of muscle fatigue assessment to cyclic dynamic contractions, thus increasing noticeably its possible clinical applications. After presenting the basics of time-frequency distributions, we introduce instantaneous spectral parameters well suited to tracking spectral changes due to muscle fatigue, discuss the issues of quasi-stationarity and quasi-cyclostationarity, and present different strategies of signal analysis to be utilized with cyclic dynamic contractions. We present preliminary results obtained by analyzing data collected from paraspinal muscles during repetitive lift movements, from the first dorsal interosseus during abduction-adduction movements of the index finger, and from knee flexors and extensors during isokinetic exercise. In conclusion, data herein reported demonstrate that the described techniques allow for evidencing the electrical manifestations of muscle fatigue in different paradigms of cyclic dynamic contractions. We believe that the extension of the objective assessment of the electrical manifestations of muscle fatigue from static to dynamic contractions may increase considerably the interest of researchers and clinicians and open new application fields, as ergonomics and sports medicine.
Knaflitz
M
M
Dipartimento di Elettronica, Politecnico di Torina, Italy. knaflitz@polito.it
Bonato
P
P
D004576:Electromyography; D006801:Humans; D007866:Leg; D009119:Muscle Contraction; D018763:Muscle Fatigue / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted