Time–frequency analysis and estimation of muscle fiber conduction velocity from surface EMG signals during explosive dynamic contractions

[1]  C Capelli,et al.  Effects of microgravity on maximal power of lower limbs during very short efforts in humans. , 1999, Journal of applied physiology.

[2]  A Forster,et al.  Changes in muscle fiber conduction velocity, mean power frequency, and mean EMG voltage during prolonged submaximal contractions , 1989, Muscle & nerve.

[3]  E. Kararizou,et al.  Distribution of muscle fibre types in human skeletal muscle fascicles: an autopsy study of three human muscles. , 1995, Functional neurology.

[4]  C. D. De Luca,et al.  Inference of motor unit recruitment order in voluntary and electrically elicited contractions. , 1990, Journal of applied physiology.

[5]  Paolo Bonato,et al.  Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions , 2001, IEEE Transactions on Biomedical Engineering.

[6]  Silvia A. Pascual,et al.  Altering muscle activity in the lower extremities by running with different shoes. , 2002, Medicine and science in sports and exercise.

[7]  C Capelli,et al.  Effects of microgravity on muscular explosive power of the lower limbs in humans. , 1995, Acta astronautica.

[8]  Benno M. Nigg,et al.  Surface EMG shows distinct populations of muscle activity when measured during sustained sub-maximal exercise , 2001, European Journal of Applied Physiology.

[9]  D T MacIsaac,et al.  Influences of dynamic factors on myoelectric parameters. , 2001, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[10]  R. Enoka,et al.  Motor-unit synchronization increases EMG amplitude and decreases force steadiness of simulated contractions. , 2000, Journal of neurophysiology.

[11]  P. Zamparo,et al.  Effects of elastic recoil on maximal explosive power of the lower limbs , 1997, European Journal of Applied Physiology and Occupational Physiology.

[12]  B. Bigland-ritchie,et al.  Conduction velocity and EMG power spectrum changes in fatigue of sustained maximal efforts. , 1981, Journal of applied physiology: respiratory, environmental and exercise physiology.

[13]  Dario Farina,et al.  Effect of joint angle on surface EMG variables for the muscles of the leg and thigh , 2001 .

[14]  C. D. De Luca,et al.  Frequency Parameters of the Myoelectric Signal as a Measure of Muscle Conduction Velocity , 1981, IEEE Transactions on Biomedical Engineering.

[15]  Walter Herzog,et al.  Determining patterns of motor recruitment during locomotion. , 2002, The Journal of experimental biology.

[16]  B. Nigg,et al.  Muscle activity in the leg is tuned in response to ground reaction forces. , 2001, Journal of applied physiology.

[17]  H B Boom,et al.  The median frequency of the surface EMG power spectrum in relation to motor unit firing and action potential properties. , 1992, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[18]  P. Zamparo,et al.  Maximal power and EMG of lower limbs after 21 days spaceflight in one astronaut. , 1998, Journal of gravitational physiology : a journal of the International Society for Gravitational Physiology.

[19]  L.H. Lindstrom,et al.  Interpretation of myoelectric power spectra: A model and its applications , 1977, Proceedings of the IEEE.

[20]  D. Farina,et al.  Effect of joint angle on EMG variables in leg and thigh muscles , 2001, IEEE Engineering in Medicine and Biology Magazine.

[21]  U. della Croce,et al.  Changes in the surface EMG signal and the biomechanics of motion during a repetitive lifting task , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[22]  J. L. F. Weytjens,et al.  The effects of motor unit synchronization on the power spectrum of the electromyogram , 2004, Biological Cybernetics.

[23]  M Miyashita,et al.  Muscle fiber conduction velocity related to stimulation rate. , 1989, Electroencephalography and clinical neurophysiology.

[24]  Dario Farina,et al.  Surface EMG crosstalk between knee extensor muscles: Experimental and model results , 2002, Muscle & nerve.

[25]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[26]  R Merletti,et al.  Repeatability of surface EMG variables during voluntary isometric contractions of the biceps brachii muscle. , 1999, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[27]  P. Lago,et al.  Effect of motor-unit firing time statistics on e.m.g. spectra , 1977, Medical and Biological Engineering and Computing.

[28]  J R Westbury,et al.  Associations between spectral representation of the surface electromyogram and fiber type distribution and size in human masseter muscle. , 1987, Electromyography and clinical neurophysiology.

[29]  Dario Farina,et al.  Assessment of average muscle fiber conduction velocity from surface EMG signals during fatiguing dynamic contractions , 2004, IEEE Transactions on Biomedical Engineering.

[30]  T. Moritani,et al.  Motor unit activity and surface electromyogram power spectrum during increasing force of contraction , 2004, European Journal of Applied Physiology and Occupational Physiology.

[31]  Jun Yu,et al.  Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study , 2000, IEEE Transactions on Biomedical Engineering.

[32]  A. R. Lind,et al.  Frequency analysis of the surface electromyogram during sustained isometric contractions , 2004, European Journal of Applied Physiology and Occupational Physiology.

[33]  Roberto Merletti,et al.  The extraction of neural strategies from the surface EMG. , 2004, Journal of applied physiology.

[34]  Roberto Merletti,et al.  Motor unit recruitment strategies investigated by surface EMG variables. , 2002, Journal of applied physiology.

[35]  D. Farina,et al.  Muscle‐fiber conduction velocity estimated from surface emg signals during explosive dynamic contractions , 2004, Muscle & nerve.

[36]  Knaflitz,et al.  Myoelectric manifestations of fatigue in voluntary and electrically elicited contractions. , 1990, Journal of applied physiology.

[37]  M. Knaflitz,et al.  Analysis of myoelectric signals recorded during dynamic contractions , 1996 .

[38]  M. Knaflitz,et al.  Time-frequency analysis of surface myoelectric signals during athletic movement , 2001, IEEE Engineering in Medicine and Biology Magazine.

[39]  William J. Williams,et al.  Improved time-frequency representation of multicomponent signals using exponential kernels , 1989, IEEE Trans. Acoust. Speech Signal Process..

[40]  B Gerdle,et al.  The behaviour of the mean power frequency of the surface electromyogram in biceps brachii with increasing force and during fatigue. With special regard to the electrode distance. , 1990, Electromyography and clinical neurophysiology.

[41]  Douglas L. Jones,et al.  Optimal kernels for nonstationary spectral estimation , 1995, IEEE Trans. Signal Process..