Abstract
Surface electromyography (sEMG) is commonly used in gait analysis for detecting muscle activity in a non-invasive way, preserving the normal mobility of the subject. The purpose of the study was to assess the variability of sEMG signals acquired from lower-limb muscles during walking. To this aim, a statistical analysis of sEMG signals from a large number (hundreds) of strides per subject was performed in twenty-two healthy young caucasian volunteers. Tibialis Anterior, Gastrocnemius Lateralis, Rectus Femoris, Biceps Femoris and Vastus Lateralis were selected to represent both proximal and distal leg segments. Besides the muscular activation onset-offset instants, the study was aimed to analysed the occurrence frequency of muscle recruitment, a parameter seldom considered because of the low number of strides usually analysed in classic EMG studies. Findings illustrated that a single muscle showed a different number of activation intervals in different strides of the same walking. The number of times when muscle activates during a single gait cycle defined the modality of muscle recruitment, that in the present study was referred to as activation modality, i.e. n-activation modality consists of n-activation intervals for the considered muscle, during a single gait cycle. For each of the selected muscles, five activation modalities were detected. Each of these activation modalities is characterized by a different occurrence frequency and by different onset-offset activation instants. Concomitance of these results indicates a large variability in onset-offset muscular activation and occurrence frequency, which should be considered in discriminating pathological from physiological behaviour and for designing focused gait studies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Frigo C, Crenna P (2009) Multichannel sEMG in clinical gait analysis: a review and state-of-the-art. Clin Biomech 24:236–245
Patikas D, Wolf SI, Schuster W et al (2007) Electromyographic patterns in children with cerebral palsy: do they change after surgery? Gait Posture 26:362–371
Romkes J, Hell AK, Brunner R (2006) Changes in muscle activity in children with hemiplegic cerebral palsy while walking with and without ankle–foot orthoses. Gait Posture 24:467–474
Sutherland DH (2001) The evolution of clinical gait analysis part l: kinesiological EMG. Gait Posture 14:61–70
Perry J (1992) Gait analysis: normal and pathological function. Slack Incorporated, Thorofare
Petersen TH, Farmer SF, Kliim-Due M et al (2013) Failure of normal development of central drive to ankle dorsiflexors relates to gait deficits in children with cerebral palsy. J Neurophysiol 109:625–639
Stewart C, Postans N, Schwartz MH et al (2007) An exploration of the function of the triceps surae during normal gait using functional electrical stimulation. Gait Posture 26:482–488
Sutherland DH, Cooper L, Daniel D (1980) The role of the ankle plantar flexors in normal walking. J Bone Joint Surg Am 62:354–363
Di Nardo F, Ghetti G, Fioretti S (2013) Assessment of the activation modalities of gastrocnemius lateralis and tibialis anterior during gait: a statistical analysis. J Electromyogr Kinesiol 23:1428–1433
Di Nardo F, Fioretti S (2012) Statistical analysis of surface electromyographic signal for the assessment of rectus femoris modalities of activation during gait. J Electromyogr Kinesiol 23:56–61
Di Nardo F, Fioretti S (2014) Emg-based analysis of treadmill and ground walking in distal leg muscles. IFMBE Proc 41:611–614. doi:10.1007/978-3-319-00846-2_151
Di Nardo F, Mengarelli A, Ghetti G et al (2014) Statistical analysis of EMG signal acquired from tibialis anterior during gait. IFMBE Proc 41:619–622. doi:10.1007/978-3-319-00846-2_153
Di Nardo F, Mengarelli A, Maranesi E et al (2014) Assessment of the ankle muscle co-contraction during normal gait: a surface electromyography study. J Electromyogr Kinesiol 25(2):347–354
Di Nardo F, Mengarelli A, Maranesi E et al (2014) Influence of gender on the myoelectric signal of shank muscles. In: MESA 2014—10th IEEE/ASME international conference on mechatronic and embedded systems and applications conference proceedings, Senigallia
Di Nardo F, Mengarelli A, Maranesi E et al (2015) Gender differences in the myoelectric activity of lower limb muscles in young healthy subjects during walking. Biomed Sig Process Control 19:14–22
Agostini V, Nascimbeni A, Gaffuri A et al (2010) Normative EMG activation patterns of school-age children during gait. Gait Posture 32:285–289
Arsenault AB, Winter DA, Marteniuk RG (1986) Is there a ‘normal’ profile of EMG activity in gait? Med Biol Eng Comput 24:337–343
Winter DA, Yack HJ (1987) EMG profiles during normal human walking: stride to stride and inter-subject variability. Electroencephalogr Clin Neurophysiol 67:402–411
Yang JF, Winter DA (1984) Electromyographic amplitude normalization methods: improving their sensitivity as diagnostic tools in gait analysis. Arch Phys Med Rehabil 65:517–521
Bonato P, D’Alessio T, Knaflitz M (1998) A statistical method for the measurement of muscle activation intervals from surface myoelectric signal during gait. IEEE Trans Biomed Eng 45:287–299
Balestra G, Knaflitz M, Molinari F (2002) Principles of statistical gait analysis. In: Proceedings of XIV ISEK conference, Vienna
Staude G, Flachenecker C, Daumer M et al (2001) Onset detection in surface electromyographic signals: a systematic comparison of methods. J Adv Signal Process 2:67–81
Maranesi E, Di Nardo F, Ghetti G et al (2014) A goniometer-based method for the assessment of gait parameters. In: 10th IEEE/ASME international conference on mechatronic and embedded systems and applications conference proceedings, Senigallia
Freriks B, Hermens HJ, Disselhorst-Klug C et al (2000) Development of recommendations for sEMG sensors and sensor placement procedures. J Electromyogr Kinesiol 10:361–374
Powers CM, Landel RF, Perry J (1996) Timing and intensity of vastus muscle activity during functional activities in subjects with and without patellofemoral pain. Phys Ther 76:946–955
Agostini V, Knaflitz M (2012) Statistical gait analysis. In: Acharya RU, Molinari F, Tamura T, Naidu DS, Suri JS (eds) Distributed diagnosis and home healthcare. American Scientific Publishers, Stevenson Ranch, pp 99–121
Sutherland DH, Olshen R, Cooper L et al (1980) The development of mature gait. J Bone Joint Surg Am 62:336–353
Winter DA (1990) Biomechanics and motor control of human movement, 2nd edn. Wiley, New York
Sutherland DH (1966) An electromyographic study of the plantar flexors of the ankle in normal walking on the level. J Bone Joint Surg Am 48:66–71
Shiavi R, Bugle HJ, Limbird T (1987) Electromyographic gait assessment, part 1: adult EMG profiles and walking speed. J Rehabil Res 24:13–23
Murray MP (1984) Kinematic & EMG patterns during slow, free, and fast walking. J Orthop Res 2:272–280
Conrad B, Meinck HM, Benecke R (1986) Motor patterns in human gait: adaptation to different modes of progression. In: Bles W, Brandt T (eds) Disorders of posture and gait. Elsevier Science Publishers BV, Amsterdam, pp 53–67
Nene A, Byrne C, Hermens H (2004) Is the rectus femoris really part of the quadriceps? Assessment of the rectus femoris function during gait in able-bodied adults. Gait Posture 10:1–13
Winter DA (1991) The biomechanics and motor control of human gait: normal elderly and pathological, 2nd edn. University of Waterloo Press, Waterloo
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Mengarelli, A., Maranesi, E., Burattini, L., Fioretti, S., Di Nardo, F. (2016). sEMG-Based Evaluation of Muscle Recruitment Variability During Walking in Terms of Activation Length and Occurrence Frequency. In: Conti, M., Martínez Madrid, N., Seepold, R., Orcioni, S. (eds) Mobile Networks for Biometric Data Analysis. Lecture Notes in Electrical Engineering, vol 392. Springer, Cham. https://doi.org/10.1007/978-3-319-39700-9_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-39700-9_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-39698-9
Online ISBN: 978-3-319-39700-9
eBook Packages: EngineeringEngineering (R0)