Elsevier

Journal of Biomechanics

Volume 49, Issue 1, 4 January 2016, Pages 19-25
Journal of Biomechanics

Regional neuromuscular regulation within human rectus femoris muscle during gait in young and elderly men

https://doi.org/10.1016/j.jbiomech.2015.11.010Get rights and content

Abstract

Recently, we demonstrated region-specific electromyography (EMG) responses along the rectus femoris (RF) muscle during gait in healthy young men (Watanabe et al., 2014b). For the RF muscle, regional EMG response should be tested to characterize neuromuscular control and/or to assess its dysfunction and/or pathology during gait. We aimed to identify spatial distribution of EMG pattern within the RF muscle in elderly during gait. Seven young men (age: 20.4±1.0 years) and 8 elderly men (age: 73.8±5.9 years) walked on treadmill with three different speed: slow (preferred −1 km/h), preferred, and fast (preferred +1 km/h). The spatial distribution of surface EMG was tested by central locus activation (CLA), which is calculated from 18 surface electrodes along the longitudinal line of the muscle. CLA were not different between the groups for slow and preferred gait speed (p>0.05) during a gait cycle. In fast gait speed, CLA at 80% of a gait cycle (swing phase) for the elderly were significantly located at more distal site than the young group (p<0.05) (13.0±2.1 cm and 10.2±2.2 cm from most proximal electrodes for the elderly and young). This difference in CLA reflected a significantly lower EMG activity at the proximal regions in the elderly group (p<0.05). These results suggest the elderly manifest characteristic regional EMG responses within the RF muscle for leg swing movement of fast speed gait.

Introduction

Age-associated changes in joint kinematics and/or kinetics during gait have been well investigated and biomechanical basis of them has been described (DeVita and Hortobagyi, 2000, Judge et al., 1996a, Judge et al., 1996b, Kerrigan et al., 1998, Riley et al., 2001, Winter et al., 1990). Although this is thought to be by neuromuscular adaptations with aging, very little work is currently available in the published literature on neuromuscular control in elderly during gait (Schmitz et al., 2009).

Surface electromyography (EMG) has been widely used for understanding neuromuscular control during gait (Winter and Yack, 1987). Comparison of EMG profiles to normal pattern is one of the standard methods for assessing dysfunction and/or pathology in gait for the elderly or patients (Annaswamy et al., 1999, Kerrigan et al., 1991, Reinbolt et al., 2008). Normal EMG patterns during gait for major lower extremity muscles were identified in previous studies (Barr et al., 2010, Byrne et al., 2005, Di Nardo and Fioretti, 2013, Nene et al., 2004). However, in rectus femoris (RF) muscle, large deviations were found among the previous studies. Two different EMG patterns, i.e., double bursts around swing-to-stance transition and stance-to-swing transition and single burst around stance-to-swing transition, were reported in the previous studies (Annaswamy et al., 1999, Winter and Yack, 1987, Yang and Winter, 1985). Since RF muscle is one of the key muscles in pathological gait patterns (Kerrigan et al., 1991, Knuppe et al., 2013, Reinbolt et al., 2008, Riley and Kerrigan, 1998, Sung and Bang, 2000), it is necessary to resolve this issue and to standardize normal EMG pattern for this muscle in the able-bodied adults, children, the elderly, and patients.

Recently, we demonstrated region-specific EMG responses within the RF muscle during gait by using multi-channel surface EMG technique (Watanabe et al., 2014b). In our study, proximal and distal regions of the RF muscle preferentially activate around stance-to-swing transition and swing-to-stance transition, respectively. Also, these two bursts were found at middle regions. Since two different patterns, which were reported in the previous studies (Annaswamy et al., 1999, Winter and Yack, 1987, Yang and Winter, 1985), were found within a muscle in our study, we suggested that variations in EMG patterns for the RF muscle among the studies is partly caused by region-specific neuromuscular regulation within a muscle. For the RF muscle, multi-channel surface EMG technique could strongly contribute to characterize neuromuscular control and to assess its dysfunction and/or pathology during gait. In the present study, we aimed to identify spatial distribution of EMG pattern within the RF muscle in elderly during gait. Since the effects of age upon joint kinetics/kinematics and/or neuromuscular activation were often found with an increase in gait speed (Judge et al., 1996a, Kerrigan et al., 1998, Riley et al., 2001), effect of gait speed on spatial distribution of surface EMG within the muscle was assessed in order to characterize age-related changes in neuromuscular responses in the present study.

Section snippets

Subjects

Seven young men (age: 20.4±1.0 years, height: 169.5±5.3 cm, body mass: 64.1±6.9 kg) and 8 elderly men (age: 73.8±5.9 years, height: 166.5±6.6 cm, body mass: 63.1±8.7 kg) volunteered for the present study. The subjects in both groups gave written informed consent for the study after receiving a detailed explanation of the purposes, potential benefits, and risks associated with participation. All subjects were healthy with no history of any musculoskeletal or neurological disorders. All study

Results

Mean normalized ARV patterns from different channels along the longitudinal line of the RF muscle at every 2% of gait cycle are shown in Fig. 2. For visualization, these data were illustrated as color scale map in Fig. 3. There were two major bursts around 90–20% of gait cycle (swing-to-stance transition) and approximately 60% of gait cycle (stance-to-swing transition) in all conditions and both subject groups. However, relative intensities of these bursts were different among the channels.

Discussion

The present study compared spatial distribution of surface EMG within the RF muscle during gait between the young and elderly groups. We recorded multi-channel surface EMG during three different gait speeds since the age-related alterations in biomechanical and/or neurophysiological parameters were found with an increase in gait speed (Judge et al., 1996a, Kerrigan et al., 1998, Riley et al., 2001). The results of present study were also influenced by gait speed. Although CLA, which is an

Conflict of interest

The authors have no conflicts of interest related to this study.

Acknowledgment

This work was supported by Japanese Council for Science, Technology and Innovation (CSTI), Cross-ministerial Strategic Innovation Promotion Program (SIP Project ID 14533567), JSPS KAKENHI, a Grant-Aid for Young Scientist (B) (No. 26750309), and Foundation for Total Health Promotion (No. 96).

References (29)

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