Muscle Activation and Rating of Perceived Exertion of Typically Developing Children during Dry and Aquatic Treadmill Walking

Abstract

Aquatic treadmill gait training is a poorly understood rehabilitation method that alters bodyweight support, increases lower limb resistance, and assists with postural stability. This training could be an attractive tool for clinical populations with balance control issues or limited weight-bearing prescriptions for the lower limb. As a first step, the purpose of this study was to quantify differences in mean muscle activity of the tibialis anterior, rectus femoris, medial gastrocnemius, and semitendinosus, and perceived exertion (RPE) in typically developing children (7:8 M:F, age = 11.3 ± 4.1 years, 1.46 ± 0.18 m, and 44.2 ± 16.8 kg) during dry and aquatic treadmill walking at 75%, 100%, and 125% self-selected speed. We hypothesized that the greatest mean muscle activity, normalized to %MVC and averaged across all strides, would be observed during 125% dry treadmill walking and that aquatic treadmill walking would produce lower RPE. Overall, aquatic treadmill walking reduced mean medial gastrocnemius activity by 50.2% (p_adj < 0.001), increased mean rectus femoris activity at least 32.8% (p_adj < 0.006), and produced 78.0% (p_adj = 0.007) greater RPE compared to dry treadmill walking. This study provides normative pediatric data for future aquatic treadmill walking studies in clinical populations to help inform gait rehabilitation protocols.

1. Introduction

Treadmill gait training is an intervention used to improve walking performance in both pediatric and adult populations as they gain repetitions of the gait cycle (Armand et al., 2016; Bishnoi et al., 2022; Earhart and Williams, 2012; Oh-Park et al., 2011; Wren et al., 2020). Typically developing children and adolescents take approximately seven more steps per minute and have a 0.1 m shorter stride length during treadmill than overground walking (Jung et al., 2021). In children with cerebral palsy (CP), treadmill training is more effective than overground walking with regard to functional mobility, functional performance, gross motor function, and functional balance, in other words their ability to move around independently in a variety of environments and their ability to complete routine activities of daily living (Badawy and Ibrahem, 2016; Booth et al., 2018; Grecco et al., 2013b, 2013a). However, individuals with neurological impairments and those prescribed non-weight bearing may benefit more from partial weight-bearing environments during rehabilitation.

Aquatic therapy exploits the buoyancy effect of water to reduce the weight-bearing force on an individual’s muscles and joints (Becker, 2009; Kutzner et al., 2017). Aquatic therapy has been effectively used as an alternative to treadmill gait training in rehabilitating children with cerebral palsy (CP) to improve stride length and walking endurance (Badawy and Ibrahem, 2016; Fragala-Pinkham et al., 2009). Aquatic treadmill walking is a newer rehabilitation paradigm with unknown effects on lower-limb muscle activity in pediatric populations. Studies performed in healthy adults have demonstrated that lower-limb muscular activity during aquatic treadmill locomotion is 30 to 60% lower compared to dry treadmill locomotion (Masumoto et al., 2008, 2004; Shono et al., 2007). However, these findings are not representative due to the physical differences and limitations in typically developing children and children with CP.

Previous investigations of lower-limb muscle activity during treadmill walking have reported greater muscle activity with increased walking speeds (Hesse et al., 2001; Khademi-Kalantari et al., 2017). Hesse et al. also found that hemiparetic adults walked with a more typical activation pattern and more efficiently at higher speeds, suggesting that treadmill training at above-average speeds may facilitate rehabilitation of lower extremity muscles.

Understanding the influence of treadmill walking environment on muscular activity and perceived exertion may help inform clinicians and physical therapists on gait rehabilitation protocol development in subject specific presentations. The purpose of this study was to determine the effect of treadmill environment and walking speed on muscle activity and perceived exertion during treadmill walking in typically developing children. This study compared two treadmill environments and three walking speeds (75%, 100%, and 125% of self-selected walking speed, determined in each environment). Our first hypothesis was that mean muscular activity of an entire gait cycle (across all strides), would be the greatest during dry treadmill walking at a fast speed. This was motivated by the increased physical demand of fast walking and increased body weight offloaded in water due to buoyancy. Our second hypothesis was that within each speed condition, perceived exertion would be lower during aquatic treadmill walking due to body weight unloading in water due to buoyancy. While we expected the hydrodynamic drag in water to have an effect on the outcome variables, we expected the buoyancy to have a greater impact on muscle activation and perceived exertion than hydrodynamic drag.

2. Materials and Methods

2.1. Participants

Fifteen typically developing children participated in this study (7:8 M:F, age = 11.3 ± 4.1 years, 1.46 ± 0.18 m, and 44.2 ± 16.8 kg). Inclusion criteria were no self-reported pain or injuries to the lower limb that required hospitalization within the past 12 months. Exclusion criteria were any lower limb musculoskeletal injury that impairs their ability to walk or a medical history of surgical correction for a lower limb injury or deformity. Before study enrollment, all participants and guardians reviewed and signed a letter of informed consent approved by the University of Nebraska Medical Center’s Institutional Review Board.

2.2. Experimental Procedures

2.2.1. Research Design

This study was a block-randomized cross-over design where participants performed DRY treadmill walking trials followed by aquatic, or WET, treadmill walking trials. Walking speed presentation was randomized. Participants performed three 3-minute walking trials on a DRY and WET treadmill at 75%, 100%, and 125% of self-selected speed (Slow, Normal, and Fast respectively).

2.2.2. Electromyography

Participants were bilaterally instrumented with waterproof wireless surface EMG equipment (Figure 1) (Mini Wave Infinity Waterproof, Cometa, Milan, Italy; input impedance = 20 MΩ, common mode rejection ratio = 120 dB, bandpass filter 10–1000 Hz). Raw EMG data were collected from muscles that contribute to the impaired gait of children with CP and those responsible for mainly hip, knee, and ankle flexion/extension. Muscle activity of the tibialis anterior (TA), medial gastrocnemius (MG), rectus femoris (RF), and semitendinosus (ST) were sampled at 2000 Hz. Electrode sites were located and prepared following SENIAM guidelines (Hermens et al., 2000, 1999; Hermens and Freriks, 2005). Briefly: TA was palpated lateral to the anterior tibial crest during resisted dorsiflexion; MG was palpated on the posterior shank during resisted plantarflexion; RF was palpated along the midline of the anterior thigh during active knee extension; and ST was palpated on the medial posterior thigh during resisted knee flexion. Pre-gelled bipolar Ag/AgCl electrodes (Coviden disposable sEMG electrodes, Coviden, Dublin, Ireland) with dimensions of 30 mm by 24 mm were adhered after shaving and cleaning the skin with alcohol. Inter-electrode spacing was 2.5 cm. Each participant completed two 7 s isometric maximum voluntary contractions (MVCs) for each muscle group with a minimum 60 s rest between trials (Table 1) (Chuang and Acker, 2019a; Kato et al., 2002; Kingston and Acker, 2018). The maximum EMG signal between isometric MVC trials was used to normalize EMG magnitude to compare muscle activity during WET and DRY treadmill walking.

Figure 1:

Anterior (A), posterior (B), and sagittal (C, D) views of an instrumented typically developing child with wireless waterproof sensors. Red boxes indicate locations of waterproof EMG sensors. Note: 3D marker-based motion capture was collected at the time of this study, however kinematics was beyond the scope of this paper.

Table 1:

SENIAM guidelines and techniques used for Maximum voluntary contraction (MVC) procedures.

Muscle(s)	SENIAM guidelines	Study protocol
Medial Gastrocnemius	Plantar flexion of the foot with emphasis on pulling the heel upward more than pushing the forefoot downward Apply pressure against forefoot as well as against calcaneus	Participant in a standing position Participant will attempt plantar flexion while a researcher resists the force from the shoulder
Tibialis Anterior	Support leg above the ankle joint Ankle joint in dorsiflexion and the foot in inversion Apply pressure against the medial dorsal surface of the foot in direction of plantar flexion of the ankle joint and eversion of the foot	Participant seated on the edge of a massage table with their legs hanging over the edge Participant will attempt dorsiflexion of the ankle joint while an investigator applies force to plantar flex the ankle joint and holds the participant’s leg above the ankle joint
Semitendinosus	Press against the leg proximal to the ankle in the direction of knee extension	Participant laying prone on a massage table while an investigator flexes the participant’s leg Participant will attempt flexion of the knee while the investigator manually resists the participant’s leg motion
Rectus Femoris	Extend the knee without rotating the thigh while applying pressure against the leg above the ankle in the direction of flexion	Participant seated on the edge of a massage table with their legs hanging over the edge Participant will attempt extension of the knee while an investigator manually resists the participant’s leg motion

2.2.3. Inertial Measurement Units

Waterproof inertial measurement units (IMUs) recorded segmental motion bilaterally on the feet, shanks, thighs, and pelvis (WaveTrack Waterproof IMU, Cometa, Milan, Italy; full-scale acc sensitivity = ±8g; full-scale gyroscope sensitivity = 1000dps; dimensions: 36×25×10 mm). Gyroscope and accelerometer calibrations were conducted according to manufacturer guidelines by aligning all IMUs in the same orientation on a table to zero sensors. Following calibration, subjects were instrumented with IMUs. After all instrumentation procedures were completed, a static trial was conducted where the participant stood in a T-pose with the negative Y-axis of the sensors approximately in line with the participant’s sagittal plane. Raw IMU data were sampled at 142 Hz and processed using the manufacturer’s mixed 6 degrees of freedom (6DoF) sensor-fusion algorithm.

2.2.4. Determination of Self-Selected Speed

Determination of a participant’s self-selected walking speed followed a protocol used in clinical settings with alterations (Dal et al., 2010). Participants were blinded to the digital display panel and began walking on the treadmill at 0.5 mph. Investigators increased the speed in 0.1 mph increments until the participant reported an uncomfortably fast walking speed. Then, investigators decreased the speed in 0.1 mph increments until the participant reported an uncomfortably slow walking speed. This procedure was repeated three times, and speeds were averaged to determine the Normal walking speed. This procedure was completed separately for each treadmill condition.

2.2.5. Experimental Protocol

This study was conducted in the Lower Gait Lab and Aquatic Therapy Lab within the University of Nebraska Omaha Biomechanics Research Building. A summary of the study protocol is provided in Figure 2. Participants changed into appropriate clothing or a bathing suit. First, each participant’s Normal walking speed was determined on the DRY treadmill via the protocol noted in section 2.2.4. Participants then had both legs instrumented with wireless surface EMG and IMU equipment. MVCs were then performed for relevant muscles. Participants completed three 3-minute walking trials on the DRY treadmill (Precor TRM 835 V2, Precor, Woodinville, WA, USA) and a WET treadmill (300 Series, HydroWorx, Middletown, PA, USA) (Figure 3). Participants reported their perceived exertion for each treadmill and speed using the Children’s OMNI-walk/run RPE scale (Figure 4) (Fragala-Pinkham et al., 2015; Robertson et al., 2006). Participants then moved to the Aquatic Therapy Lab (~15 m walk) to perform WET treadmill walking trials. Once on the WET treadmill, the water level was set to the participant’s xiphoid process, and the participant’s Normal walking speed was determined again. During all WET treadmill walking trials there were no jets used to cause greater resistance during aquatic locomotion. A xiphoid process water level was used as previous research demonstrated that neck-depth water limits hip and ankle kinematics (Narasaki-Jara et al., 2020). All trials were performed barefoot. Participants could stop walking at any point, and the investigator would turn off the treadmill and note the elapsed time.

Figure 2:

Experimental protocol for DRY walking and WET walking. The order of walking speed trials were randomized for each treadmill environment. Each walking speed trial lasted up to 3-min.

Figure 3:

An instrumented participant walking during each treadmill environment. (A) Instrument participant on Conventional treadmill (DRY) (Precor TRM 835 V2, Precor, Woodinville, WA, USA). (B) Instrument participant on Aquatic treadmill (WET) (300 Series, HydroWorx, Middletown, PA, USA) filled to the xiphoid process.

Figure 4:

Children’s OMNI Scale of Perceived Exertion for walking/running (Robertson et al., 2006). Perceived exertion was defined as the question: How tired does my body feel after this treadmill trial?

2.3. Data Processing

Data processing was completed using Matlab (2021a, The Mathworks, Natick, MA, USA). Raw EMG data had bias removed, were full wave rectified, and were filtered using a dual-pass 2^nd order Butterworth filter with a cut-off frequency of 6 Hz to produce a linear envelope (Chuang and Acker, 2019b; Hubley-Kozey et al., 2013; Rutherford et al., 2011; Winter, 2009). Acceleration peaks from IMU sensors located on the feet were used to determine gait cycles and gait events during each walking trial. Heel strikes were determined using the greatest vertical acceleration peak, where initial contact occurred, and used to define gait cycles as heel strike to heel strike of the same foot. Toe-offs were determined using the next greatest acceleration peak, after heel strike, and identified separately for each treadmill and speed condition on time series figures. Any strides that were beyond 3 standard deviations of the mean stride time were deemed outliers and removed from the analysis.

Mean EMG activation was the main outcome variable and was calculated as the average EMG of a stride and then averaged across all strides within a condition. First EMG data were normalized to individual MVCs for magnitude and gait cycle for time from 0% to 100% of stride. After magnitude and time normalization, the mean of all strides was calculated to produce an average stride of 101 data points. This average EMG stride for each participant was used to create time series waveforms for each muscle in both treadmill environments across all speed conditions. Finally, the mean of all subject’s 101 data points was then taken, producing a single discrete value.

2.4. Statistical Analyses

Statistical tests were performed using R (RStudio 2022, PBC, Boston, MA, USA). All parameters were analyzed using 2 × 3 repeated measures ANOVA (factors; treadmill environment and walking speed). Dependent variables for this study were mean stride normalized muscle activity of respective muscles from the self-reported dominant leg and ratings of perceived exertion. Independent variables for this study were treadmill environment (DRY and WET) and walking speed (Slow, Normal, Fast). Effect sizes were quantified to observe any statistical differences between main effects (environment and speed) and the interaction effect (environment × speed). Post-hoc pairwise comparisons with Bonferroni corrections were calculated to determine statistically significant differences. The a priori significance level was set at α = 0.05.

3. Results

3.1. Muscle Activation

The mean and standard deviation of stride-normalized muscle activity of the TA, RF, MG, and ST across all conditions is reported in Table 2. An interaction of walking environment and speed was observed (p = 0.05) for mean muscle activity (Table 3). Only the RF and MG showed a significant effect of environment (p < 0.002), all muscles showed a significant effect of speed (p < 0.001), and only the TA and RF showed a significant interaction effect (p < 0.002). Equipment malfunctions occurred in rare situations, resulting in the loss of RF and ST signals that were withheld from statistical analyses for a total sample of 13 for the RF and 14 for the ST.

Table 2:

Mean (standard deviation) of walking speed, number of strides, lower extremity muscle activation of all strides, and ratings of perceived exertion in typically developing children during DRY and WET treadmill walking trials. All muscle activity magnitudes are normalized to %MVC.

	DRY			WET
	Slow	Normal	Fast	Slow	Normal	Fast
Walking Speed (m/s)	0.67 (0.20)	0.88 (0.27)	1.11 (0.33)	0.56 (0.14)	0.73 (0.18)	0.93 (0.23)
Number of Strides	105 (28)	123 (29)	140 (35)	82 (15)	94 (15)	101 (29)
OMNI-RPE (n = 15)	0.27 (0.59)	0.93 (1.62)	1.53 (2.00)	0.60 (0.91)	1.33 (1.45)	2.93 (2.76)
TA (n = 15)	10.5 (3.5)	11.9 (3.7)	14.8 (4.2)	10.1 (3.9)	12.8 (4.9)	16.8 (6.6)
RF (n = 13)	2.2 (1.3)	2.5 (1.5)	3.6 (2.3)	3.2 (1.7)	4.6 (2.2)	6.6 (2.8)
MG (n = 15)	10.9 (3.8)	12.5 (5.1)	14.7 (6.5)	5.1 (2.4)	6.1 (3.0)	7.8 (4.3)
ST (n = 14)	3.6 (1.5)	5.1 (2.8)	7.3 (4.8)	3.6 (1.9)	4.5 (1.9)	5.7 (2.3)

DRY, dry treadmill walking; WET, aquatic treadmill walking; Slow, 75% self-selected walking speed; Normal, 100% self-selected walking speed; Fast, 125% self-selected walking speed; OMNI-RPE, perceived exertion; TA, Tibialis Anterior; RF, Rectus Femoris; MG, Medial Gastrocnemius; ST, Semitendinosus.

Table 3:

Results from two-way repeated measures ANOVA for each muscle of interest and ratings of perceived exertion in typically developing children.

Variable	Effect	η2	P
	Environment	0.11	0.214
TA	Speed	0.85	< 0.001
	Environment × Speed	0.40	0.001
	Environment	0.56	0.002
RF	Speed	0.79	< 0.001
	Environment × Speed	0.42	0.001
	Environment	0.81	< 0.001
MG	Speed	0.65	< 0.001
	Environment × Speed	0.09	0.281
	Environment	0.09	0.267
ST	Speed	0.57	< 0.001
	Environment × Speed	0.12	0.184
	Environment	0.28	0.036
OMNI-RPE	Speed	0.40	< 0.001
	Environment × Speed	0.17	0.077

η², partial eta-squared effect size; p, p value; TA, Tibialis Anterior; RF, Rectus Femoris; MG, Medial Gastrocnemius; ST, Semitendinosus, OMNI-RPE, perceived exertion.

3.1.1. Tibialis Anterior

Simple main effect tests were performed to determine differences of TA activation at interaction levels. The simple effect of speed was significant in both environments, DRY (p < 0.001) and WET (p < 0.001). All pairwise comparisons were significantly different (p_adj < 0.001). On the DRY treadmill, changing walking speeds from Slow to Normal elicited a 13.0% increase, Normal to Fast elicited a 24.6% increase, and Slow to Fast elicited a 40.8% increase in mean TA muscle activity (Figure 5). Similarly, on the WET treadmill changing walking speeds from Slow to Normal elicited a 26.5% increase, Normal to Fast elicited a 31.0% increase, and Slow to Fast elicited a 65.8% increase in mean TA muscle activity. The simple effect of environment was not significant at any speed (p > 0.066); therefore, no post-hoc pairwise comparisons of environment were performed.

Figure 5:

Mean (%MVC) lower extremity muscle activity during DRY (red) and WET (blue) treadmill walking in typically developing children at Slow (75% self-selected), Normal (100% self-selected), and Fast (125% self-selected) speeds.

3.1.2. Rectus Femoris

Simple main effect tests were performed to determine differences of RF activation at interaction levels. The simple main effect of speed was significant in both environments, DRY (p = 0.012) and WET (p < 0.001). All pairwise comparisons were significantly different (p_adj < 0.044), except for the Slow-Normal comparison in the DRY environment (p_adj = 0.11). Walking on a DRY treadmill changing speeds from Normal to Fast elicited a 41.9% increase, and Slow to Fast elicited a 67.0% increase in mean RF muscle activity (Figure 5). Furthermore, walking on a WET treadmill changing speeds from Slow to Normal elicited a 44.1% increase, Normal to Fast elicited a 42.5% increase, and Slow to Fast elicited a 105.3% increase in mean RF muscle activity (Figure 5). Furthermore, the simple main effect of environment was significant at all speeds, Slow (p = 0.005), Normal (p = 0.001), and Fast (p = 0.004). All pairwise comparisons were significantly different (p_adj < 0.005). Mean RF muscle activity was 32.8% lower, 45.1% lower, and 45.4% lower during DRY treadmill walking compared to WET when walking at Slow, Normal, and Fast speeds (Figure 5, Figure 6).

Figure 6:

Lower extremity stride-normalized muscular activity (% MVC) during DRY (left column) and WET (right column) treadmill walking among Slow (green), Normal (red), and Fast (blue) walking speeds in typically developing children. Heel-strike corresponds to 0% stride, colored shaded areas represent standard deviation for each walking speed, and dotted colored vertical lines represent toe-off for each walking speed.

3.1.3. Medial Gastrocnemius

There was no interaction effect of MG activation, so main effect tests were performed to interpret the main effect of speed and environment. The main effect of speed was significant (p < 0.001). All pairwise comparisons of speed were significantly different (p_adj < 0.001). Therefore, walking on a treadmill changing speeds from Slow to Normal elicited a 15.8% increase, Normal to Fast elicited a 21.0% increase, and Slow to Fast elicited a 40.0% increase in mean MG muscle activity. The main effect of environment was significant (p < 0.001). Additionally, the pairwise comparison of environment was significantly different (p_adj < 0.001). Mean muscle activity for the MG was 50.2% lower during WET treadmill walking than DRY treadmill walking (Figure 5, Figure 6).

3.1.4. Semitendinosus

There were no interaction effects of ST activation, so main effect tests were performed to interpret the main effect of speed. The main effect of speed was significant (p < 0.001). All pairwise comparisons of speed were significantly different (p_adj < 0.005). Walking on a treadmill changing speeds from Slow to Normal elicited a 31.8% increase, Normal to Fast elicited a 36.3% increase, and Slow to Fast elicited a 79.6% increase in mean ST muscle activity (Figure 5, Figure 6). The main effect of environment was not significant (p = 0.267). Therefore, no post-hoc pairwise comparisons of environment were performed.

3.2. Ratings of Perceived Exertion

The mean and standard deviation of OMNI-RPE across all conditions can be found in Table 2. ANOVA results (Table 3) showed a significant effect of environment (p = 0.036), a significant effect of speed (p < 0.001), and a non-significant interaction effect (p = 0.077).

There was no interaction effect of perceived exertion, so main effect tests were performed to interpret the main effect of speed and environment. The main effect of speed was significant (p < 0.001). All pairwise comparisons of speed were statistically different (p_adj < 0.039). Walking on a treadmill changing speeds from Slow to Normal elicited a 162.3% increase, Normal to Fast elicited a 97.3% increase, and Slow to Fast elicited a 418.6% increase in perceived exertion. Furthermore, the main effect of environment was significant (p = 0.036). The pairwise comparison of environment was significantly different (p_adj = 0.007). Perceived exertion ratings were 78.0% greater during WET treadmill walking than DRY treadmill walking (Figure 7).

Figure 7:

Ratings of perceived exertion (OMNI-RPE) after DRY (red) and WET (blue) treadmill walking in typically developing children among Slow (75% self-selected), Normal (100% self-selected), and Fast (125% self-selected) speeds.

4. Discussion

The purpose of this study was to examine the effect of treadmill environment and walking speed on lower-limb muscular activity and perceived exertion in typically developing children. Results demonstrate that DRY treadmill walking at the Fast speed produced the greatest mean stride-normalized muscle activity for the MG compared to the other conditions, supporting our first hypothesis. However, the greatest mean stride-normalized muscle activity for the TA and RF occurred during WET treadmill walking at the Fast Speed. Furthermore, the greatest mean stride-normalized muscle activity of the ST was produced during Fast DRY treadmill walking, although not statistically different from the WET environment. Our second hypothesis was not supported as WET treadmill walking resulted in greater perceived exertion than DRY treadmill walking. Although it was not an outcome variable of interest, we observed differences in toe-off events between treadmill environments. In the DRY environment toe-off occurred between 60–65% stride, depending on walking speed, while in the WET environment toe-off occurred roughly 5% earlier between 55–60% stride (Figure 6).

4.1. Muscle Activation

To our knowledge, this is the first study to investigate lower extremity muscle activity during DRY and WET treadmill walking in typically developing children. Results from this study show that mean stride-normalized muscle activity was 50.2% lower during WET treadmill walking for the MG in typically developing children. This finding agrees with previous studies investigating lower extremity muscle activity during aquatic locomotion in healthy adults that reported 27% to 60% lower gastrocnemius muscle activity during aquatic locomotion (Masumoto et al., 2004; Silvers et al., 2014). A reduction in mean MG activity is speculated to result from the buoyancy of water reducing the weight-bearing force on an individual’s muscles and joints. This reduction is clearly visible in Figure 6 as the MG peaks are less than half in the WET environment compared to DRY.

In typically developing children, mean stride-normalized muscle activity for the RF was 48.8% to 83.0% greater during WET treadmill walking. Increased swing-phase RF muscle activity has been previously reported in healthy adults during aquatic locomotion compared to dry locomotion (Chevutschi et al., 2007; Silvers et al., 2014). In water, the hydrodynamic drag during swing phase may explain the greater activation observed as it is a bi-articulate muscle involved in both knee and hip movements. We observed moderate to high effect sizes for the main effects of environment and speed as well as the interaction effect. This may suggest that the hydrodynamic drag of extending the knee and flexing the hip through water during swing phase increases in a non-linear manner, thus requiring more muscle activity compared to walking on a dry treadmill where there is no effect of hydrodynamic drag during swing.

The greatest mean stride-normalized muscle activity of the TA was observed during Fast WET treadmill walking. This finding supports previous investigations of greater TA activation in water walking at fast speeds while also observing no statistical differences when walking at Slow and Normal speeds (Kaneda et al., 2008; Kato et al., 2002). Although post-hoc tests revealed no difference between environments at every speed, we assume that to overcome the hydrodynamic resistance of water, the TA produces greater activation (dorsiflexes the ankle) to prepare for heel strike. Similar to the RF, the majority of the difference in activation between environments is observed during swing phase (Figure 6) suggesting that increasing speed linearly would increase muscle activity exponentially as the hydrodynamic drag also increases exponentially.

No studies investigating muscle activity during aquatic locomotion have measured ST activation profiles. Our results show that greater mean stride-normalized ST muscle activity is produced the faster typically developing children walk; however, there is no difference between treadmill environments. Similarly, studies during aquatic and bodyweight-supported locomotion have also reported no significant differences in hamstring muscle activity between environments (Colby et al., 1999; Silvers et al., 2014). We speculate that children with crouch gait with spastic hamstring activity could benefit from this form of treadmill walking. During WET treadmill walking, the ST effectively shuts off during swing (Figure 6) and could help children with a crouched gait pattern to extend their legs to better assist with heel strike.

4.2. Ratings of Perceived Exertion

To our knowledge, this is the first study to investigate ratings of perceived exertion during DRY and WET treadmill walking in typically developing children. Our results show that greater perceived exertion ratings were reported during WET treadmill walking than DRY treadmill walking (Figure 7). This finding contrasts with a previous investigation of older adults (61.8 yrs) that found lower, but non-significant, RPE values while walking in water than on dry land at slow and moderate speeds (Masumoto et al., 2008). This difference may be due to population differences, such as age, physical activity capacity, and walking experience. Additionally, speed conditions were normalized to their self-selected speed within each environment which doesn’t account for the added drag resistance in the WET environment which increase in a non-linear manner. This may be the reason for the exponential increase of RPE observed in the Fast WET condition.

4.3. Limitations

To the best of our knowledge, participants in this study had no experience with the WET treadmill environment. We are unaware of the experience level that participants had with the DRY treadmill environment, as it was not an inclusion/exclusion criterion or captured via self-report. While there was not an explicit familiarization section, the determination of self-selected speed acted as a familiarization period for both treadmill environments as subjects became accustomed to the treadmill environment as their self-selected speed was determined.

Limitations of this study include the inability to measure body-weight offloaded and lack of metabolic measurements. When a child or adult is immersed to the symphysis pubis, umbilicus, or xiphoid process, it is speculated to unload approximately 40%, 50%, and 60–75% of their body weight (Badawy and Ibrahem, 2016; Becker, 2009; Fragala-Pinkham et al., 2009). However, measuring body weight while participants were in water would have given a definitive value of true body weight offloaded in our study. Lastly, measuring metabolic outcomes would have provided a more fulsome representation of energy expenditure during WET treadmill walking. Although there is value in RPE as a measure of self-reported effort, it is inherently subjective and quantitative metabolic would be more reliable and accurate.

5. Conclusion

In typically developing children, WET treadmill walking reduced the mean stride-normalized muscle activity of the MG and increased muscle activity of the RF. Given our results, clinicians and physical therapists should consider WET treadmill walking for gait rehabilitation for post-operative children that experience pain when loading their limb or are prescribed as weight-bearing to tolerance. This study provides novel data that quantifies how WET treadmill walking alters muscle activity in typically developing children. Future gait rehabilitation could be improved using our results for targeted muscle training paradigms. Previous research has shown that children with CP have weaker lower-limb muscles than typically developing counterparts and decreased walking efficiency (Dallmeijer et al., 2017). Thus, collecting data from children with CP will provide more concrete evidence to see if results from typically developing children translate to those with neuromuscular impairments.

Biographies

Joseph W. Harrington is a PhD student in Biomechanics and Kinesiology at the University of Nebraska Omaha in Omaha, NE, USA. His main research interests are on the biomechanics of gait and rehabilitation in children with neuromuscular disorders. He received his MS in Biomechanics from the University of Nebraska Omaha in 2022 and his BS in Bioengineering from the University of Massachusetts Dartmouth in 2017. His MS research investigated the effects of aquatic treadmill walking on muscular activity and joint kinematics in children with cerebral palsy and typically developing children.

Jose G. Anguiano Hernandez is an PhD student at the University of Utah in the Department of Health and Kinesiology in Salt Lake City, UT, USA. His current research focuses on the vascular physiology and biomechanics of amputees with Diabetes. He received is MS in Biomechanics and BS in Physics at the University of Nebraska Omaha in 2020 and 2022, respectively. His MS research investigated plantar loading in the propulsive foot during normal and assisted walking in patients with Type 2 Diabetes.

David C. Kingston is an Assistant Professor of Biomechanics and Director of the Movement Analysis Core in the Biomechanics Research Building at the University of Nebraska Omaha in Omaha, NE, USA. His current research focuses on neuromuscular rehabilitation and assessing mobility improvements following surgical and non-surgical treatments in pediatric and diabetic populations. He completed a postdoctoral fellowship at the Canadian Center for Health and Safety in Agriculture at The University of Saskatchewan, Saskatoon, Canada. He received his Ph.D. in Kinesiology from The University of Waterloo, Waterloo, Canada in 2019 with an MSc and BSc in Kinesiology and Health Studies from Queen’s University, Kingston, Canada in 2013 and 2011, respectively.