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Effects of Slackline Training on Postural Control, Jump Performance, and Myoelectrical Activity in Female Basketball Players

Santos, Luis; Fernández-Río, Javier; Fernández-García, Benjamín; Jakobsen, Markus D.; González-Gómez, Lucía; Suman, Oscar E.

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Journal of Strength and Conditioning Research: March 2016 - Volume 30 - Issue 3 - p 653-664
doi: 10.1519/JSC.0000000000001168
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Postural stability is required for staying upright and balanced during normal activities (33). It is also a key element in successful daily function (19), with loss of postural stability precluding many physical exercises and daily activities (39). Gollhofer (14) found postural control and neuromuscular activation to be key contributors to enhanced athletic performance in many different athletic pursuits. Hence, because sports demand balance and efficient movements, athletes must develop their postural stability/control system (PCS) throughout their careers. It is evident that success in sports such as basketball and volleyball requires great muscular power to jump high and move quickly. Nevertheless, as these athletes constantly are jumping and landing in unstable situations, PCS can be crucial for their performance and injury rate. McGuine et al. (27) showed that ankle sprains are almost 7 times more likely in high school basketball players with high sway scores (poor balance) than in those with low sway scores (good balance). Furthermore, because PCS is negatively related to the individual's height (8), postural balance training seems very important for these tall athletes.

Jumping performance (i.e., countermovement jump) is a well-established measure of motor and functional capacity in young individuals (16), the elderly (6), and athletes (21). In the game of basketball, jumping is a highly demanded motor ability (7). Jump performance is part of several defensive (e.g., blocking, rebounding, and stealing) and offensive skills (i.e., passing, rebounding, and shooting) performed by basketball players in practices and games (43). Thus, jump performance improvement is a very important facet of basketball training.

Slacklining is recreational activity that has gained popularity in recent years. In slacklining, people try to walk and maintain balance on a polyester band placed between 2 anchor points. “Slackline allows very high movement variability… provides only a small nonfixed base of support and… produces very fast mediolateral perturbations to the body” (32). It produces high postural balance demands when individuals try not to fall from the band. The main difference between slacklining and classical balance training methods (31) is that slacklining uses a moveable base rather than a fixed base of support (40). Previous studies on slackline have shown that it can improve postural stability in single leg stance on a stable surface (31). Studies have also been conducted in healthy adults and young children to assess the effects of slackline training on jumping performance (12,15). Unfortunately, none showed significant interaction effects. This randomized controlled study was undertaken to determine the effect of a supervised slackline training program on PCS and jump performance in female basketball players.


Experimental Approach to the Problem

A randomized fully controlled experimental design was used to examine the effects of supervised slackline training in the group of basketball players. Although all players followed the same basketball training program during the 6 weeks of the study, only a group of them (the experimental group [EG]) completed additional supervised slackline training during the general warm-ups of the basketball training sessions. This supervised slackline training was included as a cross-training tool in the routine of general warm-ups. Before and after the slackline training, all players underwent several laboratory tests (anthropometrical assessments, centre of pressure [CoP] measurements, surface electromyography [SEMG] recordings, and jump performance tests). In addition, ratings of perceived exertion (RPE) (28) and local ratings of perceived exertion (LRPE) (30) were established at the end of the slackline trainings, only for the EG.


A group of 25 female basketball players (age: 16–31 years) agreed to participate in this research study. The senior players (n = 11) competed at the national level, whereas the under 18 players (n = 14) competed at the state level. The study was designed and performed in accordance with the guidelines contained in the declaration of Helsinki and approved by the Regional Clinical Research Ethics Committee of the Principality of Asturias, Spain (No. 41/2014). An informed written consent was obtained from all participants. Those under 18 years of age signed the document along with their parents. None of the participants had any experience in slackline training. Inclusion criteria were as follows: female athlete, a minimum of 5 years of experience as a basketball player, regular attendance to practice and matches during the season (>90%), and belonging to the same basketball club. Individuals were excluded if they had a serious injury or had missed practice or matches (>10%). Before study enrollment, participants underwent a physical examination by the Basketball Club Medical Staff to validate their health status. For this study, participants were considered healthy if they had no self-reported neurological deficits, postural instability, vestibular or visual problems, musculoskeletal injuries, cardiovascular problems, injury to the neck, back pain, and lower extremity injuries for at least 6 weeks before the evaluation. Participants' characteristics are showed in the Table 1. Age, height, weight, body mass index, and the sum of 6 skinfolds (abdominal, suprailiac, tricipital, subescapular, thigh, and medial leg) using a skinfold caliper (Holtain, Crosswell, Crymych, Pembs., United Kingdom) were determined before and after training. Players were randomly assigned to an EG (slackline, N = 13) and a CG (no slackline, N = 12) through a simple draw among participants. Three dropouts occurred during the training period because of injuries (1 from the EG and 2 from the CG), and these participants were not included in the analysis. Players in both groups participated in the same weekly basketball training program, which included 4 sessions (90 minutes each) during 8 months. All sessions focused on technical and tactical skills, and 3 had an additional conditioning workload component (endurance and strength training).

Table 1
Table 1:
Demographics and baseline characteristics.*†


A group of female basketball players experienced a 6-week supervised slackline training program, developed as a cross-training tool for 3 of the weekly sessions, 5–9 minutes for each session, including training and resting time, which was conducted before the regularly scheduled warm-ups of the practical sessions, which included endurance, strength, and speed drills. The slackline program was fitted in the first half of the basketball season, before the winter break, when players were at a high conditioning level. Several Gibbon Slackline classic lines (ID Sports, Stuttgart, Germany) (length: 25 m, width: 5 cm) were used to develop slackline tasks. Slackline training sessions were held in a gym, using pillars as anchor points to fix the lines approximately 50 cm above the floor. The lines' length was the same throughout the whole training process (6 m). Several gymnastic mats were placed under the lines to provide a safe training environment. Slackline tasks were selected based on previous studies (22,31,32,35) and personal experience of the authors. All tasks were performed barefooted to maximize the impact of the balance workout. Three repetitions of each task were performed, with each task lasting 30 seconds and resting time after each task lasting 10 seconds. One assistant stood next to the slackline with one arm held upright and fully extended for the players to use it as a support. In the first and second weeks, players developed the following tasks: tandem stance, single stance on the right leg, and single stance on the left leg (4 minutes 30 seconds of total training time and 30 seconds of total resting time). Participants worked with minor support (assistant set one of their hands in the elbow of the player). Throughout the third week, the training program was focused on tandem stance without support, single stance on the right leg without support, single stance on the left leg without support, and lateral stance (surf) with minor support (6-minute total training time and 1-minute total resting time). During the fourth week, players performed tandem stance, single stance on the right leg, single stance on the left leg, and lateral stance (surf) (6-minute total training time and 1-minute total resting time). Players worked without support. The working plan of the fifth week was focused on single stance (right leg) without support, single stance (left leg) without support, lateral stance (surf) without support, 3 or 4 forward steps with minor support, and 3 or 4 backward steps with minor support (7 minutes 30 seconds of total training time and 1 minute 30 seconds of total resting time). Finally, in the sixth week, players performed the following tasks without any support: single stance on the right leg, single stance on the left leg, lateral stance (surf), 3 or 4 forward steps, and 3 or 4 backward steps (7 minutes 30 seconds of total training time and 1 minute 30 seconds of total resting time).

Center of Pressure Measurements

Center of pressure measurements were obtained using a footscan baropodometric platform from FreeMED Sensormedica, S.A.S. (Rome, Italy) (35). Data were registered and analyzed with Free-Step software (1.0.3 version) (Rome, Italy) (35). This technology allows studying the CoP position in 2 planes: sagital plane (for analyzing anteroposterior perturbations) and transverse plane (for mediolateral perturbations). A sampling frequency of 100 Hz with a cutoff frequency of 10 Hz was used in data collection following the recommendations of Ruhe et al. (33).

Because the participants were a group of athletes, the tests were designed to challenge their PCS and were performed over firm and compliant surfaces. Stance width was established at 17 cm because stance width is inversely related to body sway (29) with this effect diminishing beyond 15 cm (37). The tests conducted were bipedal support, left leg support, and right leg support. Participants performed these tests with open eyes. The firm surface of the baropodometric platform was transformed into a complaint surface by overlaying it with a 32-cm long flexible balance disc (used in rehabilitation), which weighed 1 kg and was 6 cm thick. Thus, the biomechanical PCS assessment incorporated static and dynamic conditions. All tests were performed barefooted following recommendations of the French Association of Posture for CoP measurements (1). Based on previous studies (27), the data acquisition duration was 10 seconds for every test.

Three types of CoP parameters were assessed: positioning parameters, medial positioning parameters, and dispersion parameters. Positioning parameters expressed PCS from a global point of view using length (CoP displacement), area (PCS precision area), the length/area relationship (mathematical index that expresses PCS efficiency), and speed (postural reactions to maintain balance). Medial positioning parameters were determined from the CoP dispersion in the anteroposterior and mediolateral directions (Ymean: the CoP position in the anteroposterior direction using the ellipse centre as a reference; Xmean: the CoP position in the mediolateral direction using the ellipse centre as a reference). Dispersion parameters refer to the CoP deviation degree from the positioning parameters (deltaY: the CoP rate in the anteroposterior direction; deltaX: the CoP rate in the mediolateral direction; RMS: the root-mean-squared amplitude of the CoP; RMSY: the root-mean-squared amplitude of the CoP in the anteroposterior direction; and RMSX: the root-mean-squared amplitude of the CoP in the mediolateral direction). According to Ruhe et al. (33), these CoP parameters are the most frequently assessed throughout the literature.

Preliminary practice trials were performed to ensure that the participants felt comfortable with the test conditions and understood the instructions (22). They were told to rest their gaze on a target (10 cm2 circle) that was elevated 1.65 m and situated 2.5 m away from the platform. During testing, participants held the nonstance leg at least 5 cm above the platform, and hands were held akimbo (19). Three attempts of each test were recorded, and the average data from the 3 tests were included in the statistical analyses, according to the recommendations of Ruhe et al. (33). Before recording, participants were asked to “stand as still as possible” (33). This methodology minimizes the effect of intrinsic physical differences among participants on the reliability of CoP measures (34). A resting time of 1 minute was provided after each trial. Participants repeated the test if they touched the ground with their contra lateral leg or grasped the test assistant, who was available to stop participants from falling.

Surface Electromyography

Myoelectrical activity was recorded with a Mega Biomonitor ME6000 8-channel system (Mega Electronics Ltd., Kuopio, Finland) (4). The recording electronic module contained 4 electromyography preamplifier cables (type MT-ME8P, analog differential amplifiers, 305 preamplifier gain, 6-mm thickness, 27-mm diameter, 125-g weight, IP20 enclosure class), a 32-bit microprocessor with RISC Architecture, a data memory card, and a USB PC interface (MegaWin PC software for Windows, 2.4 version). The signal processing of the device was analog bipolar raw with band pass filtering of 8–500 Hz (3 dB points). Ag/AgCl Medicotest Blue sensor electrodes type M-00-S were used at an interelectrode distance of 2 cm. All SEMG data were stored using the PC software previously mentioned. The signal was recorded online in raw form with a sampling frequency of 1,000 Hz. To characterize the relationship between CoP and myoelectrical activity, we recorded SEMG activity from the 3 major postural leg muscles during CoP tests: soleus, tibialis anterior, and peroneus longus (36). This process was developed according to the European recommendations for SEMG (17) and Hermens et al. (18). It included skin preparation, positioning participants in a starting posture, determination of sensor location, and placement and fixation of the sensor in the skin. Electrode paste (Redux Electrolyte Crème; Parker Inc., Fairfield, Connecticut, NJ, USA) was added to every electrode surface before measurements to maximize conductivity with the skin (41). Impedance was monitored before and after SEMG recordings through a bioimpedance device (SIGGI II—Impedance Meter, Falk Minow Services, Herrsching, Germany). Maximum skin impedance was accepted below 5 kΩ (12). Participants' dominant leg was determined using the Lateral Preference Inventory 16-item questionnaire, which measures hand, foot, eye, and ear preference (11). Most participants (92%) showed right leg dominance. Thus, to avoid an unbalanced SEMG data analysis, we conducted SEMG recordings over the right leg of all players.

Myoelectrical activity (in microvolts) data were stored and analyzed with MegaWin PC software for Windows (2.4 version). Surface electromyography data were quantified using the RMS and processed as a moving average over 100 milliseconds (4). As in the case of the CoP tests, the averaging data of the 3 SEMG tests (corresponding to the CoP tests) were included into the statistical analyses. Myoelectrical activity was expressed relative to percent maximum voluntary isometric contraction (MVC). Thus, isolated maximal voluntary isometric contractions tests were performed in muscles under study before testing, following SENIAM recommendations (17). For MVC testing, participants were first allowed to become familiar with the testing procedures, and then at least 3 trials lasting 3–5 seconds were performed in each test (with 1-minute rest period between trials). Participants were given strong verbal encouragement to maximize their performance (41). The SEMG values from MVC tests were used to normalize all SEMG data. Maximal SEMG values of each MVC test were taken as an average from a 1-second period. Thus, the average value of each MVC test was used to calculate a single average value for all MVC tests.

Jump Performance

After a standard warm-up (5-minute ergometer bicycling at 100 W) and 5 minutes of rest (20), players performed 2 tests on a contact time platform (Ergojump 1000 DigiTimes, Digitest, Oulu, Finland): countermovement jump (CMJ) test and a 30-second maximal performance jump test. Participants stood upright on the contact-time platform, and both tests were performed with both hands held akimbo. In the CMJ test, participants were instructed to jump as high as they could. Participants were given exact test instructions, described elsewhere (7). Participants performed 3 attempts of the CMJ test, with rest interval of 1 minute. The best trial of the 3 CMJs (flight time/flying height) was recorded for further analysis. For the 30-second maximal performance, participants jumped as many times as they could in 30 seconds (this test was performed once). A digital timer captured the number of jumps, time in air (and/or flying height), and power generated per body weight (watts per kilogram). The timer, which was connected to the platform, was activated by removal of the foot from the platform and stopped by contact of the foot with the platform. In all cases, the CMJ was performed first and followed by the 30-second maximal performance test. Before testing, participants were allowed to become acquainted with the testing procedures to prevent learning effects. Both jumping tests are reliable (24) and highly reproducible (5).

Ratings of Perceived Exertion

Morgan and Borg (28) showed that, during long intervals of work, the rate by which RPE changes is a sensitive indicator of the time at which self-imposed exhaustion occurs. In the widely used 6–20 Borg scale, a linear relationship exists between perceptual factors and physiological (oxygen uptake and heart rate) or physical (work rate) parameters (3). Basketball training includes physical, psychological, technical, and tactical components because the sport of basketball requires specific skills and outstanding physical fitness (27). Hence, the overall workload can be very demanding. It is not easy to include new exercises in a tight training routine. Thus, it is necessary to assess the workload of every new task. Consequently, RPE was included in the research project. The 6–20 Borg scale was explained to all participants before the beginning of the slackline training program. It remained in the participants' view throughout every session, and they were asked to rate their perceived exertion at the end of each one.

Local Ratings of Perceived Exertion

Nilsson et al. (30) validated a modified version of Borg's scale to estimate the perceived exertion in specific body parts (muscles) of wrestlers. We used this tool to assess the local workload of the slackline training program. At the end of each training session, participants were given an anatomical diagram showing anterior and posterior views of the body and asked to identify the areas (muscle groups) they felt had been exerted in the slackline tasks. The goal was to understand these types of exercises and incorporate them safely into the basketball players' training protocol.

Statistical Analyses

Data were analyzed using the Statistical Package for the Social Sciences (SPSS, 22.0 version; IBM, Chicago, IL, USA). First, a 1-way analysis of variance (ANOVA), selecting Levene's test, was used to assess the equality of variances among athletes (i.e., the homogeneity of variance [p > 0.05]) between the study groups before testing (25). Reliability of the CoP measures was calculated in all pre-CoP tests using the intraclass correlation coefficient (ICC), which reflects the ability of a test to differentiate between different individuals (42). Following Weir's recommendations (42), the data used to calculate ICC were obtained from a 1-way ANOVA, using the 1,1 ICC model (ICC1,1). The ICC is unitless; nevertheless, Landis and Koch (23) suggested that an ICC value between 0.2 and 0.4 can be considered fair, between 0.4 and 0.6 moderate, between 0.6 and 0.8 substantial, and from 0.8 to 1 almost perfectly reliable. The following formula was used: MSB − MSW/MSB + (k − 1) MSW (42).

Pretest and posttest descriptive statistics were also calculated. Finally, the general linear model for repeated measures was used to assess the effect of the training program, with time and intervention group as intrasubject and intersubject variables, respectively (repeated-measures ANOVA). For all statistical analyses, p ≤ 0.05 was accepted as significant. In addition, effect size (ƒ) was computed and reported when significant differences were obtained between groups. This formula was used: ƒ = (MEX − MC)/(SDC) (13). It is a measure of the effectiveness of a treatment (9). Effect size was defined as small for f > 0.1, medium for f > 0.25, and large for f > 0.40 (10).


One-way ANOVA showed no significant differences between EG and CG in independent variables (anthropometric characteristics and training condition) at baseline (Table 1).

Regarding reliability of the bipedal firm surface CoP test, ICC1,1 for length, area, length/area, speed, Ymean, Xmean, deltaY, deltaX, RMS, RMSY, and RMSX was 0.83, 0.87, 0.91, 0.84, 0.92, 0.87, 0.90, 0.88, 0.93, 0.83, and 0.88, respectively. Considering reliability of the right leg firm surface CoP test, ICC1,1 for length, area, length/area, speed, Ymean, Xmean, deltaY, deltaX, RMS, RMSY, and RMSX was 0.90, 0.84, 0.87, 0.82, 0.89, 0.91, 0.91, 0.82, 0.88, 0.85, and 0.81, respectively. Taking into account reliability of the left leg firm surface CoP test, ICC1,1 for length, area, length/area, speed, Ymean, Xmean, deltaY, deltaX, RMS, RMSY, and RMSX was 0.87, 0.91, 0.89, 0.83, 0.91, 0.86, 0.92, 0.92, 0.89, 0.83, and 0.92, respectively. Concerning reliability of the bipedal compliant surface CoP test, ICC1,1 for length, area, length/area, speed, Ymean, Xmean, deltaY, deltaX, RMS, RMSY, and RMSX was 0.88, 0.91, 0.89, 0.87, 0.89, 0.93, 0.92, 0.82, 0.90, 0.84, and 0.82, respectively. With respect to reliability of the right leg compliant surface CoP test, ICC1,1 for length, area, length/area, speed, Ymean, Xmean, deltaY, deltaX, RMS, RMSY, and RMSX was 0.86, 0.89, 0.93, 0.90, 0.89, 0.92, 0.91, 0.84, 0.87, 0.81, and 0.82, respectively. In relation to reliability of the left leg compliant surface CoP test, ICC1,1 for length, area, length/area, speed, Ymean, Xmean, deltaY, deltaX, RMS, RMSY, and RMSX was 0.87, 0.89, 0.89, 0.90, 0.91, 0.89, 0.95, 0.89, 0.88, 0.82, and 0.83, respectively.

Significant differences were detected in several CoP parameters before and after training in the EG, but not the CG (Tables 2 and 3). For the left leg on a compliant surface, length changed from 258.63 ± 171.89 to 172.70 ± 38.76 (p = 0.032; ƒ = 0.30), area from 337.54 ± 146.55 to 290.87 ± 184.01 mm (p = 0.048; ƒ = 0.41), speed from 228.00 ± 163.09 to 147.49 ± 41.87 mm·s−1 (p = 0.005; ƒ = 1.01), deltaY from 26.18 ± 15.72 to 20.23 ± 10.40 mm (p = 0.006; ƒ = 1.01), and deltaX from 22.22 ± 14.05 to 10.00 ± 2.39 mm (p = 0.016; ƒ = 0.97). For the right leg on a compliant surface, length changed from 207.50 ± 108.36 to 166.13 ± 51.53 mm (p = 0.005; ƒ = 0.26), speed from 197.66 ± 106.65 to 144.13 ± 52.21 mm·s−1 (p = 0.003; ƒ = 0.90), Ymean from 0.02 ± 0.02 to −0.014 ± 0.01 mm (p = 0.001; ƒ = 0), deltaY from 30.19 ± 22.75 to 24.13 ± 12.61 mm (p = 0.024; ƒ = 0.61), and RMSY from 2.86 ± 1.43 to 1.99 ± 1.09 mm (p = 0.003; ƒ = 0.87).

Table 2
Table 2:
Center of pressure measurements in the experimental group before and after training.*†
Table 3
Table 3:
Center of pressure measurements in the control group before and after training.*†

Neither study group showed any significant differences in SEMG recordings after training on either firm (Table 4) or compliant surfaces (Table 5).

Table 4
Table 4:
Surface electromyography recordings (% of maximum voluntary isometric contraction) in the experimental group (EG) and control group (CG) during center of pressure tests on a firm surface.
Table 5
Table 5:
Surface electromyography recordings (% of maximum voluntary isometric contraction) in the experimental group (EG) and control group (CG) during center of pressure tests on a compliant surface.

Analysis of a jump performance revealed significant differences in the EG. Flight time increased from 465.15 ± 23.56 to 490.42 ± 20.97 milliseconds (p = 0.014; ƒ = 3.21) and jump height increased from 26.62 ± 2.63 to 29.58 ± 2.47 cm (p = 0.038; ƒ = 1.36). In contrast, the CG showed no changes in flight time (449.17 ± 34.08 milliseconds before training vs. 448.10 ± 26.66 milliseconds after training) or jump height (25.00 ± 3.91 cm before training vs. 24.70 ± 3.59 cm after training). Mechanical power of the legs, as measured through the 30-second maximal performance jump test, did not improve in either EG (15.29 ± 2.40 W·kg−1 before training vs. 15.03 ± 1.49 W·kg−1 after training) or CG (13.99 ± 2.17 W·kg−1 before training to 13.17 ± 1.59 W·kg−1 after training).

EG participants reported an RPE of 12 ± 0.33 on the whole training program (“somewhat hard” in the 6–20 Borg scale) (Table 6). Analysis of LRPE revealed that quadriceps (20%), soleus (18%), and gastrocnemius (14%) received the highest ratings from participants (Table 6). Foot muscles (12%), tibialis anterior (9%), hamstrings (7%), peroneus longus (6%), rectus abdominis (6%), and gluteus (4%) were also mentioned by participants. Latissimus dorsi (3%), lumbars (2%), adductor longus (2%), deltoid (1%), trapezius (0.96%), brachialis (0.43%), pectoralis major (0.18%), sternocleidomastoid (0.09%), and brachioradialis (0.04%) were rarely mentioned.

Table 6
Table 6:
RPE and LRPE (%) in slackline training sessions.*


To our knowledge, this study is the first to assess the effects of supervised slackline training (as a cross-training tool) in the game of basketball. Our results showed that, in female basketball players, a 6-week slackline training program, applied 3 times a week, had significant positive effects on several PCS parameters measured on a compliant surface (left leg: length, area, speed, deltaY, and deltaX; right leg: length, speed, Ymean, deltaY, and RMSY). The program also produced significant gains in the CMJ. The slackline training was associated with an average somewhat hard rating of perceived exertion during the training sessions. Finally, the quadriceps and the gastrocnemius muscles were mentioned as the most exerted during the slackline training program.

Basketball players exhibited noteworthy improvements in 2 balance tests performed over a compliant surface. In the left leg test, positive effects were seen in several CoP positioning parameters (length, area, and speed). These findings are in accordance with previous studies on Slackline. Granacher et al. (15) found a decrease in total CoP displacements (length) in young, healthy, and active adults after performing slackline training 3 times per week for 4 weeks. Pfusterschmied et al. (32) reported a decrease in maximum velocity in a 10-second single stance CoP excursion test after a 4-week slackline program (10 sessions, 90 minutes each one) in 24 young healthy adults (12 male, 12 female). Donath et al. (12) demonstrated a reduced left leg dynamic sway in a 30 seconds single upright stance CoP excursion test in primary school students after 6 weeks of slackline training (5 times a week for 10 minutes everyday). Regarding the CoP dispersion parameters, our female basketball players showed improved deltaY and deltaX. These data agree with the findings of Keller et al. (22), who reported refinements in the right leg sway path in the anteroposterior and mediolateral axis in healthy subjects (12 males, 12 females) undergoing a 4-week slackline program (10 sessions, 2–3 sessions per week, 90 minutes each session). Previous studies have indicated that slackline can produce very fast mediolateral body perturbations (22,31), enhancing the PCS in mediolateral and anteroposterior directions. Regarding the right leg (over a compliant surface), positive effects were also seen on several positioning parameters (length and speed). These results agree with the ones obtained by Donath et al. (12), who reported a reduced right leg dynamic sway. Improvements shown in this study were stronger on the left leg. The basketball players in this study had a dominant right leg. The dominant leg tends to be stronger and more skillful than the nondominant one, demanding higher intensity stimuli than the nondominant leg to gain improvements. Additionally, significant improvements were found in the single stance tests and not in the bipedal ones, both over a compliant surface. The larger number of single stance slackline training tasks (over the tandem stance tasks) could have produced these results. Coaches and researchers should consider this issue in future projects. Finally, there were no significant improvements in any of the CoP parameters measured on a firm surface (bipedal, right leg, and left leg). Because slackline provides a highly movable base of support (31), improvements will be greater on tests carried over compliant surfaces. It is speculated that, if the goal is to enhance PCS over firm surfaces, the slackline band should have stronger tension to provide a firmer surface.

Six weeks of supervised slackline training were effective in improving jump performance measured through the CMJ. In a previous study, Santos et al. (35) reported that, in a group of 15 regional and national-level under 20 judoists (12 males, 3 females) after 4 weeks of slackline training (2 sessions per week, 60 minutes each) improved performance in the CMJ test. Granacher et al. (15) found improvements in the rate of force development of the plantar flexors; however, no positive effects were found in maximal torque of the plantar flexors, jumping height, maximal torque of the plantar flexors under isometric conditions, or rate of force development of the plantar flexor under isometric conditions. Similarly, Donath et al. (12) did not detect significant effects in the CMJ conducted in their primary-school students. We found that, in contrast to jumper performance, mechanical power (assessed by the 30-second maximal performance test) did not significantly improve after the slackline program. We speculate that the load of the slackline training program (approximately 5-minute working time per session, 3 times per week, for 6 weeks) was too low to produce significant gains. Longer and harder training plans are probably needed.

The lack of significant change in SEMG data obtained before and after training does not allow us to link the improvements in CoP measurements to neuromuscular activity. Nevertheless, SEMG recordings should not be ignored because they show a clear tendency. Exercising on unstable platforms is believed to put pressure on synergistic and stabilizing muscles (2). Our results on the compliant surface bipedal test showed stability improvements because SEMG activity of the plantar flexion and eversion antagonist muscles (tibialis anterior) was higher after training. Moreover, the bipedal and right leg firm surface tests also showed stability improvements because the SEMG activity of dorsiflexion antagonist muscles (soleus) was higher after training. Keller et al. (22) observed no significant changes in normalized EMG of selected lower limb muscles (soleus, gastrocnemius, and tibialis anterior) after 4 weeks of slackline training in healthy subjects. Donath et al. (12) stated muscle activity during static and dynamic balance testing on a force-plate revealed no significant group × time interaction in soleus, gastrocnemius, and tibialis anterior in children undergoing 6 weeks of slackline training. Finally, Pfusterschmied et al. (32) reported increased activation of the rectus femoris and a tendency toward greater rectus femoris to biceps femoris preparatory coactivation, but no other changes in EMG variables after 4 weeks of slackline training in healthy young adults. Longer slackline schedules are believed to yield significant SEMG improvements. McCaw and Friday (26) and Stone et al. (38) recommended free weights rather than machines, as they engage more synergistic, stabilizing, and antagonistic muscle groups, yielding better training results.

Ratings of perceived exertion scores indicated that the basketball players described the slackline training program as somewhat hard in the 6–20 Borg scale. In a previous study on slackline training, judo players defined the slackline training program as “fairly-light” (35). Although data are quiet similar, basketball players reported a higher score. This difference seems reasonable because the slackline training programs were different. However, results from both studies indicate that slacklining is not a hard exercise, and it can be easily included into any athlete's training schedule. Furthermore, researchers observed that the basketball players considered slacklining a fun challenging activity.

Basketball players indicated that the quadriceps, soleus, and gastrocnemius to be the most frequently used muscles during slacklining. Previous studies (35) have shown that different athletes (judoists) identify similar muscles after slackline training: gastrocnemius, hamstrings, and quadriceps. Our basketball players also mentioned the soleus and the tibialis anterior as important muscles in slacklining. This is a significant finding because Sozzi et al. (36) indicated that these muscles are 2 of the 3 major postural leg muscles (soleus, tibialis anterior, and peroneus longus). Data from both studies indicate that slacklining requires activation of the main lower limb muscles. These data should be considered in the design of training tasks. Nevertheless, more research is necessary to achieve more precise knowledge.

This study has several limitations. First, changes in the participants' PCS were assessed through CoP. Including an analysis of the center of mass would provide deeper insights into the effects of slacklining on athletes' PCS. Second, our basketball players had a heterogeneous performance level. It is speculated whether similar slackline training programs were tested on basketball players with a homogeneous performance level, deeper PCS, jump performance, and neuromuscular refinements would be expressed. Third, this study was conducted on female basketball players. Further studies should be conducted on male athletes. Finally, SEMG recordings were applied only on the participant's dominant leg. Potential differences in the neuromuscular adaptations between dominant and nondominant legs should be evaluated.

In summary, the current findings provide support for the use of slackline training as simple and safe training tool that could be introduced into female basketball players' training regimen without causing an overload.

Practical Applications

Results of this study have showed that a 12-week slackline training program can produce significant positive effects on female basketball players' PCS parameters measured on a compliant surface. Simple tasks during short periods of time were enough to produce those gains. Thus, they could be easily integrated into the athletes' specific training routine during the warm-up phase to avoid overloading the basketball players with too many training programs. In addition, this simple and brief slackline training program also produced significant gains in the athletes' jumping performance. Thus, it could be used as a specific training supplement. Moreover, the same slackline training can be used as prophylactic training because it expressed a clear tendency to improve ankle stability. It has been hypothesized that long-term slackline training could produce stronger ankle stability. The basketball players' RPE scores have also showed that slackline training is not a hard exercise. Thus, it can be used in all periods of training. The quadriceps and the gastrocnemius were revealed as the most exerted muscles while slacklining. Therefore, coaches should be aware of it when designing training sessions to avoid muscle overloads and/or injury relapses.


The authors would like to thank the coaches, players, and the Medical Staff of the Agrupación Deportiva Baloncesto Avilés (ABDA) from Aviles (Spain) for their committed participation in this research project.

The authors have no professional relationships with companies or manufacturers who will benefit from the results of this study. The results of this study do not constitute endorsement of the product by the authors or the National Strength and Conditioning Association.


1. AFP. Normes. Paris, France: Association Posture et Équilibre, 1985.
2. Anderson KG, Behm DG. Maintenance of EMG activity and loss of force output with instability. J Strength Cond Res 18: 637–640, 2004.
3. Borg G. Borg's Perceived Exertion and Pain Scales. Leeds, United Kingdom: Human Kinetics, 1998. pp. 2–8.
4. Borreani S, Calatayud J, Martin J, Colado JC, Tella V, Behm D. Exercise intensity progression for exercises performed on unstable and stable platforms based on ankle muscle activation. Gait Posture 39: 404–409, 2014.
5. Bosco C, Belli A, Astrua M, Tihanyi J, Pozzo R, Kellis S, Tsarpela O, Foti C, Manno R, Tranquili C. A dynamometer for evaluation of dynamic muscle work. Eur J Appl Phys 70: 379–386, 1995.
6. Bosco C, Komi PV. Influence of aging on the mechanical behaviour of leg extensor muscles. Eur J Appl Phys 45: 209–219, 1980.
7. Bosco C, Luhtanen P, Komi PV. A simple method for measurement of mechanical power in jumping. Eur J Appl Phys 50: 273–282, 1983.
8. Chiari L, Rocchi L, Cappello A. Stabilometric parameters are affected by anthropometry and foot placement. Clin Biomech (British, Avon) 17: 666–677, 2002.
9. Coe R. What is an “effect size”? CEM Centre, Univeristy of Durham, 2000. Available at: Accessed May 14, 2014.
10. Cohen J. Statistical Power for the Behavioral Sciences. Hillsdale, NJ: Lawrence Eribaum Associates, 1988.
11. Coren S. The lateral preference inventory for measurement of handedness, footedness, eyedness, and earedness: Norms for young adults. Bull Psychon Soc 31: 1–3, 1993.
12. Donath L, Roth R, Rueegge A, Groppa M, Zahner L, Faude O. Effects of slackline training on balance, jump performance & muscle activity in young children. Int J Sports Med 34: 1093–1198, 2013.
13. Glass GV, McGraw B, Smith ML. Meta-Analysis in Social Research. Beverly Hills, CA: Sage, 1981.
14. Gollhofer A. Proprioceptive training: Considerations for strength and power production. In: Strength Pow Sport (3rd ed.). Komi P.V., ed. Oxford, United Kingdom: Blackwell, 2003. pp. 331.
15. Granacher U, Iten N, Roth R, Gollhofer A. Slackline training for balance and strength promotion. Int J Sports Med 31: 717–723, 2010.
16. Harrison AJ, Gaffney S. Motor development and gender effects on stretch-shortening cycle performance. J Sci Med Sport 4: 406–415, 2001.
17. Hermens HJ, Freriks B. The SENIAM CD-rom (SENIAM 9) European Recommendations for Surface ElectroMyoGraphy Results of the SENIAM Project. Enschede, The Netherlands: Roessingh Research and Development, 1999.
18. Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G. Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyo Kinesiol 10: 361–374, 2000.
19. Jakobsen MD, Sundstrup E, Krustrup P, Aagaard P. The effect of recreational soccer training and running on postural balance in untrained men. Eur J Appl Phys 111: 521–530, 2011.
20. Jakobsen MD, Sundstrup E, Randers MB, Kaer M, Andersen LL, Krustrup P, Aagaard P. The effect of strength training, recreational soccer and running exercise on stretch-shortening cycle muscle performance during countermovement jumping. Hum Mov Sci 31: 970–986, 2012.
21. Kasovic M, Pribanic T, Medved V. Take-off and landing properties in top-level football players: A ground reaction force study. Kinesio. Int J Fund Appl Kinesiol 34: 182–191, 2002.
22. Keller M, Pfusterschmied J, Buchecker E, Müller E, Taube W. Improved postural control after slackline training is accompanied by reduced H-reflexes. Scand J Med Sci Sports 22: 471–477, 2012.
23. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 33: 159–174, 1977.
24. Markovic G, Disdar D, Jukic I, Cardinale M. Reliability and factorial validity of squat and countermovement jump tests. J Strength Cond Res 18: 551–555, 2004.
25. Martin WE, Bridgmon KD. Quantitative and Statistical Research Methods: From Hypothesis to Results. San Francisco, CA: John Wiley & Sons, 2012. pp. 42–43.
26. McCaw ST, Friday J. A comparison of muscle activity between a free weight and machine bench press. J Strength Cond Res 8: 259–264, 1994.
27. McGuine TA, Greene JJ, Best T, Leverson G. Balance as a predictor of ankle injuries in high school basketball players. Clin J Sport Med 10: 239–244, 2000.
28. Morgan WP, Borg GAV. Perception of effort in the prescription of physical activity. In: The Humanistic and Mental Health Aspects of Sports, Exercise and Recreation. Craig T., ed. Chicago, IL: American Medical Association, 1976. pp. 126–129.
29. Mouzat A, Dabonneville M, Bertrand P. The effect of feet position on orthostatic posture in a female sample group. Neurosci Lett 365: 79–82, 2004.
30. Nilsson J, Csergö S, Gullstrand L, Tveit P, Refnes PE. Work-time profile, blood lactate concentration and rating of perceived exertion in the 1998 Greco-Roman Wrestling World Championship. J Sports Sci 20: 939–945, 2002.
31. Pfusterschmied J, Buchecker M, Keller M, Wagner H, Taube W, Müller E. Supervised slackline training improves postural stability. Eur J Sport Sci 13: 49–57, 2013.
32. Pfusterschmied J, Stöggi T, Buchecker M, Lindinger S, Wagner H, Müller E. Effects of 4-week slackline training on lower limb joint motion and muscle activation. J Sci Med Sport 16: 562–566, 2013.
33. Ruhe A, Fejer R, Walker B. The test-retest reliability of centre of pressure measures in bipedal static task conditions—A systematic review of the literature. Gait Posture 32: 436–445, 2010.
34. Salavati M, Hadian MR, Mazaheri M, Negahban M, Ebrahimi I, Talebian S, Jafari AH, Sanjari AM, Sohani SM, Parnianpour M. Test-retest reliability of center of pressure measures of postural stability during quiet standing in a group with musculoskeletal disorders consisting of low back pain, anterior cruciate ligament injury and functional ankle instability. Gait Posture 29: 460–464, 2009.
35. Santos L, Fernández-Río J, Fernández-García B, Due Jakobsen M. The effects of supervised Slackline Training on postural balance in judoists. Med Sport 67: 539–553, 2014.
36. Sozzi E, Honeine JL, Do MC, Schieppati M. Leg muscle activity during tandem stance and the control of body balance in the frontal plane. Clin Neurophysiol 124: 1175–1186, 2013.
37. Stoffregen TA, Villard S, Chen FC, Yu Y. Standing posture on land and at sea. Ecolog Psychol 23: 19–36, 2011.
38. Stone MH, Plisk SS, Stone ME, Schilling BK, O'bryant HS, Pierce KC. Athletic performance development: Volume load-1 set vs. multiple sets, training velocity and training variation. Strength Cond J 20: 22–31, 1998.
39. Taube W, Gruber M, Gollhofer A. Spinal and Supraspinal adaptations associated with balance training and their functional relevance. Acta Physiol 193: 101–116, 2008.
40. Taube W, Leukel C, Golhofer A. Influence of enhanced visual feedback on postural control and spinal reflex modulation during stance. Exp Brain Res 188: 353–361, 2008.
41. Tikkanen O, Haakana P, Pesola AJ, Häkkinen K, Rantalainen T, Havu M, Pullinen T, Finni T. Muscle activity and inactivity periods during normal daily life. PLoS One 8: e52228, 2013.
42. Weir JP. Quantifying test–retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res 19: 231–240, 2005.
43. Ziv G, Lidor R. Vertical jump in female and male basketball players: A review of observational and experimental studies. J Sci Med Sport 13: 332–339, 2010.

balance; CMJ; LRPE; RPE; SMEG; sway

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