Biofeedback for Improved Performance

The arousal-performance relationship has been investigated with multi-dimensional arousal assessments such as global state anxiety, a measure of nervousness or apprehensiveness at a particular time; cognitive state anxiety, a measure of worry at a particular time, and; somatic state anxiety, a measure individual perception of physiological activation (Gould and Udry, 1994). Gould and Krane (1992) define emotional arousal as the dynamic physiological and psychological activation that varies between deep sleep and intense excitement. According to Gould and Udry (1994), arousal when referred to in the context of sport, refers to how intense, excited, nervous, or emotionally activated an athlete is prior to or during competition.

The Yerkes-Dodson inverted-U hypothesis states that as arousal increases performance improves until an optimal or moderate amount of arousal is reached, beyond which, performance slowly declines (Williams, Landers, & Boutcher, 1993). The inverted-U, however, does not take into account the multi-dimensional nature of the arousal construct. According to the catastrophe model proposed by Hardy and Parfitt (1991), physiological arousal or somatic anxiety are related to performance in an inverted-U under conditions of low cognitive anxiety and worry. Conversely, when cognitive anxiety is high, increases in physiological arousal are related to performance only until a threshold point is reached, after which a sudden decrement in performance, or catastrophe, will occur. According to Gould and Udry (1994), understanding the combined interaction between cognitive anxiety, physiological arousal, and performance is more important for the sport psychologist than the understanding of each value separately.

Getner, Fisher, and Wrisberg (2004) surveyed a group of Division I college athletes and coaches and reported the most important sport psychological topics of interest were arousal regulation, stress management and relaxation. Similar results were reported previously for Olympic athletes by Gould, Murphey, Tannen, and May (1991). The perceptions of physiological and emotional stressors by the athlete, in conjunction with situational concerns, mediate potential anxiety created by the competitive environment (Blumenstein, Bar-Eli, & Tenenbaum, 1997). Prior to competition, athletes must find and maintain ideal levels of arousal to facilitate optimal performance. Sport psychologists have thus implemented mental training strategies to help athletes regulate and achieve an optimal level of arousal in order to enhance performance, including: muscle relaxation and deep breathing, autogenic training, imagery, and adaptive cognitive behavioral interventions in order to prepare athletes to confront or handle a stressor, cope with feelings of being overwhelmed, and reinforce self-statements for effective coping (Blumenstein et al., 1997; Cox, 2006; Gould and Udry, 1994; Myers, Whelan, & Murphy, 1996; Rotella & Lerner, 1993). According to Gould and Udry (1994), effective implementation of arousal regulation strategies must take into account the interactions between varying levels of cognitive anxiety and physiological arousal. Gould and Krane (1992) suggest that arousal be assessed using multidimensional constructs including a physiological arousal component and a cognitive interpretation-appraisal component.

Biofeedback, which provides physiological feedback to assist self-regulation, is suggested to be one of the most powerful techniques for enhancing the learning of arousal self-regulation by athletes (Bar-Eli, Dreshman, Blumenstein, & Weinstein, 2002). The technique of biofeedback utilizes instruments which provide measurements of physiological functions that are not typically under voluntary control (Zaichkosky & Takenaka, 1993). Via the use of external signals and cues, biofeedback allows the athlete or subject to increase voluntary control over physiological processes (Pop-Jordanova & Gucev, 2010). Sport psychologists have used biofeedback, often in conjunction with relaxation techniques, mental imagery, or autogenic training to improve self-regulation and enhance performance (Pretruzzello, Landers, and Salazer, 1991).

To better understand the relationship between arousal-regulation with biofeedback and performance the following sections will: describe the physiological indices of arousal measured, review literature investigating the effect of biofeedback on performance, discuss the application of biofeedback in competition, and suggest directions for future research.

Physiological Indices Measured

During biofeedback, changes in psychological activation and arousal are related to the changes in physiological activation. The most common physiological measures provided via biofeedback in arousal regulation have been heart rate (HR), blood pressure (BP), muscle activity measured via electromyogram (EMG), skin conductance measured via electrodermalgram (EDR), and brain waves measured via electroencephalogram (EEG) (Zaichkowsky and Fuchs, 1988). To better discuss the impact physiological regulation via biofeedback on arousal the following sections will be presented: heart rate, muscle tension, and electro-cortical activity.

Heart Rate

Increased psychological arousal and anxiety has been shown to manifest physiologically in an elevated heart rate (HR) (Cox, 2006). Regulation of heart rate has therefore been suggested as a method to reduce arousal (Zaichkosky and Fuchs, 1988).  McKinney, Gatchel, Brantley, and Harrinton (1980) investigated the effects of chronic HR slowing with biofeedback on self-reported anxiety. Subjects were split into two groups. Both groups were instructed to reduce HR, however only one group was provided with biofeedback. Subjects underwent 18 one hr sessions conducted 4 to 5 times each week over the course of 5 to 6 weeks. Heart-rate slowing with biofeedback was associated with lower state anxiety, and the decrement in anxiety increased across training sessions. According to the authors, chronic HR reduction training with biofeedback produce the consistent and stable reductions in heart rate needed to significantly impact state anxiety.

Biofeedback has also been used to reduce HR during dynamic exercise. Goldstein, Ross, and Brady (1977) investigated the effect of biofeedback training on HR regulation following an acute bout of dynamic exercise. Exercise was conducted on a treadmill at a fixed speed of 4 km/hr and 6% grade. An experimental-control was instructed to reduce HR following exercise and provided with visual feedback for 5 sessions. During the next 5 sessions subjects were instructed to reduce HR without visual feedback utilizing the previously learned strategies. In the control-experimental group subjects received instructions to reduce HR following exercise for the first 5 sessions without visual feedback. Over the next 5 sessions, subjects were again instructed to reduce HR with the aid of visual feedback. Goldstein et al. (1977) reported that following feedback training subjects maintained the ability to reduce HR without the aid of feedback. The control-experimental group, however, was unable to reduce HR with or without the aid of visual feedback. Thus, healthy participants can learn to control HR responses to mild exercise by using HR biofeedback; however, HR reduction as a result of unassisted feedback are unlikely and therefore HR biofeedback should be applied throughout the first sessions of exercise (Goldstein et al., 1977).

In a follow up study, Alvarez and Villamarin (2001) investigated the effects of biofeedback assisted voluntary HR reduction training on differing relative intensities of exercise compared to unassisted voluntary HR reduction training. Subjects were split into 4 groups: Group 1 exercised at 50% max HR and received biofeedback; Group 2 exercised at 30% max HR and received biofeedback; Group 3 and 4 exercised at 50% and 30% max HR, respectively, and received only verbal instructions. Subjects performed five 8 min bouts of exercise followed by a 4 min break where voluntary HR control was performed. Alvarez and Villamarin (2001) reported subjects trained with HR biofeedback were better able to attenuate exercise induced increases in HR than subjects trained with verbal instructions alone. Subjects trained with biofeedback were able to reduce HR by 5 beats/min and 3.3 beats/min following exercise at 50% and 30% max HR, respectively. In contrast, subjects trained with verbal instruction were only able to reduce HR by 0.4 beats/min and 1.4 beats/min following exercise at 50% and 30% HR max, respectively. Greater consistency was also exhibited in the groups trained with biofeedback, such that all subjects were able to reduce HR, while HR both increased and decreased in the verbally instructed group.

Researchers have investigated the relationships between HR acceleration and deceleration prior to skill execution and aiming performance. Molander and Backman (1989) reported significant reductions in performance when HR acceleration was performed prior to skill execution, while Boutcher and Zinsser (1990) reported that HR deceleration was associated with enhanced performance. Future research, therefore, is needed to investigate the relationship between HR reduction training with biofeedback and performance in aiming sports such as golf, archery, and free-throw shooting during competition situations.

Muscle Tension

Anxiety and elevated arousal has been shown to be related to increases in muscular tension and activity (Thomas, Tiber, & Schireson, 1973). Researchers have therefore used EMG biofeedback to help athletes reduce muscle tension in order to improve the economy of muscular effort and enhance performance (Petruzzello et al., 1991). Landers (1988) reviewed 10 studies examining the performance enhancing effects of EMG biofeedback and concluded that reductions in muscle tensions via EMG biofeedback do not significantly improve performance compared to control groups. Several issues arise when investigating relationships between altering muscular tension via EMG biofeedback and performance. First, there is limited research documenting differences in muscular tension between successful and unsuccessful performances, or between elite and amateur athletes in varying sports. Second, the site of EMG activity needs to be standardized. Previous researchers have measured activity at the frontalis muscle (Zachowsky & Fuchs, 1988). The frontalis muscle has been shown to be unrelated to general muscle activity at rest (deVries, 1968), and therefore changes in activity may not reflect systemic changes in muscular tension. Future research should include discussions with coaches and athletes regarding the muscle groups most important to various sport skills. Finally, EMG values obtained must be measured relative to the 100 percent maximal voluntary contraction, rather than absolute displays as tissues have different thicknesses and electrical outputs between individuals (Petruzzello et al., 1988).

Electrical-Cortical Activity

The monitoring of brain waves via EEG activity during varying tasks has been conducted to examine the relationship between cortical activation and cognitive and emotional tasks. Ray and Cole (1985) reported that slightly elevated alpha wave activity was associated with relazation and attentional focus, while beta wave activity was related to cognitive processes.  In addition, theta waves (4-7 Hz) have been suggested to be partially representative of a positive emotional state (Aftanas & Golocheikine, 2001; Kamiya, 1968). Hatfield, Landers, and Ray (1984) measured continuous EEG activity during rifle shooting in right-handed marksmen. The researchers reported relaxation in left hemisphere of the brain, measured by a reduction in cortical activation, 7.5 sec prior to pulling the trigger. In addition, other researchers have reported that left hemispheric EEG activity decreases while right hemispheric EEG activity does not change prior to improved shooting performance (Hatfield et al., 1984; Hatfield, Landers, & Ray, 1987; Salazar, Landers, Petruzzello, Han, Crews, & Kubitz, 1990).

Other researchers have examined the relationship between slow potential changes and task execution (Zaichkosky & Fuchs, 1988). According to Petruzzello et al. (1988), slow potentials are the slow electrical potential shift that develops in the brain during the period prior to an altering stimulus. Slow potentials may be electrically negative or positive. Positive slow potentials reflect a consumption of cerebral resources while negative potentials most likely relate to the state of preparation and mobilization of cerebral resources for the ensuing response (Birbaumer, Lutzenberger, Elbert, Rockstroh, & Schwarz, 1981). Use of slow potential EEG biofeedback has been shown to enhance reaction-time performance and attenuate performance decrements during vigilant tasks involving signal detection (Rockstroh, Elbert, Lutzenberger, & Birbaumer, 1982).

Biofeedback and Performance

In physical and skills training athletes are continuously evaluating physical performance via self feedback and peer and/or coach feedback. Psychoregulation training with biofeedback, therefore, may be seamlessly implemented into the daily routine of athletes because biofeedback serves as an extension of the feedback-evaluation process already performed by the athlete (Blumenstein, Bar-Eli, & Tenenbaum, 1997). Because different levels of arousal are required to perform optimally in various sports, the following sections will discuss the research investigating the effect of biofeedback on performance in the following activities: swimming, archery and shooting, and the performing arts.

Swimming

Bar-Eli, Dreshman, Blumenstein, and Weinstein (2002) investigated the effectiveness of psychoregluation training with biofeedback on youth swimmers. 31 male and 7 female subjects between 11 and 14 years of age volunteered for 38 sessions over the course of 14 weeks. Athletic performance measurements and technique evaluations were performed prior to training, at week 8, and following the training program. The treatment group received psychoregulation training in arousal regulation and imagery in conjunction with biofeedback for 35 min prior to practice. Biofeedback was provided in the form of HR, EMG, and galvanic skin response (GSR). The control group underwent various relaxing activities such as quite music, nature movies, and table games for 35 min prior to practicing. Both groups received the same athletic training.

Bar-Eli et al. (2002) reported a greater rate in skill performance and a reduction in 50 m freestyle times in youth swimmers following biofeedback and mental training in comparison with controls. There was also a significant improvement in the treatment group, but not the control group, when comparing week 8 and week 14 technique evaluations and swim time. According to Bar-Eli et al. (2002), ongoing psychoregulation training with biofeedback in conjunction to athletic training will lead to enhanced swimming performances in youth athletes than athletic training alone.

Archery and Shooting

Landers et al. (1991) investigated the effects of electrocortical biofeedback training in pre-elite archers to determine whether EEG biofeedback training improves archery performance. Subjects were randomly assigned into one of three groups: the “correct group” received feedback designed to increase left temporal low frequency activation; the “incorrect group” received biofeedback training designed to increase activity in the right hemisphere in order to control for motivational or expectancy effects associated with the use of novel equipment, and; a control group received no biofeedback training. Each group underwent pre- and post-trial testing, where archery performance was assessed and EEG measures were taken. Subjects performed 45-75 min of biofeedback training in the biofeedback groups prior to post-trial testing, while the control group relaxed for 45 min. Biofeedback was provided via microcomputer display. Subjects were provided with two bars, the top bar reflecting left hemisphere activity, and the bottom bar reflecting right hemisphere activity. The correct group was instructed to move the top bar to the right side of the screen while the incorrect group moved the bottom bar. Biofeedback was provided to assist subjects with producing a -40 µV shift. Following achievement of -40 µV shifts, biofeedback was removed and subjects were given pass/fail verbal feedback regarding the ability to produce a -40 µV shift. Next, subjects were instructed to produce -40 µV shifts in a shooting stance. Training ended when subjects could consistently produce a -40 µV shift in the shooting stance.

Landers et al. (1991) reported increases in left hemispheric alpha and beta wave activity but no changes in right hemispheric wave activity in the “correct” training group following left hemispheric activation with EEG biofeedback. A significant increase right hemispheric beta activity occurred following right hemispheric activation with biofeedback in the “incorrect group”. Left hemispheric activation training with biofeedback resulted in improved archery performance. No significant differences between pre- and post-trial scores were reported for the control group; however, there was a reduction in performance in the group that performed right hemispheric activation with EEG biofeedback. Specifically, the correct biofeedback training group improved accuracy on target by 1.66 cm whereas a loss of accuracy by 1.87 cm was recorded for the incorrect biofeedback training group. According to Ray and Cole (1985), increases in right hemispheric beta activity prior to skill execution are associated with cognitive processing. In high level athletes the execution of a skilled task is autonomous, and increased cognitive processes prior to execution are likely to negatively affect performance. Landers et al. (1991) partially attributed the enhanced relaxation following left hemispheric activation training with biofeedback for the improved performance in pre-elite archers. Future research should be conducted to determine if biofeedback training may benefit novice archers move from a cognitive stage of learning to an autonomous stage. Furthermore, more research is needed to examine the impact of relaxation training with EEG biofeedback on other sports that involve skilled task execution, such as the shoot-out at the end of a soccer match or hockey game. In addition, Landers et al. (1991) demonstrates that inappropriate methods of training with biofeedback can actually harm performance; therefore, more research is needed to distinguish between beneficial and harmful forms of psychological training with biofeedback.

A major limitation in Landers et al. (1991) was that EEG changes in slow potential activity could not be measured during competition due to electrical interference in low frequencies. Future research is needed to measure slow potential activity during competition to investigate the chronic adaptations and performance enhancements of biofeedback.

Performing Arts

Decreasing performance anxiety and reducing arousal levels has been shown to improve the ability and confidence of performing artists (Kendrick, Craig, Lawson, & Davidson, 1982); therefore, providing performing artists with biofeedback to enhance arousal regulation may improve musical and dance performance. Egner and Gruzelier (2003) investigated the relationship between EEG biofeedback with relaxation and attention training on musical performance in collegiate performers. Two separate experiments were conducted. In the first, subjects were split into three groups: group 1 received EEG biofeedback and was trained to enhance sensorimotor rhythm (SMR) and beta1 waves for a 5 week protocol followed by 5 weeks of training to enhance theta over alpha wave activity (a/t); group 2 received physical fitness and mental skills training; and, group 3 (control) received no training. In the second experiment a different cohort of subjects were split into 5 groups and trained separately on: a/t biofeedback training, beta1 biofeedback training, SMR biofeedback training, physical exercise, or one-on-one musical training (Alexander technique group). The purpose of experiment two was to contrast performance changes between biofeedback groups and comparison groups undergoing alternative interventions. Biofeedback subjects completed two 15 min sessions per week over the duration of the studies while the Alexander group took part in one 30 min session weekly. Musical performance was assessed prior to and subsequent to each training protocol. Subjects selected and performed two 15 min musical pieces given in front of a panel of internal assessors. The performances were recorded and rated on a 10-point scale by four external judges whom were blind to the order of the performances and groups of treatments.

Egner and Gruzelier (2003) reported significant improvements in musical performance following EEG biofeedback training in overall quality, rhythmic accuracy, emotional commitment and conviction, and stage presence. To rule out enhancements due to reduced anxiety, all three groups were assessed and no significant differences in anxiety reduction were reported between the three groups. In experiment two, only the a/t training group displayed significant improvements in musical performance following 10 weeks of biofeedback training. There were no significant differences in performance reported for the SMR, beta1, physical exercise, or Alexander training groups. In addition, there were no significant differences in anxiety reduction reported between groups following training intervention. Egner and Gruzelier (2003) conclude that enhancing slow wave potentials via increasing theta waves over alpha waves with biofeedback is beneficial to improving musical performance under stressful conditions amongst collegiate musicians.

Raymond, Sajid, Parkinson, and Gruzelier (2005) investigated the effects relaxation training by increasing theta wave activity over alpha (a/t) waves and heart rate variability (HRV) biofeedback on dance performance in competitive collegiate dancers. The researchers hypothesized that both forms of mental training would enhance performance in differing ways. Twenty four subjects were split into 3 groups: an a/t group, and HRV group, and a control group. The a/t and EEG group completed 20 min of relaxation training for 10 sessions.

During a/t training subjects were instructed to relax and focus on deep breathing. Biofeedback was provided via headphones such that when alpha waves power was high subjects heard a “babbling brook” and when theta wave power was higher subjects heard “crashing waves”. When the sounds were heard, subjects were instructed to visualize optimal dancing. HRV feedback was provided to subjects in the form of a numerical score. Subjects were instructed to breath slowly at normal depth. Control participants did not undergo any mental training. All groups continued practicing dance skills as normal. Dance performance assessments were carried out prior to and following training by qualified dance judges on technicality, musicality, timing, partnering skill, performing flair and overall execution. To control for bias judges were blind to treatment groups.

Raymond et al. (2005) reported relaxation training with EEG and HRV biofeedback resulted in improved dance performance compared to controls. Biofeedback in general significantly improved the subset of overall execution, but had no effect on musicality, partnering skill, or performance flair. EEG feedback exerted the greatest influence on timing while HRV feedback most influenced technicality. The authors suggest that higher levels of relaxation via enhanced a/t wave activity followed by mental imagery may have facilitated the increase in performance. More research, however, is needed to investigate the relationship between theta wave activation, imagery, and physical performance.

Application of Biofeedback

Blumenstein, Bar-Eli, and Tenenbaum (1995) developed a two-stage method using biofeedback to help athletes mentally train for competition. In the first stage, the athlete is trained using biofeedback in order to consciously control psychophysiological responses. In the second stage, the athlete learns to voluntarily shift and sustain varying levels of arousal. The two-step method of biofeedback when combined with autogenic training and imagery was shown to significantly augment the physiological components of arousal and improve 100 m sprint times. Blumenstein et al. (1997) expanded the two stage model into a five-step procedure. Step 1 involves introducing the athlete to biofeedback and takes place in a laboratory and is designed to teach the athlete mental state control via psychophysiological feedback. Successful completion of step 1 requires the athlete to achieve and maintain a deep relaxation state, which is then followed by imagery training. Step 2 requires the sport psychologist to identify the most efficient biofeedback response modality with regards to the individual characteristics of the athlete and the needs of the sport. Step 3 involves integrating the use of biofeedback in the natural environment. Specifically, Blumenstein et al. (1997) suggest presenting the athlete with pre-recorded audio and visual material to gradually elevate competitive stressors as the athlete goes through previously learned relaxation-excitation cycles.

Step 4 and 5 is designed to transition the use of biofeedback into the competitive environment of the athlete. In step 4 the athlete uses relaxation-excitation training with biofeedback to mentally begin preparing for a future competition. Relaxation-excitation cycles are performed before, during, and after training via portable biofeedback devices in the training environment. Autogenic relaxation techniques are first used prior to training as part of the warm up. Then, imagery is combined with biofeedback as the athlete visualizes specific movements or skills ideally performed. Finally, video and audio of the upcoming competitor is introduced to the athlete. In step 5 biofeedback and the acquired mental techniques are applied during competition. Blumenstein et al. (1997) suggest that the athlete begin applying biofeedback in less important competitions and build up to very important competitions. The authors suggested that the successful outcome of the 5-step program would allow the athlete to control relaxation and excitation levels to match the requirements of arousal needed during high-level competition.

The 5-step model has been ecologically employed in high-level competitions by Israeli athletes according to Blumenstein et al. (1997). For example, during the 1995 European Windsurfing Championship in Great Britain an athlete used GSR biofeedback during breaks to maintain optimal arousal and concentration while waiting for winds to pick up. During the 1995 Wrestling Championships in Prague, another athlete used GSR biofeedback to enhance relaxation between matches. Finally, a judo athlete used GSR and EMG biofeedback to achieve optimal excitation between matches during the 1995 Judo World Championships in Japan.

Future Research

Gould and Udry (1994) state that three issues must be addressed by sport psychologists interested in enhancing athletic performance via arousal regulation: 1. identifying the emotional state referred to by the athlete as arousal; 2. furthering the relationship between arousal and performance, and; 3. selecting the best techniques to individually regulate arousal in order to achieve an ideal emotional state for optimum performance. The following section will discuss recommendations for future research in the arousal-perforamance relationship using biofeedback.

Previous research has employed an arbitrary number of biofeedback training sessions; however, this poses a limitation as the researcher cannot be fully certain the athlete has mastered an adequate amount of arousal regulation skills to improve performance (Gould and Udry, 1994). Thus, future research is needed to establish predetermined levels of competency in regulating arousal via biofeedback. Extended research is also needed to examine the longitudinal effects of biofeedback training. For example, how long will the athlete be able to replicate the skills learned during biofeedback following the cessation of biofeedback, and what ongoing training is needed to maintain these skills? In addition, future research should entail more field tests and competition situations in order to further examine the practical and applicable nature of biofeedback. Finally, ongoing research in biofeedback should incorporate multiple physiological system feedback to investigate how different individuals physiologically manifest stress.

Summary

     Arousal regulation, stress management and relaxation have been identified as some of the most relevant issues where sport psychologists can improve the performance of collegiate and Olympic athletes (Getner et al., 2004; Gould et al., 1991). Biofeedback has been suggested as one of the most powerful techniques for enhancing arousal-regulation in athletes (Bar-Eli et al., 2002). Via the use of external signals and cues, biofeedback allows the athlete to increase voluntary control over physiological processes in order to improve self-regulation and enhance performance (Pop-Jordanova & Gucev, 2010). The most effective modalities of biofeedback are suggested to be heart rate and brain waves (Zaichkosky & Fuchs, 1988). Improvements in swimming (Bar-Eli et al., 2002), archery and shooting (Landers et al., 1991), and the performing arts (Raymond et al., 2005) have been reported following psychoregulation training with biofeedback. A 5-step model of psychoregulation training with biofeedback has been proposed and successfully implemented by athletes during world championship level competition (Blumenstein et al., 1997). Future research is needed to determine a standard quantity of biofeedback for varying biofeedback modalities, examine the chronic effects of biofeedback on performance, and further investigate the use of biofeedback during competition.

Jason Cholewa, Ph.D., CSCS

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