Beta/Theta Neurofeedback Training Effects in Physical Balance of ...

Beta/Theta Neurofeedback Training Effects in Physical Balance of Healthy People Wenya Nan1, Xiaoting Qu1, Limin Yang1, Feng Wan1, Yong Hu2, Pedro Mou1, Pui-In Mak1, Peng Un Mak1, Mang I Vai1, and Agostinho Rosa3 1

Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China Department of Orthopaedics and Traumatology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China 3 Department of Bio Engineering, Systems and Robotics Institute, University of Lisbon, Lisbon, Portugal

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Abstract—This study aimed to investigate beta/theta ratio (BTR) neurofeedback training (NFT) effects in physical balance of healthy individuals. Thirty-one healthy volunteers were randomly assigned to NFT group (n=15) and non-NFT control group (n=16). The NFT group completed 25 sessions in consecutive five days with five sessions per day. Before and after NFT, physical balance was measured by Wii Balance Board (WBB). The non-NFT control group only performed the physical balance test on the first day and the fifth day without any training. The results showed no significant improvement in physical balance in the NFT group compared to the nonNFT control group. The reason of the failure will be further studied in our future work. Keywords—neurofeedback training, beta/theta, physical balance, center of pressure. I. INTRODUCTION

Neurofeedback training (NFT) is an operant conditioning procedure, in which the EEG is recorded from scalp and the relevant feature is extracted and presented to the training individual by visual, audio, or combined visual and audio format [1]. By NFT, the individuals can learn to selfregulate their own brain activity and in doing so their behavioral performance can be potentially improved [2]. An increasing number of studies have shown the positive effects of NFT in both clinical treatment [3] and peak performance enhancement [4,5]. On the other hand, physical balance is important for everyone, especially for the patients with physical balance problems (e.g. stroke, Parkinson’s disease), the elderly, the athletes, the soldiers, and the sailors. To our knowledge, only two studies have reported the improvement of physical balance by NFT. In Hammond [6], inhibiting theta (4-7 Hz) simultaneously reinforcing beta (15-18 Hz) using NFT with only several days achieved successful treatment of balance problems in four clinical patients. Moreover, a recent study from [7] showed improvement of both static and dynamic balance in Parkinson’s patients by the same training protocol as [6]. Although the aforementioned studies showed NFT positive effects in patients with balance problems, it is unknown

that whether the healthy people also can achieve physical balance improvement by the same training protocol. Thus, this study aimed to investigate the NFT training effects in physical balance in healthy individuals. II.

MATERIALS AND METHODS

A. Participants A total of 35 healthy volunteers were randomized into NFT group (n=19) and non-NFT control group (n=16, 4 females). Four participants in the NFT group were excluded from data analyses due to bad EEG signal quality (n=3) and dropout (n=1). Thus, the final sample consisted of 15 participants in the NFT group (5 females). The mean age of the participants was 24.13 years (standard deviation (SD) 2.66, range 19-30) in the NFT group and 23.50 years (SD 2.09, range 21-29) in the non-NFT control group. Inclusion criteria for the experiment were as follows: healthy persons without any neurologic, psychiatric or psychological disorder, no history of neurologic disease, no major back or lower limb pathology, no chronic medication or addictive drugs (legal or illegal), no pregnant, no any disease which may influence standing balance such as diabetes. Prior to the experiment, a written informed consent was obtained from all participants after the experimental nature and procedure were explained and their questions were answered. The protocol was in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee (University of Macau). B. Balance test Wii Balance Board (WBB) (Nintendo, Kyoto, Japan) was adopted to measure the physical balance as an equivalent measurement tool of Force platform in this experiment. Participants should be well prepared before the balance test without any exhausted state. WBB was put in front of a solid wall with a settled distance of 2 meters. A clear marked symbol was placed for visual fixation on the wall and the height of the symbol was adapted according to each

© Springer International Publishing Switzerland 2015 D.A. Jaffray (ed.), World Congress on Medical Physics and Biomedical Engineering, June 7-12, 2015, Toronto, Canada, IFMBE Proceedings 51, DOI: 10.1007/978-3-319-19387-8_294

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participant’s own height in order to keep their eyes in the horizontal direction, as suggested by [8]. The balance assessment protocol consisted of six different postures, including standing on both legs with eyes open (OB) and eyes closed (CB), standing with single leg (left or right leg) with eyes open (OL & OR) and eyes closed (CL & CR). In each posture task, the participants were required to take off their shoes and stand still with their arms placed downward at their sides of the body. When the participants stood with both legs, they were asked to stand on the “foot area” on the WBB and their hands loosely hanging at the sides, the support legs were straight during the test. When it came to single leg stance, the lifted foot was about 10 cm of the board and no interactive force between lifted foot and supportive leg was allowed during the test. The whole balance test involved the above 6 kinds of postures and each posture was repeated for 3 times. Thus, there were 18 trials in total and all these trials were assigned in a consistent order. For each trial of the first four postures (OB, CB, OL, OR), the participants were asked to keep the posture as immobile as possible for 15 s. Considering that some participants could not perform the single leg stance without the vision input (for example, NO.3 participant could not keep this posture more than 3 s and his data was removed from the dataset), the posture of CL and CR lasted as long as the participants can (usually about 15 to 30 s) and the ceiling was set as 120 s. C. Balance evaluation parameters CoP trajectory (x, y) information acquired during the balance tasks was used for evaluation. The mean CoP path velocity (to sum up all the distance between adjacent CoP points and then divided by the time) and mean absolute CoP sway distance (the mean distance between the CoP point and the mean value of (x, y) (virtual center)) were the selected parameters. The mean value of the CoP parameter of the three trials in each posture was used for data analysis. D. NFT protocol Each participant in the NFT group completed 5 training sessions per day for a total of 25 sessions in 5 consecutive days. Each session was composed by 4 successive trials of 1 min each and with an interval of 10 s between two consecutive trials. After each session, the participants could have a rest and they were required to write down the mental strategy in each trial. Before and after NFT on each day, two 30-s epochs with eyes open and two 30-s epochs with eyes closed resting baseline were recorded. On the first day before training and on the fifth day after training, the participants in the NFT group performed physical balance test.

Regarding the non-NFT control group, only balance test was performed on the first day and the fifth day without any training sessions. According to Hammond [6], NFT employed a bipolar (sequential) montage. Two electrodes were placed directly below the electrode sites O1 and O2, barely above (at the top edge of) the inion. The ground was located at the forehead. EEG signal was amplified by an EEG amplifier (Vertex 823 from Meditron Electomedicina Ltda, SP, Brazil) with an analog band-pass filter from 0.1 to 70 Hz. The signals were recorded by a Somnium system (Cognitron, SP, Brazil) at a sampling frequency of 256 Hz. In the Somnium system, the signals were filtered by a band-pass filter from 0.5 to 30 Hz, and a notch filter at 50 Hz. The impedance was maintained below 10kΩ for all electrodes. The training parameter was the beta amplitude to theta amplitude ratio (BTR). The amplitude was calculated by fast Fourier-transforms (FFT) every 125 ms based on 2 s data windows. Thus, the frequency resolution was 0.5 Hz. The feedback display contained two 3D objects: a sphere and a cube. The sphere radius reflected the feedback parameter in real time and if this value reached a threshold (Goal 1) the sphere color changed. This sphere was made of several slices and the more slices it had, the smoother it looked. The cube height was related to the period of time for which Goal 1 kept being achieved continuously. If Goal 1 was being achieved continuously for more than a predefined period of time (2 s), Goal 2 was accomplished and the cube rose up until Goal 1 stopped being achieved. Then the cube started falling slowly until it reached the bottom or Goal 2 was achieved again [9]. Therefore, the participants were instructed to apply mental strategies to increase the sphere size or keep the cube as high as possible. No instructions about the effective mental strategies were given since the effective mental strategies vary among individuals [9]. In the first session of each day, the feedback threshold was empirically set to 90% of the BTR in pre baseline on the corresponding day, in order to have a proper difficulty level for the subject. After each session, the session report would show the percentage of time for the training parameter above threshold in the training session. If the percentage of time was above 70%, the threshold would be increased by 0.1 in the next session. E. Data analyses Firstly, independent t test was performed to investigate whether each balance parameter significantly differed between the NFT group and the non-NFT control group. Moreover, paired t test was employed to compare the pre and post balance performance for each group respectively. If any balance parameter showed significance difference in the NFT group by paired t test, repeated analysis of variance

IFMBE Proceedings Vol. 51

Beta/Theta Neurofeedback Training Effects in Physical Balance of Healthy People

(ANOVA) was used with Time (pre vs post) as within subject factor and Group (NFT vs control) as between subject factor in order to make sure the improvement of balance resulted from NFT rather than test-retest effects.

III. RESULTS The velocity and distance for the basic six postures and the dominant standing legs in the pre balance test are presented in Table 1. Dominant leg standing with eyes-open and eyes-closed are abbreviated with O_D and C_D while non-dominant leg standing with eyes-open and eyes-closed with O_ND and C_ND. No significant difference between the NFT group and the non-NFT control group was found in any balance parameter in table 1. Table 1 Velocity and distance (mean±SD) of each posture in pre balance test

Postures

Velocity

Distance

NFT

Control

NFT

Control

OB

1.27±0.21

1.28±0.16

0.31±0.12

0.31±0.10

CB

1.39±0.17

1.39±0.23

0.39±0.15

0.39±0.15

OL

4.29±1.03

4.47±0.87

0.76±0.17

0.85±0.31

OR

4.11±0.86

4.00±0.64

0.73±0.12

0.76±0.19

CL

8.28±2.34

9.10±2.75

1.45±0.26

1.56±0.31

CR

8.49±2.98

7.90±1.37

1.48±0.29

1.57±0.23

O_D

4.30±1.06

4.23±0.80

0.75±0.16

0.78±0.17

C_D

8.14±2.04

8.40±2.34

1.43±0.26

1.55±0.30

O_ND

4.16±0.89

4.24±0.80

0.75±0.14

0.82±0.33

C_ND

8.63±3.18

8.60±2.16

1.50±0.29

1.58±0.24

Paired t test showed no significant difference in any balance parameter between the pre and post-test in the nonNFT control group. Regarding the NFT group, the distance of right leg standing with eyes-closed (CR) revealed significant improvement after NFT (t14=2.532, p=0.024), and the distance of dominant leg standing with eyes-closed (C_D) achieved marginal significant improvement after NFT (t14=1.950, p=0.071). However, all of the factors (Time, Group, and their interaction) failed to show any significant main effect in the distance of CR and C_D, indicating that the improvement in these two parameters may result from test-retest effects rather than the NFT effects.

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uals. The participants performed NFT in 5 consecutive days. However, there was no significant improvement in physical balance in the NFT group compared to the non-NFT control group. There are several possible reasons as follows. Firstly, the healthy individuals have much better balance performance than the patients with balance problems. The studies from [6] and [7] focused on the patients with balance problems, and they demonstrated significant balance improvement by training the same EEG parameter as our study. The patients with balance problems have much larger improvement space than healthy individuals. It may be difficult to improve balance in healthy people since their performance is already at normal level. Additionally, although the training protocol (i.e. enhancement of BTR at the locations below O1 and O2 by NFT, bipolar montage) improved physical balance in patients [6,7], it may be not suitable in healthy individuals with normal balance performance. What’s more, balance evaluation methods are quite different between the ones for healthy and the ones for patients. Almost all the assessment methods for patients have the ceiling effects when applied on healthy people. In general, the patients had abnormal brain function whereas the healthy people not. Therefore, future work should investigate that which EEG feature at which location correlates with or even influence balance in healthy people, and then utilize NFT to modify the corresponding EEG feature. Finally, if the training protocol was suitable, the session number and training schedule maybe not set properly to elicit balance change. In [6], one patient with balance and unsteadiness problems reported that he felt steadier after 2 30-min training using the same protocol. In our case, the total training time is 100 min in 5 consecutive days. In [7], Parkinson’s patients performed 8 30-min sessions in twoand-a-half weeks with 3 sessions per week. The difference between this study and reference [6,7] is the participant population. The healthy individuals may need a longer training process to elicit balance enhancement. To our knowledge, the training session and schedule settings are empirical, and there is no guideline for it. To summarize, different from patients with balance problems [6,7], BTR NFT could not enhance physical balance in healthy people without balance problems. Future study should investigate which and how brain activity affects balance performance in healthy people without balance problems, and regulate the corresponding brain activity by NFT to optimize the physical balance in healthy people who need high physical balance, e.g. athletes and soldiers.

IV. DISCUSSION & CONCLUSIONS The objective of this work was to investigate the BTR NFT training effects in physical balance in healthy individ-


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ACKNOWLEDGMENT This work is supported in part by FCTPEstOE/EEI/LA0009/2013 Grant and the Macau Science and Technology Development Fund under Grant FDCT036/2009/A and the University of Macau Research Committee under Grants MYRG139(Y1-L2)-FST11-WF, MYRG079(Y1-L2)-FST12-VMI, MYRG069(Y1-L2)FST13-WF, and MYRG2014-00174-FST.

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CONFLICT OF INTEREST The authors declare that they have no conflict of interest.

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Corresponding author

Vernon D J (2005) Can neurofeedback training enhance performance? An evaluation of the evidence with implications for future research. Appl Psychophysiol Biofeedback 30: 347–364 Dempster T, Vernon D (2009) Identifying indices of learning for alpha neurofeedback training. Appl Psychophysiol Biofeedback 34:309-328 Lofthouse N, Arnold L E, Hersch S, Hurt E, DeBeus R (2012) A review of neurofeedback treatment for pediatric ADHD. J Atten Disord 16:351-372

Author: Feng Wan Institute: Department of Electrical and Computer Engineering, University of Macau City: Macau Country: China Email: [email protected]
