Biofeedback flutter device for managing the symptoms of patients with COPD

Abstract

BACKGROUND:

Flutter is a device used in removing excess lung secretions. The conventional flutter lacks a biofeedback component to facilitate optimal use by the patients.

OBJECTIVE:

The current research aims to compare the effects of biofeedback flutter devices with the conventional flutter in managing the symptoms of patients with chronic obstructive pulmonary diseases.

METHODS:

One hundred and sixty-eight participants were randomly allocated into four groups: Group A (conventional), Group B (visual biofeedback), Group C (auditory biofeedback) and Group D (visual and auditory biofeedback). All groups were treated five days for 20 minutes. Outcome measures included wet sputum weight [during intervention (T1) and 1 hour after intervention (T2)], oxygen saturation and dyspnea score (before and after intervention) on all days.

RESULTS:

The wet sputum expectorated (T2) by Group B was significantly higher than Group A ( $P<$ 0.001), Group C ( $P<$ 0.001) and Group D ( $P<$ 0.05). The dyspnea score for Group B ( $P<$ 0.05), Group C ( $P<$ 0.05) and Group D ( $P<$ 0.05) was significantly lower than Group A. The post-intervention oxygen saturation level was higher in Group D followed by Groups B, C and A.

CONCLUSION:

The use of biofeedback flutter is effective in the removal of secretion, reducing dyspnea and improving oxygen saturation when compared to conventional flutter.

Keywords

Biofeedback flutter COPD

1. Introduction

The hyper secretion of respiratory mucus is a common manifestation among patients with chronic obstructive pulmonary diseases (COPD) [1, 2, 3]. The hyper secretion of respiratory mucus can obstruct the lumen of the respiratory tract, causing a decline in airflow and a rapid decrease in lung function resulting in dyspnea, poor work ability, poor quality of life, increased hospitalization rate, and high mortality [4, 5]. The traditional physical therapy techniques such as percussion, postural drainage, forced expiration technique (FET), active cycle of breathing technique (ACBT), autogenic drainage and the use of a positive expiratory pressure (PEP) were effective in clearing the secretions from the lung [6].

Flutter is a small self-administered hand-held device, which is an alternative to traditional physical therapy techniques in removing excess lung secretions. Expiration through flutter causes the steel ball inside the device to move up and down producing a positive expiratory pressure (PEP) that is oscillatory in nature and the same is transmitted back to the patient [7, 8]. The PEP aids in clearing secretions by opening the respiratory airways and lowering the peripheral airway resistance. The thixotropic effect produced by the oscillations decreases the viscoelasticity of the secretions, which further facilitates the removal of secretions by means of flutter resulting in improved lung function and oxygenation among adult and pediatric patients with respiratory disorders [6, 9, 10, 11, 12, 13, 14].

Biofeedback is a mechanism of providing additional biological information referred to as feedback (augmented or extrinsic), which is beyond the naturally available information to the users [15]. Biofeedback devices determine the biological variables and convey to the user as a direct feedback (a numerical value e.g. heart rate) or as a transformed feedback. In transformed biofeedback, the device utilizes the measurements of the biological variable to control a visual display or an auditory signal. A biofeedback device facilitates the users in improving the control of functional tasks resulting in therapeutic benefits [16]. There are various biofeedback systems complied with rehabilitation devices, whereas the devices used for respiratory disorders which help in mucus clearance do not add any feedback systems. Respiratory training with the biofeedback system facilitates the proper breathing pattern, improves respiratory function, reduces respiratory rate and stress, improves gas exchange, improves ventilation and perfusion and thereby decreases the activity of the sympathetic nervous system by clearing secretions [17]. Initially the position at which the patient holds the conventional flutter is critical. Hence, patients need a healthcare professional to achieve the ‘fluttering’ effect by placing the hands on the patient’s chest wall and needs to be adjusted to the patient’s pulmonary resonance frequency, which is done by tilting the flutter slightly up or down. The flutter therapy starts only when the patient establishes a comfortable position and an appropriate tilt of the device [18]. In contrast, the biofeedback flutter device would allow patients to acquire appropriate tilt of the device, increases the sense of awareness and gains the motivation that in turn maximizes the elimination of sputum and improves lung function. The conventional flutter device lacks a biofeedback component to facilitate optimal use by the patients. Therefore, the objective of the current research is to compare the effect of flutter devices equipped with visual biofeedback, auditory biofeedback, and auditory and visual biofeedback with that of the conventional flutter in reducing perceived dyspnea, sputum removal reflected by sputum weight and oxygen saturation among patients with COPD characterized by mucus hyper secretion.

Figure 1.

Flowchart representation of the study.

2. Materials and methods

2.1 Design

A randomized single blind study was conducted at Saveetha Medical College Hospital, India. We aimed to examine the effects of the audiovisual biofeedback flutter device in mucus clearance among COPD patients. Individuals of both genders, an age between 18 to 58 years, a radiography diagnosis of consolidation, and individuals under mucolytic agents of COPD were included. We excluded individuals with current acute chest pain, recent respiratory infection ( $<$ 4 weeks), recent facial, oral or skull surgery or trauma, hemodynamic instability, active hemoptysis, recent history of rib fractures ( $<$ 3 months), recent cardio thoracic surgeries, individuals with mechanical ventilation and extubation within 48 hours, and individuals with impaired vision and hearing. In total, 168 participants were included, which were randomly allocated into four groups. The participants were treated for a period of five days and every day the sputum weight, oxygen saturation and dyspnea were assessed. All the outcomes assessors were blinded. All participants were given detailed explanation about the procedure with an information sheet for their co-operation and provided written informed consent prior to enrollment (Fig. 1). Ethical approval was obtained from the Institutional Human Ethics Committee (IHEC No-001/12/2015/IEC/SU) of Saveetha University.

2.2 Intervention

Group A was treated with a standard flutter (oscillatory device; Aptalis Pharma, USA) conventional method without any biofeedback system, Group B was treated with a visual biofeedback flutter, Group C was treated with an auditory biofeedback flutter and Group D was treated with an auditory visual biofeedback flutter. The visual and auditory biofeedback flutter device was made out of a hardware’s microcontroller (ATmega328p chip, 8 bit microcontroller; Arduino, USA), mick (A/D converter), light emitting diode (LED) light and buzzer. The flutter device was connected to the Arduino microcontroller through the mick which converts an analog signal into a digital signal. If the oscillation of the flutter device exceeds the 15 Hz threshold level, the Arduino microcontroller sends the signal to the LED indicator which blinks LED light. In auditory biofeedback, the Arduino microcontroller sends a signal to the buzzer which makes 60 decibels of sound. Flutter therapy was performed for 10 minutes in the morning session with an adequate rest in-between for a total of five days for all four groups. The participants were seated with their back straight and head slightly tilted upward so the upper airway is wide open. As an alternative, the patient can be seated with elbows resting on a table at a comfortable level and head position as described above. Group A was asked to blow with the flutter without feedback which was adjusted to the oscillation frequency, which was done by tilting the flutter slightly up or down to achieve the maximum ‘fluttering’ effect. Group B was asked to visualize the LED light as visual feedback. Group C was asked to listen to the buzzer sound as audio feedback. Group D was asked to visualize the LED light and simultaneously listen to the buzzer sound as audiovisual biofeedback to achieve the ‘fluttering’ effect. The audiovisual signals render feedback to the subjects only when they achieve the oscillation frequency of 15 Hz. The subjects were made aware of their low threshold level through the absence of audiovisual feedback. Hence, they were instructed to modify the inclination of the flutter device slightly up or down during their intervention to experience audiovisual feedback in order to maximize the flutter effect.

The sputum weight was calculated two times a day. Initially participants were asked to collect the sputum during the treatment session (T1) followed by sputum collection during the next one hour period after the respective treatment session (T2) for five days. The participants were asked to collect their sputum in pre-weighed sterile sputum containers which was then weighed using a digital weighing scale (Bulfyss digital weighing scale, PRC). We measured the ratio of perceived exertion using the Borg-RPE scale. The scale starts from 6–20 with adequate rest before and after intervention. The oxygen saturation using fingertip pulse oximeter (Dr Trust Signature Series, SS 02; Nureca Inc, USA) was measured before and after the intervention for all days.

2.3 Statistical analysis

The statistical analysis was performed using SPSS version 22. The demographic and baseline characteristics of the participants of the four groups are presented as mean and standard deviation or frequency and percentage as appropriate. The data was tested for normality and homogeneity of variance for deciding appropriate statistics. Parametric statistics were used to analyze normally distributed data and nonparametric statistics for other data. Baseline comparisons of the study groups in terms of gender distribution, age, height, weight, body mass index (BMI), dyspnea score and oxygen saturation was done using the Chi-square test or Kruskal-Wallis test as appropriate. The difference in sputum weight expectorated during the intervention sessions (T1). The difference in sputum weight expectorated one hour after the intervention (T2) and the dyspnea score were analyzed by the Kruskal-Wallis test (post hoc Mann-Whitney U test). The difference in oxygen saturation during the pre- and post-intervention within all groups were analyzed using the paired $t$ test. The differences between the intervention groups in terms of the oxygen saturation during pre- and post-intervention were analyzed using repeated-measures analysis of variance and estimated marginal means. Missing data was dealt with the intention-to-treat analysis by using the participant’s latest available data or baseline data as applicable. An overall statistical significance level was maintained at $P<$ 0.05.

3. Results

3.1 Demographic data (participants)

One hundred and sixty-eight participants that met the selection criteria were enrolled in the study. One hundred and fifty-six participants completed the research as per the protocol and 12 participants discontinued due to various reasons. The demographic and baseline characteristics of the participants belonging to the four intervention groups are presented in Table 1. The participants were similar in the baseline in terms of age, gender distribution, height, weight, body mass index, FEV1%, dyspnea score and oxygen saturation, as shown in Table 1.

Table 1
Demographic and baseline characteristics of the participants

Variables	Group A ( $n=$ 42)	Group B ( $n=$ 42)	Group C ( $n=$ 42)	Group D ( $n=$ 42)	$P$ value
Male (%)	13 (31%)	22 (52%)	17 (40%)	14 (33%)	0.180 ${}^{\text{a}}$
Female (%)	29 (69%)	20 (48%)	25 (60%)	28 (67%)
Age (y)
$\bar{X}$ $\pm$ SD	52.3 $\pm$ 7.8	54.1 $\pm$ 7.3	53.5 $\pm$ 6.5	53.4 $\pm$ 8.1	0.738 ${}^{\text{b}}$
Height (cm)
$\bar{X}$ $\pm$ SD	156.3 $\pm$ 8.5	158.3 $\pm$ 9.7	157.3 $\pm$ 7.7	156.3 $\pm$ 8.5	0.665 ${}^{\text{b}}$
Weight (kg)
$\bar{X}$ $\pm$ SD	61.9 $\pm$ 9.3	59.1 $\pm$ 8.4	60.8 $\pm$ 8	59.5 $\pm$ 8.6	0.464 ${}^{\text{b}}$
BMI
$\bar{X}$ $\pm$ SD	25.3 $\pm$ 3.5	23.7 $\pm$ 3.8	24.6 $\pm$ 3.4	24.5 $\pm$ 3.9	0.274 ${}^{\text{b}}$
FEV1 (%)
$\bar{X}$ $\pm$ SD	49.9 $\pm$ 4.7	47.8 $\pm$ 4.9	48.8 $\pm$ 5.5	51 $\pm$ 5.8	0.129 ${}^{\text{b}}$
Dyspnea (Borg-RPE scale)
$\bar{X}$ $\pm$ SD	10.2 $\pm$ 1.2	10.5 $\pm$ 1.3	10.4 $\pm$ 1.2	10 $\pm$ 1.2	0.294 ${}^{\text{b}}$
SpO ${}_{2}$ (%)
$\bar{X}$ $\pm$ SD	91.5 $\pm$ 1	91.9 $\pm$ 1	91.3 $\pm$ 1.5	91.1 $\pm$ 1.9	0.073 ${}^{\text{b}}$

y, Years; cm, Centimeter; Kg, Kilogram; BMI, Body mass index; SpO ${}_{2}$ , Oxygen saturation; FEV1, Forced expiration volume in first second; $\bar{X}$ , Mean; SD, Standard deviation; ${}^{\text{a}}$ , $P$ value for Chi-square test; ${}^{\text{b}}$ , $P$ value for Kruskal-Wallis test.

Table 2

Wet weight of expectorated sputum during and one hour post-intervention and dyspnea: Comparison between the four intervention groups

Outcome	Group A ( $n=$ 42)	Group B ( $n=$ 42)	Group C ( $n=$ 42)	Group D ( $n=$ 42)	$P$ value ${}^{\#}$	$P$ value ${}^{\$}$
Sputum production (grams)
T1 ( $\bar{X}$ $\pm$ SD)	8.5 $\pm$ 4.5	10 $\pm$ 5.7	9.9 $\pm$ 5.6	10.3 $\pm$ 5.1	0.098	NA
T2 ( $\bar{X}$ $\pm$ SD)	12.3 $\pm$ 2.2	15.4 $\pm$ 2.5	12.4 $\pm$ 3.9	14.7 $\pm$ 2.6	0.000	0.000 ${}^{\text{a}}$
						0.000 ${}^{\text{b}}$
						0.000 ${}^{\text{c}}$
						0.034 ${}^{\text{d}}$
						0.007 ${}^{\text{e}}$
Dyspnea ( $\bar{X}$ $\pm$ SD)	10.4 $\pm$ 1.2	9.7 $\pm$ 1.3	9.6 $\pm$ 1.3	9.6 $\pm$ 1.2	0.037	0.02 ${}^{\text{f}}$
						0.02 ${}^{\text{g}}$
						0.01 ${}^{\text{h}}$

$\bar{X}$ , Mean; SD, Standard deviation; T1, Sputum collected during treatment session; T2, Sputum collected one hour after the treatment session; ${}^{\#}$ , $P$ value for Kruskal-Wallis test; ${}^{\$}$ , $P$ value for post hoc analysis by Mann-Whitney U test; ${}^{\text{a}}$ , $P$ value for significant differences between Group A and Group B; ${}^{\text{b}}$ , $P$ value for significant differences between Group A and Group D; ${}^{\text{c}}$ , $P$ value for significant differences between Group B and Group C; ${}^{\text{d}}$ , $P$ value for significant differences between Group B and Group D; ${}^{\text{e}}$ , $P$ value for significant differences between Group C and Group D; ${}^{\text{f}}$ , $P$ value for significant differences between Group A and Group B; ${}^{\text{g}}$ , $P$ value for significant differences between Group A and Group C; ${}^{\text{h}}$ , $P$ value for significant differences between Group A and Group D.

3.2 Expectorated wet sputum weight

The difference in the wet sputum weight expectorated during the intervention sessions (T1) among the four groups and was not significant (Table 2). There was a significant difference in the wet sputum weight expectorated one hour after the intervention session (T2) among the four groups ( $P<$ 0.001). The wet sputum expectorated (T2) by participants of Group B was significantly higher compared to Group A ( $P<$ 0.001), Group C ( $P<$ 0.001) and Group D ( $P<$ 0.05). Furthermore, the wet sputum expectorated (T2) by participants of Group D was significantly higher compared to Group A ( $P<$ 0.001) and Group C ( $P<$ 0.05). The difference in the wet sputum weight expectorated during the intervention sessions (T2) between Group A and Group C was not significant.

3.3 Dyspnea score

Table 2 shows a significant difference in the dyspnea score among the four groups ( $P<$ 0.05). The dyspnea score of the participants of Group B ( $P<$ 0.05), Group C ( $P<$ 0.05) and Group D ( $P<$ 0.05) was significantly lower compared to Group A. The difference in dyspnea score between Group B, Group C and Group D was not significant.

Table 3
Oxygen saturation before and after intervention: Comparison between the four intervention groups

Outcome	Group A ( $n=$ 42)	Group B ( $n=$ 42)	Group C ( $n=$ 42)	Group D ( $n=$ 42)	$P$ value ${}^{\text{b}}$
SpO2 % ( $\bar{X}$ $\pm$ SD)
Before intervention	90.4 $\pm$ 3.7	93.5 $\pm$ 1.7	92.8 $\pm$ 2.3	94 $\pm$ 1.8	0.000
After intervention	90.6 $\pm$ 3.7	93.9 $\pm$ 1.7	93.11 $\pm$ 2.2	94.4 $\pm$ 1.7
$P$ value ${}^{\text{a}}$	0.003	0.000	0.000	0.000

$\bar{X}$ , Mean; SD, Standard deviation; ${}^{\text{a}}$ , $P$ value for paired $t$ test comparing scores before and after interventions within the groups; ${}^{\text{b}}$ , $P$ value for repeated measures ANOVA, comparing the mean difference (after – before intervention) between the four intervention groups.

3.4 Oxygen saturation

Table 3 shows a significant increase in oxygen saturation during the post-intervention in comparison to pre-intervention in all groups ( $P<$ 0.05). There was a significant difference between the groups in terms of the increase in oxygen saturation during the post-intervention period in comparison to pre-intervention ( $P<$ 0.001). The increase in oxygen saturation during post-intervention in comparison to pre-intervention was higher in Group D followed by Group B, Group C and Group A.

4. Discussion

No study has yet published the comparison between biofeedback flutter intervention and the conventional flutter therapy for clearing mucus, dyspnea reduction and increasing oxygen saturation [18, 19, 20].

The major findings of this study are as follows. (1) The biofeedback flutter therapy proved to be more effective when compared with conventional flutter therapy in clearing mucus. However, out of the three types of biofeedback techniques used, in session (T2) the visual biofeedback group showed better mucus clearance than other biofeedback systems. (2) Dyspnea scores recorded following biofeedback intervention were lower in comparison to conventional flutter intervention. (3) All subjects who underwent biofeedback flutter intervention reported a marked increase in the level of oxygen saturation. Concurrently, the audiovisual biofeedback flutter intervention groups showed a significant increase in the level of oxygen saturation in comparison to the other groups.

The common pathological manifestation among COPD patients are the disruption of the epithelial barrier and obtrusion with mucociliary clearance apparatus which results in deposition of mucous exudates in the small airways and inflammatory cells infiltration in the respiratory walls. These changes in the airways lead to dyspnea and reduction in oxygen saturation [19]. When comparing wet sputum weight between the groups, there was no significant difference in the amount of sputum expectorated during treatment session (T1). The mean difference of wet sputum collected one hour after the intervention session (T2) was significantly higher in the visual group followed by the audiovisual group. The factors that contribute to increased sputum expectoration: the application of biofeedback devices allows the patients to become more aware of their physiological functions. It also enables the patients to train themselves in learning the skills to enhance their performance [17]. In the earlier studies sputum weight was collected only once after the treatment session [12, 21] whereas in the present study sputum expectorated was collected twice: T1 (sputum collected during the treatment session) and T2 (sputum collected one hour after the treatment session).

The amount of sputum measured in T2 for the conventional flutter therapy was 12.3 g and the visual biofeedback flutter therapy was 15.4 g, which was higher than in earlier studies [13, 21, 22]. The difference between T1 and T2 in the audiovisual group was 4.4 g, which strongly supports the audiovisual biofeedback flutter training as the best method for mucus removal in COPD conditions.

The difference in the amount of sputum measured in T2 between the conventional flutter therapy and visual biofeedback flutter therapy was 3.1 g, which was similar to earlier studies which documented the accepted clinical difference of the sputum amount 3 to 3.5 g [13, 22]. However, the audiovisual groups also showed a difference of 2.4 g. The results of this study strongly support the visual and audiovisual biofeedback flutter training as the best method of mucus removal in COPD conditions. Some authors have suggested that patients would feel dizziness and lightheadedness when using the conventional flutter device due to hyperventilation [21], but these symptoms did not occur in the subjects in the biofeedback flutter groups as the expiration time and flow was lengthened. Thus, the practice of using the biofeedback flutter device among COPD patients is strongly recommended.

Dyspnea is the other major problem encountered by the patients with respiratory disorders. The effect of flutter therapy on dyspnea was well explained in earlier studies [23]. The results of our study were similar in minimizing the rate of exacerbation while using the flutter device with the biofeedback mechanism. These devices not only provide motivation to the patient, but also guide the correct method of using the flutter device through the visual cues with the LED light and buzzer sound if the oscillation of the flutter device exceeds the threshold level. It furthermore helps to practice a physiological controlled vibration system that produces expiration against resistance that results in increased alveolar pressure and reduces peripheral airway resistance by improving collateral ventilation and enhancing movement of secretion from peripheral airways to central airways, which in turn improves oxygenation and reduces dyspnea [24].

The current study shows that the biofeedback flutter devices are effective in improving oxygen saturation, while there are significant improvements in the audiovisual biofeedback flutter group. The difference between baseline oxygen saturation (90.4%) and obtained oxygen saturation among the audiovisual group (94.4%) denotes the clinical benefits of using the biofeedback flutter device among COPD conditions. Within group differences are clinically insignificant, even though they are supposedly statistically significant.

The benefits of the flutter device is that it effectively mobilizes secretions from the distal to the primary airways and thereby improving oxygenation [10, 24, 25]. When the expiration is encouraged, the ball in the flutter device oscillates and creates vibration in the chest wall and simultaneously feedback of a buzzer or light will be enhanced to encourage the person. Prolonged expiration helps to improve collateral ventilation, prevents airway collapse and mobilizes the sputum [26]. The lack of data regarding expiratory time, flow and oscillation frequency can be considered as a limitation of the present study. Standardization of these variables during the use of the biofeedback flutter device can be considered in future studies. It would have been more beneficial for the patients if the audio and visual feedback system was built in the flutter device, since the tool used in the current study incorporates a separate wire to connect the audio and visual feedback to the flutter device. Despite these limitations, inclusion of the biofeedback system in the flutter device proved to be a valuable mechanism in the rehabilitation of COPD patients.

5. Conclusion

The use of biofeedback flutter is very effective in removing secretion, reducing dyspnea and improving oxygen saturation in comparison to conventional flutter therapy. However, audiovisual and visual biofeedback therapy was more effective than the audio biofeedback flutter therapy group. Biofeedback flutter therapy is strongly recommended for managing the symptoms of COPD patients.

Footnotes

Conflict of interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

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Biofeedback flutter device for managing the symptoms of patients with COPD

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2.1 Design

2.2 Intervention

2.3 Statistical analysis

3. Results

3.1 Demographic data (participants)

Table 1 Demographic and baseline characteristics of the participants

3.3 Dyspnea score

Table 3 Oxygen saturation before and after intervention: Comparison between the four intervention groups

4. Discussion

5. Conclusion

Footnotes

Conflict of interest

References

Table 1
Demographic and baseline characteristics of the participants

Table 3
Oxygen saturation before and after intervention: Comparison between the four intervention groups