Expiratory muscle strength training (EMST) studies have reported significant improvements in maximum expiratory strength, cough efficacy, and swallowing function in patients with Parkinson's disease (PD).1 Currently, EMST is usually performed in short and intensive training periods.1 However, information about detraining outcomes highlights the need for the development of long‐term maintenance home‐based programs to sustain training gains following intensive periods of EMST, especially considering the progressive nature of PD.2 Nevertheless, low long‐term adherence to home exercise is an important issue in many patient groups and may compromise treatment outcomes.3 Therefore, we developed a mobile phone‐based visual feedback (MPVF) application to keep patients motivated to continue EMST following intensive periods of training. With the help of a specially developed algorithm, the application can evaluate real‐time data using a microphone attached to an expiratory handheld device (Fig. 1). Supplement S1 provides detailed information about the algorithm.
FIG. 1.
The microphone is attached to the expiratory muscle trainer (EMST150; Aspire Products, LLC, Cape Carteret, NC) with a special grip ring created by a 3‐dimensional printer. Single arrow indicates the grip ring and the double arrow indicates the microphone.
The first step in the research process of examining whether the feedback application is effective in long‐term EMST adherence is to find out whether a MPVF application is suitable for patients with PD who may experience difficulties in using a smartphone due to motor and cognitive problems related to age and PD itself. Therefore, we conducted a pilot study to investigate the usability of MPVF in EMST in patients with PD.
A total of 12 patients (Table S1) with PD performed an intensive home‐based EMST with MPVF for 2 weeks. Peak cough flow, maximum expiratory pressure, and maximum inspiratory pressure were measured. The usability of the MPVF was also assessed using a semistructured interview. Supplement S2 provides detailed information about the methods.
The median of adherence for completing the prescribed exercises in the training period was 90.5% (between 174 and 431 completed EMST maneuvers). A total of 2 weeks of intensive EMST were sufficient to significantly improve the participants' maximum expiratory pressure and voluntary peak cough flow (Table S2). The improvement is quantitatively comparable with the results of other intensive EMST studies with longer durations, for example.4, 5 When interpreting such rapid improvement, the impact of visual feedback should be considered. It can be assumed that visual feedback increased training effort compared with regular training without immediate control. All participants appreciated EMST with MPVF (12/12). They found it motivating (11/12), comprehensible (11/12), and user friendly (10/12). Even participants (n = 3) with mild cognitive impairment (Montreal Cognitive Assessment scores 24–25) who coincidentally had no previous experience with smartphones were able to use the application without difficulties or help from another person. With respect to the suggestions for improvement from a semistructured interview, the patients might be divided into 2 groups. The first group proposed simplifying the application as much as possible. The second group preferred more advanced options of presenting training data, such as in overview graphs and charts. To meet the needs of both groups, the application should be able to work in basic and advanced modes in the future.
These findings indicate that EMST coupled with MPVF is feasible and potentially useful in patients with PD.
Author Roles
(1) Research Project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript Preparation: A. Writing of the First Draft, B. Review and Critique.
M.S.: 1A, 1B, 1C, 2A, 2B, 2C, 3A
R. Korteová: 1A, 1B, 1C, 2C
R. Kliment: 1A, 3A
R.J.: 3B
E.R.: 1A, 2C, 3B
M.H.: 1A, 3B
Disclosures
Ethical Compliance Statement
This study was approved by the Ethics Committee of the General University Hospital in Prague (No. 1613/19 S‐IV). All participants signed an informed consent. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines.
Funding Sources and Conflicts of Interest
This work was supported by The EU Joint Programme–Neurodegenerative Disease Research 8F19003iCARE‐PD and Ministry of Health of the Czech Republic Grants No NV19‐04‐00233 and NU20‐04‐0337. The authors declare that there are no conflicts of interest relevant to this work.
Financial Disclosures for the Previous 12 Months
The authors declare that there are no additional disclosures to report.
Supporting information
Supplement S1 The MPVF algorithm.
Supplement S2 The methods.
Table S1 Demographic and clinical characteristics.
Table S2 Median and interquartile range (IQR) of maximum respiratory pressure and voluntary cough values across pre‐ and posttesting time points.
Acknowledgments
We thank Tomas Sieger, PhD, from the Czech Technical University in Prague for his advice on the method of instantaneous sound level calculation. We also thank Ota Gal, PhD, from the Department of Neurology and Centre of Clinical Neuroscience, General University Hospital in Prague for manuscript review and critique.
Relevant disclosures and conflicts of interest are listed at the end of this article.
References
- 1.van de Wetering‐van Dongen V, Kalf JG, van der Wees PJ, et al. The effects of respiratory training in Parkinson's disease: a systematic review. J Parkinson's Dis 2020;10(4):1315–1333. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Troche MS, Rosenbek JC, Okun MS, Sapienza CM. Detraining outcomes with expiratory muscle strength training in Parkinson disease. J Rehabil Res Dev 2014;51(2):305–310. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Peek K, Carey M, Sanson‐Fisher R, Mackenzie L. Aiding patient adherence to physiotherapist‐prescribed self‐management strategies: an evidence‐based behavioural model in practice. Phys Therap Rev 2016;21(2):124–130. [DOI] [PubMed] [Google Scholar]
- 4.Reyes A, Castillo A, Castillo J. Effects of expiratory muscle training and air stacking on peak cough flow in individuals with Parkinson's disease. Lung 2020;198(1):207–211. [DOI] [PubMed] [Google Scholar]
- 5.Reyes A, Castillo A, Castillo J, Cornejo I. The effects of respiratory muscle training on peak cough flow in patients with Parkinson's disease: a randomized controlled study. Clin Rehabil 2018;32(10):1317–1327. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplement S1 The MPVF algorithm.
Supplement S2 The methods.
Table S1 Demographic and clinical characteristics.
Table S2 Median and interquartile range (IQR) of maximum respiratory pressure and voluntary cough values across pre‐ and posttesting time points.