Sound-based cough peak flow estimation in patients with neuromuscular disorders.

INTRODUCTION/AIMS: Cough impairment is common in individuals with neuromuscular disorders and is associated with respiratory infections and shorter survival. Cough strength is assessed by measuring cough peak flow (CPF) using a flow meter, but this method requires a complex device setup and trained staff. The aim of the study is to evaluate the reliability of a smartphone app to estimate CPF based on cough sounds in a cohort of individuals with neuromuscular disorders. METHODS: Individuals with neuromuscular disorders underwent CPF measurement with a flow meter and a smartphone app. A CPF <270 L/min was considered abnormal. RESULTS: Of the 50 patients studied, 26 had amyotrophic lateral sclerosis (52%), 15 had hereditary myopathies (30%), and 9 had myasthenia gravis (18%). The intraclass correlation coefficient (ICC) between the CPF measured with a flow meter and CPF estimated with cough sounds was 0.774 (p < .001) even if the patients had orofacial weakness (ICC = 0.806, p < .001). The smartphone app had 94.4% sensitivity and 100% specificity to detect patients with CPF of less than 270 L/min. DISCUSSION: Our findings suggest that sounds measured with a smartphone app provide a reliable estimate of CPF in patients with neuromuscular disorders, even in the presence of with orofacial weakness. This may be a convenient way to monitor respiratory involvement in patients with neuromuscular disorders, but larger studies of more diverse patient cohorts are needed.

Cough sound-based estimation of vital capacity via cough peak flow using artificial neural network analysis.

This study presents a novel approach for estimating vital capacity using cough sounds and proposes a neural network-based model that utilizes the reference vital capacity computed using the lambda-mu-sigma method, a conventional approach, and the cough peak flow computed based on the cough sound pressure level as inputs. Additionally, a simplified cough sound input model is developed, with the cough sound pressure level used directly as the input instead of the computed cough peak flow. A total of 56 samples of cough sounds and vital capacities were collected from 31 young and 25 elderly participants. Model performance was evaluated using squared errors, and statistical tests including the Friedman and Holm tests were conducted to compare the squared errors of the different models. The proposed model achieved a significantly smaller squared error (0.052 L2, p < 0.001) than the other models. Subsequently, the proposed model and the cough sound-based estimation model were used to detect whether a participant's vital capacity was lower than the typical lower limit. The proposed model demonstrated a significantly higher area under the receiver operating characteristic curve (0.831, p < 0.001) than the other models. These results highlight the effectiveness of the proposed model for screening decreased vital capacity.

Clinical Features for Identifying the Possibility of Toileting Independence after Convalescent Inpatient Rehabilitation in Severe Stroke Patients: A Decision Tree Analysis Based on a Nationwide Japan Rehabilitation Database.

BACKGROUND AND PURPOSE: In severe stroke patients, considerable concern should be given to toileting activity in rehabilitative support. Recently, the application of artificial intelligence, including machine learning (ML), has expanded into the stroke medical field, which could clarify the factors affecting toileting independence in severe stroke patients. This study aimed to identify the factors affecting toileting independence in severe stroke patients using ML. METHODS: We used the Japan Rehabilitation Database from 2005 to 2015 to investigate data from 2292 severe stroke patients. We performed the chi-squared automatic interaction detection (CHAID) algorithm with various explanatory variables. RESULTS: The CHAID model identified modified Rankin scale (mRS) score as the first discriminator. Among those with an mRS score ≤4, the next discriminator was age (score ≤72, 73-80, or >80). Among those with an mRS score > 4, the next discriminator was also age (score ≤57, 58-72, 73-80, or >80). Interestingly, some patients achieved toileting independence, although this study focused on severe stroke patients. In branches based on age, the percentage of the patients who achieved toileting independence at discharge decreased progressively with age. CONCLUSION: We identified the influential factors, including reference values, for achieving toileting independence in convalescent severe stroke patients.

Twenty-four-hour ambulatory oximetry monitoring in a patient with idiopathic pulmonary fibrosis for assisting in the discharge instruction on activities of daily living: a case report.

[Purpose] Patients with idiopathic pulmonary fibrosis (IPF) often develop remarkable exercise-induced hypoxemia and are hospitalized for management. The pre-discharge management of activities of daily living (ADL) should determine the amount of exercise-induced hypoxemia permitted during daily activities and inform concrete instructions based on these results. This clinical report aimed to promote 24-hour ambulatory oximetry monitoring in a patient with IPF to guide the pre-discharge management of ADL. [Participant and Methods] Our patient was a 67-year-old male with IPF. He was hospitalized and scheduled to be discharged after introduction of home oxygen therapy. Prior to discharge, we conducted a 24-hour ambulatory oximetry monitoring in the patient's home. We administered instructions on ADL based on these results. Furthermore, 1 day after discharge, we monitored his oxygen saturation level during ADL in his home. [Results] During the pre-discharge monitoring, the patient experienced hypoxemia during bathing, with a minimum oxygen saturation (SpO2) level of 87% and SpO2 level of <90% for 14.3% of the time. The patient was instructed on bathing by a physical therapist before discharge; this led to decreased desaturation, as the patient's SpO2 was <90% for 7.7% of the time. [Conclusion] Twenty-four-hour ambulatory oximetry monitoring is effective in guiding the pre-discharge management of ADL in the home with home oxygen therapy for patients with IPF.

A Mobile Cough Strength Evaluation Device Using Cough Sounds.

Although cough peak flow (CPF) is an important measurement for evaluating the risk of cough dysfunction, some patients cannot use conventional measurement instruments, such as spirometers, because of the configurational burden of the instruments. Therefore, we previously developed a cough strength estimation method using cough sounds based on a simple acoustic and aerodynamic model. However, the previous model did not consider age or have a user interface for practical application. This study clarifies the cough strength prediction accuracy using an improved model in young and elderly participants. Additionally, a user interface for mobile devices was developed to record cough sounds and estimate cough strength using the proposed method. We then performed experiments on 33 young participants (21.3 ± 0.4 years) and 25 elderly participants (80.4 ± 6.1 years) to test the effect of age on the CPF estimation accuracy. The percentage error between the measured and estimated CPFs was approximately 6.19%. In addition, among the elderly participants, the current model improved the estimation accuracy of the previous model by a percentage error of approximately 6.5% (p < 0.001). Furthermore, Bland-Altman analysis demonstrated no systematic error between the measured and estimated CPFs. These results suggest that the developed device can be applied for daily CPF measurements in clinical practice.

Estimation of Cough Peak Flow Using Cough Sounds.

Cough peak flow (CPF) is a measurement for evaluating the risk of cough dysfunction and can be measured using various devices, such as spirometers. However, complex device setup and the face mask required to be firmly attached to the mouth impose burdens on both patients and their caregivers. Therefore, this study develops a novel cough strength evaluation method using cough sounds. This paper presents an exponential model to estimate CPF from the cough peak sound pressure level (CPSL). We investigated the relationship between cough sounds and cough flows and the effects of a measurement condition of cough sound, microphone type and participant's height and gender on CPF estimation accuracy. The results confirmed that the proposed model estimated CPF with a high accuracy. The absolute error between CPFs and estimated CPFs were significantly lower when the microphone distance from the participant's mouth was within 30 cm than when the distance exceeded 30 cm. Analysis of the model parameters showed that the estimation accuracy was not affected by participant's height or gender. These results indicate that the proposed model has the potential to improve the feasibility of measuring and assessing CPF.