Validation of the C-mo System - Cough Monitoring

Not Applicable

Recruiting

• Conditions: Cough; Asthma; Chronic Obstructive Pulmonary Disease; Gastro Esophageal Reflux; Idiopathic Pulmonary Fibrosis; Cough Frequency; Cough Severity; Coughing

• Registration Number: NCT05989698
• Lead Sponsor: Cough Monitoring Medical Solutions

Brief Summary

The goal of this clinical study is to validate C-mo System's ability to automatically detect and characterise cough, in patients over 2 years old with cough as a key or refractory symptom.

The main questions it aims to answer are:

1. Can C-mo System detect cough events? (automatic cough detection)

2. Can C-mo System characterise cough events? (calculation of cough intensity, identification of cough type and presence of wheeze in detected coughs)

Participants will be asked to:

* Wear the C-mo Wearable device for 24 hours (1 day);

* Complete a diary with relevant activities throughout the monitoring period;

* Fill-out questionnaires related to coughing frequency and intensity, usability of the device, and impact of cough on quality of life.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2023-05-12
• Study First Submitted QC: 2023-08-04
• Study First Posted: 2023-08-14
• Study Start: 2023-12-11
• Status Verified: 2025-09
• Last Update Submitted: 2025-09-03
• Last Update Posted: 2025-09-10
• Primary Completion: 2025-12
• Study Completion: 2026-09-01

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 245

Inclusion Criteria

• Patients aged 2 years or older;
• Patients with symptoms/complaints of cough;
• Signed Informed Consent (age ≥ 18 years), signed Informed Consent from the parents/legal representative and the patient (16 and 17 years), or signed Informed Assent and Consent (5 years ≤ age ≤ 15 years).

Exclusion Criteria

• Presence of musculoskeletal (e.g., severe scoliosis), neurological (e.g., post stroke), cardiac (e.g., unstable angina), cognitive (e.g., dementia) changes, or other significant conditions that hinder the participants from collaborating in the collection of data.
• Damaged/weakened skin at the C-mo wearable device's placement area (epigastric region).
• Absence of Informed Consent and/or Assent, as applicable.

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Primary Outcome Measures

Name	Time	Method
Cough detection (precision and recall)	24 hours	Measure C-mo System's performance and ability to automatically detect cough, using precision and recall (percentage - between 0% and 100%), higher scores mean a better outcome.
Cough detection (F1-score)	24 hours	Measure C-mo System's performance and ability to automatically detect cough, using the F1-score (value between 0 and 1), higher scores mean a better outcome.
Cough characterisation (precision, recall and global accuracy)	24 hours	Measure C-mo System's performance and ability to automatically characterise cough, using precision, recall, and global accuracy (percentage - between 0% and 100%), higher scores mean a better outcome.
Cough characterisation (Cohen's Kappa)	24 hours	Measure C-mo System's performance and ability to automatically characterise cough using Cohen's Kappa coefficient (κ). The κ value indicates the level of agreement between C-mo System's output and the result obtained from expert analysis (considered to be the gold standard in this study). It ranges from -1 (worst possible performance) to 1 (best possible performance). Hence, higher scores mean a better outcome.
Cough characterisation (F1-score)	24 hours	Measure C-mo System's performance and ability to automatically characterise cough, using the F1-score (value between 0 and 1), higher scores mean a better outcome.
Cough characterisation (Matthews correlation coefficient)	24 hours	Measure C-mo System's performance and ability to automatically characterise cough using Matthews correlation coefficient (MCC). The MCC value ranges from -1 to 1, and in this case it indicates the level of agreement between C-mo System's output and the result obtained from expert analysis (considered to be the gold standard in this study). A MCC value of -1 indicates total disagreement, 0 indicates that C-mo System's classification is no better than random guessing, and 1 represents a perfect classification (total agreement between C-mo System's output and the gold standard). Hence, higher scores mean a better outcome.
Cough frequency (Matthews correlation coefficient)	24 hours	Measure C-mo System's performance and ability to automatically assess cough frequency, based on the average "number of coughs per hour", using Matthews correlation coefficient (MCC). The MCC value ranges from -1 to 1, and in this case it indicates the level of agreement between C-mo System's output and the result obtained from expert analysis (considered to be the gold standard in this study). A MCC value of -1 indicates total disagreement, 0 indicates that C-mo System's classification is no better than random guessing, and 1 represents a perfect classification (total agreement between C-mo System's output and the gold standard). Hence, higher scores mean a better outcome.
Cough type percentage (Matthews correlation coefficient)	24 hours	Measure C-mo System's performance and ability to automatically assess cough type, based on the percentage of each cough type, using Matthews correlation coefficient (MCC). The MCC value ranges from -1 to 1, and in this case it indicates the level of agreement between C-mo System's output and the result obtained from expert analysis (considered to be the gold standard in this study). A MCC value of -1 indicates total disagreement, 0 indicates that C-mo System's classification is no better than random guessing, and 1 represents a perfect classification (total agreement between C-mo System's output and the gold standard). Hence, higher scores mean a better outcome.
Cough type percentage (Cohen's Kappa Index)	24 hours	Measure C-mo System's performance and ability to automatically assess cough type, based on the percentage of each cough type, using Cohen's Kappa coefficient (κ). The κ value indicates the level of agreement between C-mo System's output and the result obtained from expert analysis (considered to be the gold standard in this study). It ranges from -1 (worst possible performance) to 1 (best possible performance). Hence, higher scores mean a better outcome.
Wheezing detection (precision, recall, true negative rate, accuracy, and negative predictive value)	24 hours	Measure C-mo System's performance and ability to automatically detect wheezing in cough events, using precision, recall, true negative rate, accuracy, and negative predictive value (percentage - between 0% and 100%), higher scores mean a better outcome.
Wheezing detection (F1-score)	24 hours	Measure C-mo System's performance and ability to automatically detect wheezing in cough events, using the F1-score (value between 0 and 1), higher scores mean a better outcome.
Cough frequency (Cohen's Kappa Index)	24 hours	Measure C-mo System's performance and ability to automatically assess cough frequency, based on the average "number of coughs per hour", using Cohen's Kappa coefficient (κ). The κ value indicates the level of agreement between C-mo System's output and the result obtained from expert analysis (considered to be the gold standard in this study). It ranges from -1 (worst possible performance) to 1 (best possible performance). Hence, higher scores mean a better outcome.
Wheezing detection (Matthews correlation coefficient)	24 hours	Measure C-mo System's performance and ability to automatically assess wheeze in cough, based on the percentage of cough events in which wheezing was identified, using Matthews correlation coefficient (MCC). The MCC value ranges from -1 to 1, and in this case it indicates the level of agreement between C-mo System's output and the result obtained from expert analysis (considered to be the gold standard in this study). A MCC value of -1 indicates total disagreement, 0 indicates that C-mo System's classification is no better than random guessing, and 1 represents a perfect classification (total agreement between C-mo System's output and the gold standard). Hence, higher scores mean a better outcome.
Wheezing detection (Cohen's Kappa Index)	24 hours	Measure C-mo System's performance and ability to automatically assess wheeze in cough, based on the percentage of cough events in which wheezing was identified, using Cohen's Kappa coefficient (κ). The κ value indicates the level of agreement between C-mo System's output and the result obtained from expert analysis (considered to be the gold standard in this study). It ranges from -1 (worst possible performance) to 1 (best possible performance). Hence, higher scores mean a better outcome.

Secondary Outcome Measures

Name	Time	Method
Cough intensity	24 hours	Analyse the collected EMG signal to describe cough intensity, as percentage of maximum voluntary contraction (MVC).
Usability results	24 hours	Analyse the results from usability questionnaires regarding the C-mo wearable, calculating average scores for each of the evaluated parameters. A 5-point Likert scale will be used for the overall satisfaction score, in which a higher rating corresponds to a better outcome.
Cough patterns	24 hours	Describe cough patterns through the analysis of changes of cough characteristics (frequency, intensity, type and presence of wheeze) for each subject during their monitoring period, based on their post-monitoring questionnaire (if/how cough changes in relation to physical exercise, eating, resting, body position and time of day).
Cough perception vs. C-mo System analysis, in relation to gold standard (expert evaluation)	24 hours	Analyse the difference between the results obtained by the C-mo System and the results of the questionnaires filled out by the participants about their cough, comparing these obtained results to the gold standard. Differences between participants will also be analysed.; Statistical tests will be used to identify significant differences between groups (patient perception, C-mo System, and gold standard results).

Trial Locations

Locations (8)

HPAV - Trofa Saúde Hospital de Alfena; 🇵🇹 Alfena, Portugal

HFF - Hospital Professor Doutor Fernando Fonseca; 🇵🇹 Amadora, Portugal

Lab3R - Laboratório de Investigação e Reabilitação Respiratória da Escola Superior de Saúde da Universidade de Aveiro; 🇵🇹 Aveiro, Portugal

CHUC - Centro Hospitalar e Universitário de Coimbra; 🇵🇹 Coimbra, Portugal

HDE - Hospital Dona Estefânia; 🇵🇹 Lisbon, Portugal

NMS Research - Laboratório de Exploração Funcional | Fisiopatologia; 🇵🇹 Lisbon, Portugal

CHUSJ - Centro Hospitalar Universitário de São João; 🇵🇹 Porto, Portugal

ICUFP - Instituto CUF Porto; 🇵🇹 Porto, Portugal