Validation of the C-mo System - Cough Monitoring

NCT05989698 | Recruiting

• 1 other identifier: C-mo_01
• Study Type: interventional
• Target: 300
• Locations: 1 country
• Sites: 8

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:

• 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.

Conditions

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

Keywords

Cough monitoring; Cough detection; Cough assessment; C-mo

Outcome Measures

Primary Outcomes (14)

• Cough detection (precision and recall)

  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.

  24 hours

• Cough detection (F1-score)

  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.

  24 hours

• Cough characterisation (precision, recall and global accuracy)

  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.

  24 hours

• Cough characterisation (F1-score)

  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.

  24 hours

• Cough characterisation (Matthews correlation coefficient)

  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.

  24 hours

• Cough characterisation (Cohen's Kappa)

  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.

  24 hours

• Wheezing detection (precision, recall, true negative rate, accuracy, and negative predictive value)

  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.

  24 hours

• Wheezing detection (F1-score)

  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.

  24 hours

• Cough frequency (Matthews correlation coefficient)

  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.

  24 hours

• Cough frequency (Cohen's Kappa Index)

  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.

  24 hours

• Cough type percentage (Matthews correlation coefficient)

  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.

  24 hours

• Cough type percentage (Cohen's Kappa Index)

  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.

  24 hours

• Wheezing detection (Matthews correlation coefficient)

  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.

  24 hours

• Wheezing detection (Cohen's Kappa Index)

  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.

  24 hours

Secondary Outcomes (4)

• Cough intensity

  24 hours

• Cough patterns

  24 hours

• Usability results

  24 hours

• Cough perception vs. C-mo System analysis, in relation to gold standard (expert evaluation)

  24 hours

Other Outcomes (1)

• Relation between cough characteristics and target diseases

  24 hours

Study Arms (1)

C-mo System

EXPERIMENTAL

Device: C-mo System

Interventions

C-mo System DEVICE

Patients will use C-mo System for a period of 24h, to assess cough characteristics.

C-mo System

Eligibility Criteria

• Age: 2 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• 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).

You may not qualify if:

• 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.

Sponsors & Collaborators

• Cough Monitoring Medical Solutions: lead
• Universidade Nova de Lisboa: collaborator

Study Sites (8)

HPAV - Trofa Saúde Hospital de Alfena

Alfena, Portugal

RECRUITING

HFF - Hospital Professor Doutor Fernando Fonseca

Amadora, Portugal

RECRUITING

Lab3R - Laboratório de Investigação e Reabilitação Respiratória da Escola Superior de Saúde da Universidade de Aveiro

Aveiro, Portugal

COMPLETED

CHUC - Centro Hospitalar e Universitário de Coimbra

Coimbra, Portugal

RECRUITING

HDE - Hospital Dona Estefânia

Lisbon, Portugal

RECRUITING

NMS Research - Laboratório de Exploração Funcional | Fisiopatologia

Lisbon, Portugal

RECRUITING

CHUSJ - Centro Hospitalar Universitário de São João

Porto, Portugal

RECRUITING

ICUFP - Instituto CUF Porto

Porto, Portugal

RECRUITING

MeSH Terms

Conditions

Cough; Asthma; Pulmonary Disease, Chronic Obstructive; Gastroesophageal Reflux; Idiopathic Pulmonary Fibrosis

Condition Hierarchy (Ancestors)

Respiration Disorders; Respiratory Tract Diseases; Signs and Symptoms, Respiratory; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Bronchial Diseases; Lung Diseases, Obstructive; Lung Diseases; Respiratory Hypersensitivity; Hypersensitivity, Immediate; Hypersensitivity; Immune System Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Esophageal Motility Disorders; Deglutition Disorders; Esophageal Diseases; Gastrointestinal Diseases; Digestive System Diseases; Pulmonary Fibrosis; Lung Diseases, Interstitial

Study Officials

• Nuno M Neuparth, PhD

  NOVA Medical School | Faculdade de Ciências Médicas da Universidade Nova de Lisboa

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Diogo B Tecelão, MSc

CONTACT

+351 917 935 447; diogo.tecelao@c-mo.solutions

Sara B Lobo

CONTACT

+351 967 889 091; sara.lobo@c-mo.solutions

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: OTHER
• Intervention Model: SINGLE GROUP
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 12, 2023
• First Posted: August 14, 2023
• Study Start: December 11, 2023
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): September 1, 2026
• Last Updated: April 8, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

PT (8)