C-mo System 1.0's Validation - Cough Monitoring

Asthma Clinical Trial

— C-mo_01  

Official title:

C-mo System 1.0's Validation - Cough Monitoring

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05989698
• Other study ID #: C-mo_01
• Status: Recruiting
• Phase: N/A
• Start date: December 11, 2023
• Est. completion date: June 11, 2025

Study information

• Verified date: February 2024
• Source: Cough Monitoring Medical Solutions
• Contact: Diogo B Tecelão, MSc
• Phone: +351 917 935 447
• Email: diogo.tecelao[@]c-mo.solutions
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Cough is one of the most reported symptoms, especially associated with respiratory diseases. Additionally, cough contains extremely insightful information regarding the patient's health. It is a symptom full of physiopathological information, which can be extremely helpful in clinical practice. However, cough is not currently used as a clinical biomarker given that:

1. Cough is an extremely subjective symptom for patients (patients can't accurately describe and understand their cough's traits).

2. There is currently no tool available to evaluate cough objectively and thoroughly.

As such, there is an unmet medical need: solutions for objective cough monitoring and management.

C-mo System is a novel non-invasive medical device, which performs an objective monitoring of the patient's cough for long periods of time. The C-mo System consists of a wearable device (C-mo wearable) and a desktop software (C-mo Medical Platform). C-mo System characterises cough automatically through data collection and processing techniques (automatic classification), and its base outputs include:

• Cough frequency (how many times the patient coughs)

• Cough intensity (how strong cough's expiratory effort is)

• Cough type (if the cough is dry, wet, or laryngeal)

• Identification of patterns (associations between cough characteristics and specific events, namely the time of day, body position, physical exercising, and meals).

It is extremely important to validate C-mo System in a wide and diverse population, given the use of signal processing algorithms and artificial intelligence. C-mo System's base outputs will allow healthcare professionals to improve significantly the medical care associated with this symptom, namely:

• Speed-up and improve the accuracy of the diagnosis of several medical conditions, especially respiratory diseases. C-mo System's ability to objectively monitor cough will allow healthcare professionals to make associations between specific cough patterns and specific medical conditions.

• Optimize treatment prescription and monitor their effectiveness. C-mo System's objective assessment of cough will allow healthcare professionals to understand if a given therapy is working as intended.

• Objectively monitor chronic disease progression. C-mo System's monitoring of cough will allow healthcare professionals to objectively assess the progression of the patient's cough.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 245
• Est. completion date: June 11, 2025
• Est. primary completion date: September 11, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 2 Years and older

Eligibility

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.

Related Conditions & MeSH terms

• Asthma
• Chronic Obstructive Pulmonary Disease
• Cough
• Gastro Esophageal Reflux
• Gastroesophageal Reflux
• Idiopathic Pulmonary Fibrosis
• Lung Diseases, Obstructive
• Pulmonary Disease, Chronic Obstructive
• Pulmonary Fibrosis

Intervention

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

Locations

Country	Name	City	State
Portugal	HFF - Hospital Professor Doutor Fernando Fonseca	Amadora
Portugal	NMS Research - Laboratório de Exploração Funcional | Fisiopatologia	Lisboa
Portugal	CHUSJ - Centro Hospitalar Universitário de São João	Porto

Sponsors (2)

Lead Sponsor	Collaborator
Cough Monitoring Medical Solutions	Universidade Nova de Lisboa

Country where clinical trial is conducted

Portugal, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Relation between cough characteristics and target diseases	Compare each indicator (cough frequency, type, intensity, presence of wheeze, and cough patterns) amongst the diseases observed in the study's sample. This will be performed using multivariate analysis of variance (MANOVA).	24 hours
Primary	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
Primary	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
Primary	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
Primary	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
Primary	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
Primary	Cough characterisation (Cohen's Kappa)	Measure C-mo System's performance and ability to automatically characterise cough using Cohen's Kappa coefficient (?). The ? 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
Primary	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
Primary	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
Primary	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
Primary	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 (?). The ? 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
Primary	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
Primary	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 (?). The ? 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
Primary	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
Primary	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 (?). The ? 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	Cough intensity	Analyse the collected EMG signal to describe cough intensity, as percentage of maximum voluntary contraction (MVC).	24 hours
Secondary	Cough patterns	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).	24 hours
Secondary	Usability results	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.	24 hours
Secondary	Cough perception vs. C-mo System analysis, in relation to gold standard (expert evaluation)	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).	24 hours