CoughC-mo_01NCT05989698
Validation of the C-mo System - Cough Monitoring
A study testing C-mo System in people with Cough and Asthma, run by Cough Monitoring Medical Solutions at 8 sites in Portugal.
Trial 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. Read more about this study
- Who is it for?
- Ages 2 years and older
- Conditions the study is for
- Cough, Asthma, Chronic Obstructive Pulmonary Disease
- What is being tested?
- C-mo System
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 300 participants
- Where
- 8 sitesPortugal
- Study dates
- 11 Dec 2023to Sep 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 2 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- 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).
Who cannot join
- 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.
Trial locations and contacts
8 sites in 1 country. Contact the study team or a site near you to ask about taking part.
8 sites in 1 country
Portugal8 sites, 7 recruiting
- Recruiting
HPAV - Trofa Saúde Hospital de Alfena
Alfena
Daniela Rodrigues
- Recruiting
HFF - Hospital Professor Doutor Fernando Fonseca
Amadora
José Pedro Boléo-Tomé
- Completed
Lab3R - Laboratório de Investigação e Reabilitação Respiratória da Escola Superior de Saúde da Universidade de Aveiro
Aveiro
- Recruiting
CHUC - Centro Hospitalar e Universitário de Coimbra
Coimbra
Pedro Gonçalo Ferreira
- Recruiting
HDE - Hospital Dona Estefânia
Lisbon
Raquel Lopes de Bragança
- Recruiting
NMS Research - Laboratório de Exploração Funcional | Fisiopatologia
Lisbon
Nuno Neuparth
- Recruiting
CHUSJ - Centro Hospitalar Universitário de São João
Porto
David Araújo
- Recruiting
ICUFP - Instituto CUF Porto
Porto
João Carlos Winck
About this study
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:
Read more
- Can C-mo System detect cough events? (automatic cough detection)
- 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.
- Conditions
- Cough, Asthma, Chronic Obstructive Pulmonary Disease, Gastro Esophageal Reflux, Idiopathic Pulmonary Fibrosis, Cough Frequency
- Being tested
- C-mo System
- Keywords
- Cough monitoring, Cough detection, Cough assessment, C-mo
- Medical subject headings
- Cough, Asthma, Pulmonary Disease, Chronic Obstructive, Gastroesophageal Reflux, Idiopathic Pulmonary Fibrosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
C-mo SystemDevice
Patients will use C-mo System for a period of 24h, to assess cough characteristics.
| Study group | Role | What they receive |
|---|---|---|
| C-mo System | Experimental | Not described Receives: Device: C-mo System |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 24 hours
Secondary outcomes (4)
Cough intensity
Analyse the collected EMG signal to describe cough intensity, as percentage of maximum voluntary contraction (MVC).
Measured: 24 hours
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).
Measured: 24 hours
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.
Measured: 24 hours
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).
Measured: 24 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Aug 2023
- Study start11 Dec 2023
- Primary completionJun 2026 (estimated)
- Study completionSep 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for CoughStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cough Monitoring Medical Solutions
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Universidade Nova de Lisboa
- Responsible party
- Sponsor
- Investigators
- Nuno M Neuparth, PhD, Principal investigator, NOVA Medical School | Faculdade de Ciências Médicas da Universidade Nova de Lisboa
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05989698
- Sponsor's protocol ID
- C-mo_01
- Acronym
- C-mo_01
- Status last verified
- Apr 2026
- First submitted
- 12 May 2023
- Last updated
- 8 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of the C-mo System - Cough Monitoring
- ClinicalTrials.gov ID
- NCT05989698
- Acronym / sponsor ID
- C-mo_01 / C-mo_01
- Conditions
- Cough, Asthma, Chronic Obstructive Pulmonary Disease, Gastro Esophageal Reflux, Idiopathic Pulmonary Fibrosis, Cough Frequency
- Keywords
- Cough monitoring, Cough detection, Cough assessment, C-mo
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- Cough Monitoring Medical SolutionsIndustry (pharma, biotech, devices)
- Collaborators
- Universidade Nova de Lisboa
- Study start
- 11 Dec 2023 (actual)
- Primary completion
- Jun 2026 (estimated)
- Study completion
- Sep 2026 (estimated)
- First posted
- 14 Aug 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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:
- Can C-mo System detect cough events? (automatic cough detection)
- 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.
Study design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| C-mo System | Experimental | Device: C-mo System |
Who may qualify
- Ages
- 2 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (3 listed)
- 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).
Key exclusion criteria (3 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| C-mo SystemPatients will use C-mo System for a period of 24h, to assess cough characteristics. | Device | C-mo System |
Primary outcome
Cough detection (precision and recall)
Time frame: 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)
Time frame: 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)
Time frame: 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 (F1-score)
Time frame: 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)
Time frame: 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 characterisation (Cohen's Kappa)
Time frame: 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.
Wheezing detection (precision, recall, true negative rate, accuracy, and negative predictive value)
Time frame: 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)
Time frame: 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 (Matthews correlation coefficient)
Time frame: 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 frequency (Cohen's Kappa Index)
Time frame: 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.
Cough type percentage (Matthews correlation coefficient)
Time frame: 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)
Time frame: 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 (Matthews correlation coefficient)
Time frame: 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)
Time frame: 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.
4 secondary outcomes
Cough intensity
Time frame: 24 hours
Cough patterns
Time frame: 24 hours
Usability results
Time frame: 24 hours
Cough perception vs. C-mo System analysis, in relation to gold standard (expert evaluation)
Time frame: 24 hours
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Apr 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Nuno M Neuparth, PhD principal investigator
NOVA Medical School | Faculdade de Ciências Médicas da Universidade Nova de Lisboa
8 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing C-mo System in people with Cough and Asthma, run by Cough Monitoring Medical Solutions at 8 sites in Portugal.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 8 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 8 sites in Portugal. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Diogo B Tecelão, MSc (+351 917 935 447, diogo.tecelao@c-mo.solutions), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Cough detection (precision and recall) (time frame: 24 hours). The study lists 14 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Apr 2026.