Sensors for HEalth Recording and Physical Activity Monitoring (SHERPAM)
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Bretagne
-
Rennes, Bretagne, France, 35000
- Unité de Biologie et médecine du Sport
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
Healthy volunteers Healthy active subjects aged 50 or over (ie without diagnosed disease, without chronic treatment) and recruited in the sports associations of Ille et Vilaine (cycle tourism clubs).
- having benefited from an oral or written prescription of physical activity carried out by a health professional and applying this prescription daily in autonomy or in a sports club.
Common to all subjects
- physically active (adherent to a club or sports association or practicing independently according to the recommendations of their physician);
- practicing at least once a week;
- residence located less than 100 km return from Rennes University Hospital
- affiliate or beneficiary of a social protection scheme;
- having given his written consent
Exclusion Criteria:
Common to all subjects
- wearing a pacemaker or implanted cardiac defibrillator (precaution because using telemetry);
- participation in another research protocol;
- persons aver 18 yrs-old subject to legal protection (legal safeguards, guardianship, tutorship), persons deprived of their liberty;
- pregnant or nursing woman.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Device Feasibility
- Allocation: Non-Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Experimental: Healthy volunteers
Sensors assigned for 3 weeks
|
Acquisition and transmission of exploitable recordings in the public targeted by the DS, that is to say which allow to draw clinical information in relation to the objectives of the DS (detection of the cardiac rhythm): data without artefact (saturation), in a good signal to noise ratio.
|
|
Experimental: Patients with arythmic disease or peripheral vascular disease
Sensors assigned for 3 weeks
|
Acquisition and transmission of exploitable recordings in the public targeted by the DS, that is to say which allow to draw clinical information in relation to the objectives of the DS (detection of the cardiac rhythm): data without artefact (saturation), in a good signal to noise ratio.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
asses the continuous acquisition of data by sensors
Time Frame: every day (during 3 weeks)
|
transmission and reception of physiological parameters of a patient
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every day (during 3 weeks)
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Test acceptability of SHERPAM Device
Time Frame: after 7 days of use
|
questionnary
|
after 7 days of use
|
|
Test acceptability of Sherpam Device
Time Frame: after 21 days of use
|
questionnary
|
after 21 days of use
|
|
Test usability of Sherpam Device
Time Frame: after 7 days of use
|
questionnary
|
after 7 days of use
|
|
Test usability of Sherpam Device
Time Frame: after 21 days of use
|
questionnary
|
after 21 days of use
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Carre François, MD, Rennes University
Publications and helpful links
General Publications
- Houssein A, Ge D, Gastinger S, Dumond R, Prioux J. Estimation of respiratory variables from thoracoabdominal breathing distance: a review of different techniques and calibration methods. Physiol Meas. 2019 Apr 3;40(3):03TR01. doi: 10.1088/1361-6579/ab0b63.
- Dumond R, Gastinger S, Rahman HA, Le Faucheur A, Quinton P, Kang H, Prioux J. Estimation of respiratory volume from thoracoabdominal breathing distances: comparison of two models of machine learning. Eur J Appl Physiol. 2017 Aug;117(8):1533-1555. doi: 10.1007/s00421-017-3630-0. Epub 2017 Jun 13.
- Khreis S, Ge D, Rahman HA, Carrault G. Breathing Rate Estimation Using Kalman Smoother With Electrocardiogram and Photoplethysmogram. IEEE Trans Biomed Eng. 2020 Mar;67(3):893-904. doi: 10.1109/TBME.2019.2923448. Epub 2019 Jun 17.
Helpful Links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
Other Study ID Numbers
- 35RC17_8836
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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