Lack of enrollment

The proposed study seeks to assess the performance of continuous biosensor data and machine learning analytics in assessment of health patient status in a pulmonary rehabilitation program.

It is hypothesized that using continuous physiologic biosensor data and machine learning analytics to detect changes in physiology may play a role in managing patients in the pulmonary rehabilitation setting.

Inclusion Criteria:

• Male or female, at least 40 years of age;
• Diagnosis of Chronic Obstructive Pulmonary Disease (COPD);
• Enrolled in the study site's 12-week pulmonary rehabilitation program;
• Capable of completing a 6-minute walk test;
• Willing and able to comply with scheduled protocol procedures and follow up;
• Signed and dated informed consent and HIPAA materials indicating that the patient has agreed to participate in this study and has been informed of all pertinent aspects of the trial.

Exclusion Criteria:

• Patient has cognitive or physical limitations that, in the opinion of the investigator, limit the patient's ability to utilize the System as instructed;
• Patient is actively enrolled in another clinical investigation that, in the opinion of the investigator, interferes with or compromises either that patient's ability to participation in this study or the ability for the study to generate results;
• Patients who have implanted defibrillators or pacemakers;
• Patient is allergic to hydrocolloid adhesive;
• Patient does not speak English.

The study population will be patients diagnosed with COPD participating in a pulmonary rehabilitation program.