Mobile Sensor Devices and Exercise Decision-Making Support System for Patients With Chronic Obstructive Pulmonary Disease

Purpose: Chronic obstructive pulmonary disease (COPD) is a major public health problem and is currently the third leading cause of death worldwide. Physical inactivity appears to be more common in patients with COPD compared with age-matched healthy individuals. A sustained low level of physical activity and declined function capacity over time is associated with an accelerated progression of exercise intolerance and declined quality of life in patients with COPD. Pulmonary rehabilitation has been identified as the best available means of improving muscle function and exercise tolerance in patients with COPD. However, pulmonary rehabilitation provided by hospitals might not be available for every patient. COPD symptoms are very much affected by the environmental conditions of the location of the patient. Symptoms of breathlessness and fatigue during physical activities are associated with activity-avoiding behaviors that may, in turn, exacerbate the experienced symptoms due to deconditioning. Recently, utilizing wearable devices is gaining in popularity for improving individual’s physical activity and health behavior. However, the application of care-related mobile technology in people with chronic conditions in the home and community settings is still underdeveloped. The major purpose of this study was to develop an integrated system, which will improve daily physical activity of COPD patients in stable condition.

Methods: This system consisted of wearable physiological sensors (heart rate and SPO₂), mobile environmental detectors (temperature, humidity, ultraviolet, and atmospheric particulate matter) combined with a mobile phone App of exercise-decision support system to assist COPD patients exercising in a safe environment. The mobile phone App running by the Android operating system was developed to provide patients with pre-exercise assessment (based on the data of physiological and environmental conditions), physical activity guidance related to a personal goal, real-time monitoring, and feedback. The users can monitor their exercise levels from their mobile phone and transmit the information to the cloud computing system. The health care professionals can analyze the data to provide feedback and counseling for the individual patient, and to facilitate a supportive environment and empowering patients’ exercise behaviors.

Results: Pilot studies will be designed to test the usefulness of the invented system. First, we evaluated the accuracy of the mobile sensors as well as physical activity measurement by the App. We began our first pilot study with 3 healthy adult volunteers in our research team who carried the environmental sensors in pouches and worn the physiological sensors armband and mobile phones during waking hours for one week. Usability of the App and rates of the technical problems were the key evaluation parameters and we adjusted the program of this system accordingly. A subsequent version then will be tested in a subset of patients with COPD to evaluate the feasibility and acceptance of the system for COPD users. Since COPD mostly affects older adults, special attention will be paid to readability and comprehensibility of the App. Finally, a larger group of patients with COPD will be invited to test the usefulness of the final version.

Conclusion: Although various mobile health technology are available that stimulate engagement in physical activity, none of the mobile devices and Apps met the requirements that are needed to support the personalized decision of physical activity in COPD patients. Therefore, we hope that the exercise decision support system developed in this study can be taken into consideration for the initial design of an integrated care system of COPD patients to enable their physical activity at home.