Aiding Clinical Decision-Making at the Individual and Community Level Using Mobile Sensor Data: Study Protocol for an...

Area of Science:

• Digital Health and mHealth
• Biomedical Engineering
• Clinical Informatics

Background:

• Mobile sensor data, particularly from accelerometers, offers insights into patient behavior and physical activity.
• Underutilization of smartphone sensor data stems from a lack of awareness and clear usage guidelines.
• Accelerometer data can inform interventions for sedentary lifestyles and improve clinical decisions for related diseases.

Purpose of the Study:

• To investigate and promote the use of mobile accelerometer sensor metadata for physical activity interventions.
• To establish foundational guidelines for utilizing mobile accelerometer data in patient activity monitoring and clinical decision support.
• To enhance adherence to physical activity plans through remote monitoring and clinician messaging.

Main Methods:

• Sequential explanatory mixed-method research design (July 2023 - December 2024).
• Screening individuals (30-45 years) with lifestyle-related diseases for sedentary behavior.
• Collecting physical activity accelerometer data, creating individualized plans, and monitoring over three months with clinician messaging.

Main Results:

• Exploration of remote sensor data monitoring's role in improving adherence to prescribed physical activity plans.
• Identification of variables influencing remote data collection monitoring.
• Assessment of improvements in physical activity levels through remote monitoring.

Conclusions:

• Development of a protocol to improve physical activity in sedentary patients with hypertension and type 2 diabetes.
• Leveraging remote mobile sensor data, messaging, and clinical decision-making for health improvement.
• Establishing a framework for effective remote patient monitoring and intervention delivery.